# NOTE: this file was automatically generated on 2023-04-04, # and contains IDs of all videos from the MIT OpenCourseWare # YouTube channel, at that date. # # You can generate an up-to-date list, or a list of available playlists, # for this channel or any others, using the code at: # https://tales.mbivert.com/on-youtube-api-golang/ # # First column is the video ID, from which you can generate # an URL from. e.g. from ID # eFX04wkGZ3Y # the corresponding URL is: # https://www.youtube.com/watch?v=eFX04wkGZ3Y # # Second column is an arbitrary counter, and everything after # is the video title. # eFX04wkGZ3Y 0 Lecture 18: Case Hx: Cancer Diagnostics 0XUW8l1Dzyc 1 Lecture 7: Informational Resources 0tI1CRv-DPs 2 Lecture 20: Practical Genomic Medicine 9KNmqar0Dd8 3 Lecture 8: Complex Traits: What to Believe GzGed-6NIBY 4 Lecture 6: Information Science at the Center of Genomic Medicine LvI6V3VbL9Q 5 Lecture 3: Measurement Techniques O8gzYz51K9I 6 Lecture 17: Direct Prediction of Outcome / Mortality VSSF1LCnE20 7 Lecture 4: Microarray - Massively Parallel Measurement X_6i7j_TDVU 8 Lecture 1: Genomic Introduction _-gQchCLmXk 9 Lecture 9: Machine-learning Approach aDIvhuNrWO4 10 Lecture 5: Limits of Technologies aQ2SuAHFE5w 11 Lecture 16: Microarray Disease Classification II dcVU_uELhGU 12 Lecture 15: Microarray Disease Classification na4fKtOHxFI 13 Lecture 12: Pharmacogenomics pHJzX2noZxs 14 Lecture 19: Modeling and Reverse Engineering wr5BT78iYa4 15 Lecture 11: The Importance of Data Representation 90xRzK69EuM 16 Lecture 10: Association with Markers izl46nTo1ng 17 Lecture 13: Case Hx: Complex Traits yDy3L7V-tL8 18 Lecture 2: Introduction to Biology and Genomic Measurement 7i5fpNGMMhA 19 S4 E6: Teaching Teachers with Dr. Summer Morrill q7WZdYAaVtQ 20 Video 5: Kanji in Tobira Lesson 5 TxKzqbpLi0Y 21 Video 4: Kanji in Tobira Lesson 4 _FtXi0_ZMvk 22 Video 1: Kanji in Tobira Lesson 1 3N1A14hQjZA 23 Video 3: Kanji in Tobira Lesson 3 zZlD3c_1PLg 24 Video 2: Kanji in Tobira Lesson 2 NgaW_p7gsRc 25 Ethics of AI Bias jejZMh_-geI 26 S4E5: Communication is the Whole Game with Paige Bright and Prof. Haynes Miller Ad4HmoAkgBo 27 S4:E4: Opening Computer Science to Everyone with Chancellor Eric Grimson 2QZUwB6F6Zw 28 Lecture 4: Computational Illumination: dual photography, relighting - Part 1 hnAqRae1nTM 29 Lecture 8: Project ideas discussion wbI3VXsOJ6k 30 Lecture 6: Recent research: BiDi Screen LP085DG79lU 31 Lecture 5: Recent research: Retrographic Sensing for the Measurement of Surface Texture and Shape wHeJbvRoj00 32 Lecture 8: Wavelengths and colors Br1zazcSI4M 33 Lecture 1: Introduction and fast-forward preview of all topics - Part 1 tnmQ8gytqyc 34 Lecture 5: Lightfields, part 1 - Part 2 aWLS9GE3elo 35 Lecture 9: "Cameras We Cannot Picture": a survey of the computational imaging field wP-1t-djakw 36 Lecture 3: Epsilon Photography: Improving Film-like Photography QG8SNZ4jGbw 37 Lecture 6: Cameras for human-computer interaction (HCI) B3AUmClsJiA 38 Lecture 2: Modern optics and lenses; ray-matrix operations; context enhanced imaging - Part 2 H2zauvCW-to 39 Lecture 8: Survey of Hyperspectral Imaging Techniques qW--3_vX1Aw 40 Lecture 6: Lightfields, part 2 xbDqd-dVVb0 41 Lecture 3: Single-shot Multi-domain Camera tpfRoPZZrjI 42 Lecture 4: Computational Illumination: dual photography, relighting - Part 2 s_2w1gY1K4M 43 Lecture 2: Modern optics and lenses; ray-matrix operations; context enhanced imaging - Part 1 Xrsk2Avd3Xc 44 Lecture 11: Coded imaging 8autJMHEzBU 45 Lecture 1: Introduction and fast-forward preview of all topics - Part 2 x-ijexq_D2U 46 Lecture 9: Computational imaging: a survey of medical and scientific applications h4-GpUrdi1M 47 Lecture 5: Lightfields, part 1 - Part 1 xHNIknabsRY 48 1-1: Introduction, Overview, and Syllabus for Game Design DF9fniCnL10 49 14. Adding and Cutting Mechanics S_fiR00UBGo 50 2-1: Meaningful Decisions in Gameplay VXQAhzat098 51 22. Changing Rules I -Fd6JJ1Xkt4 52 17. Guest Lectures by Professional Designers 1_t7ixz5XRY 53 11. Defining Game, Play, and Sport FC_eWZp7a4E 54 3-2: Altering Rules & Playtesting H0MFJwQH2fo 55 4. Mechanics, Dynamics, Aesthetics - The MDA Framework JK29_2fW-w4 56 16. The Simulation Gap & Assignment 3 Pitches K3QfVXBqbYM 57 23. Changing Rules II OSlcaoq80Xs 58 2-2: Brainstorming RWSypiENYfc 59 5. Imperfect Information and Dice SUcIAQTu-Ts 60 20. Cooperative Games Uq0zx1Hy9Jw 61 10. History of American Board Games Ym5M_EQuNmU 62 3-1: Prototyping _bjy6AMn5aY 63 7. Aesthetics and Player Experience _yMU8qMSKzw 64 21. Social Play bgeWfB0SNEg 65 19. Space Control cZkKaqj9K1U 66 15. Assignment 3 dK55mOcHdAc 67 1-2: Game Mechanics fN1uPAtLatY 68 24. Indie Games and Aesthetics with Jesper Juul hM5erRmEzCk 69 9. Randomness and Player Choice w56ICZB3IfI 70 6. Constraints and Usability wmoKns-IQ-E 71 13. Cybernetics and Multiplayer po0oVE5Lhf0 72 S4:E3: Seeing Green with Drs. Jessica Sandland and Cécile Chazot Mvy5hjAWeZw 73 Lecture 2: Morphology, Part 1 12UWP2ZhUl0 74 Lecture 26: Signed Languages vxOO8cIn398 75 Lecture 4: Morphology, Part 3 xZ8mnJPu95Q 76 Lecture 5: Phonetics, Part 1 6QRlpk8ZmPI 77 Lecture 22: Dialects NfD6QNY6Zzg 78 Lecture 3: Morphology, Part 2 SyM5j0SeDRQ 79 Lecture 8: Phonology, Part 1 ruzcPdSyn8o 80 Lecture 16: Syntax, Part 6 vWC6Q3Dv1ws 81 Lecture 19: Semantics, Part 3 UXG4JImev-s 82 Lecture 18: Semantics, Part 2 qb1U3_Q-7o8 83 Lecture 10: Phonology, Part 3 caLQIEeYpEk 84 Lecture 25: Language Acquisition q7pPG7V2ack 85 Lecture 11: Syntax, Part 1 LOsNklq-dH8 86 Lecture 24: Endangered Languages TgwDg_svSnM 87 Lecture 14: Syntax, Part 4 msSCIvkjbHI 88 Lecture 21: Semantics, Part 5 NVQWWXhbUvs 89 Lecture 6: Phonetics, Part 2 5itfLAwQol8 90 Lecture 23: Historical Linguistics Di8e2opeGA0 91 Lecture 17: Syntax, Part 7, and Semantics, Part 1 -OeyjP2zri4 92 Lecture 12: Syntax, Part 2 4ndEWbwbIrA 93 Lecture 13: Syntax, Part 3 wrcQ5wUVxd0 94 Lecture 15: Syntax, Part 5 VymHeBjublw 95 Lecture 20: Semantics, Part 4 -Pg11JHzUTo 96 Lecture 9: Phonology, Part 2 4GiPsGjGVVM 97 S4:E2: Wellbeing is the Goal with Prof. Frank Schilbach _Y-G8sTTYsg 98 S4:E1: The Greatest Existential Threat with Prof. Robert Redwine and Dr. Jim Walsh -htdFMTbPvg 99 From Open Access to Educational Equity: An HBCU+MERLOT+MIT OCW Collaboration A1vOpAxkuZ4 100 Guest lecture (2022): Unmaking and remaking community (part 2) qU8Wi_KHH1E 101 Guest lecture (2022): Unmaking and remaking community (part 1) EBdgFFf54U0 102 Lecture 14: Basic Hilbert Space Theory PBMyBVPRtKA 103 Lecture 19: Compact Subsets of a Hilbert Space and Finite-Rank Operators SFDMFbzCsH0 104 Lecture 20: Compact Operators and the Spectrum of a Bounded Linear Operator on a Hilbert Space TXMCTAF6SEE 105 Lecture 10: Simple Functions BctaYoR9tOY 106 Lecture 18: The Adjoint of a Bounded Linear Operator on a Hilbert Space BYR1fXW95zY 107 Lecture 13: Lp Space Theory O0Tw47okZJM 108 Lecture 21: The Spectrum of Self-Adjoint Operators and the Eigenspaces of Compact Self-Adjoint... KcI2_r51Eb8 109 Lecture 17: Minimizers, Orthogonal Complements and the Riesz Representation Theorem QTg7040uSc0 110 Lecture 23: The Dirichlet Problem on an Interval W2pw1JWc9k4 111 Lecture 12: Lebesgue Integrable Functions, the Lebesgue Integral and the Dominated Convergence... KlAjiDivJoQ 112 Lecture 5: Zorn’s Lemma and the Hahn-Banach Theorem Yb69dAq4uh8 113 Lecture 15: Orthonormal Bases and Fourier Series -sfaHVFWBU8 114 Lecture 22: The Spectral Theorem for a Compact Self-Adjoint Operator ETmIxkbTm3I 115 Lecture 9: Lebesgue Measurable Functions pWs93gASTJk 116 Lecture 6: The Double Dual and the Outer Measure of a Subset of Real Numbers G3mAXHuoDSw 117 Lecture 4: The Open Mapping Theorem and the Closed Graph Theorem OHiu2F18dFA 118 Lecture 7: Sigma Algebras 78vN4sO7FVU 119 Lecture 2: Bounded Linear Operators 58B5dEJReQ8 120 Lecture 3: Quotient Spaces, the Baire Category Theorem and the Uniform Boundedness Theorem ZWzCHjN3_3s 121 Lecture 11: The Lebesgue Integral of a Nonnegative Function and Convergence Theorems cqdUuREzGuo 122 Lecture 8: Lebesgue Measurable Subsets and Measure 8IxHMVf3jcA 123 Lecture 16: Fejer’s Theorem and Convergence of Fourier Series uoL4lQxfgwg 124 Lecture 1: Basic Banach Space Theory WXshIwISJ5Y 125 Learn Climate with Open MIT Resources pjBsOFUNN34 126 Unit 2: The Forecast is ‘Always’ wrong, Video 2: Demand Forecasts cF6he3JbWbs 127 Unit 10: Utility Analysis and Multidimensional Evaluation, Video 1: Is Optimization Possible? 8DlysThtgbM 128 Unit 8: Decision Analysis 5 Video 5: Retrospective Overview JDmNvQj0I5A 129 Unit 5: Mechanics of Simulation, Video 5: Physical Situation 9w73uiDyLHo 130 Unit 4: Parking Garage Case Example, Video 5: Design to Manage Uncertainties Ju2WGx363_Q 131 Unit 2: the Forecast is always wrong, Video 1: Cost Estimates M8kt-t6CKRI 132 Unit 4: Parking Garage Case Example, Video 2: Logic of Analysis 7UNiSHGyg1Q 133 Unit 11: LNG Case 1, Video 2: Introduction xKnBPAcwx4I 134 Unit 2: The Forecast is "Always" wrong, Video 4: Common Forecasting Process Inherently Flawed dp-ZTe9jn48 135 Unit 7: Drivers of Flexibility, Video 2: Economies of Scale Lk-4waYYz68 136 Unit 10: Utility Analysis and Multidimensional Evaluation, Video 4: Consequences EKBX3PB7DYg 137 Unit 8: Decision Analysis 1, Video 1: Advantages ErZpH8eUB1Q 138 Unit 9: Value of Information 5, Video 5: Is Test Worthwhile? zzsfHbb-Xq0 139 Unit 5: Mechanics of Simulation, Video 7: Value of Flex "in" Project bEF_PpP6eCM 140 Unit 5: Mechanics of Simulation, Video 3: Outcomes and Target Curves 93-dFNci-2A 141 Unit 10: Utility Analysis and Multidimensional Evaluation, Video 5: There's No Valid Group Utility FhK9O1yn9jU 142 Unit 11: LNG Case 4, Video 5: Final Analysis QdE66s-3BNw 143 Unit 2: The Forecast is Always wrong, Video 3: Porcupine Graphs OMdmcfA1MDU 144 Unit 2: The Forecast is Always wrong, Video 6: Flaw of Averages 2-the Consequences nSPZP92vWsE 145 Unit 2: The Forecast is Always wrong, Video 5: Flaw of Averages 1-the Concept ULmjdacV_aw 146 Unit 11: LNG Case 3, Video 4: Learning effects L_aENIg6tJk 147 Unit 5: Mechanics of Simulation, Video 1: Concept—What Is Needed 1VoDpRYS7GM 148 Unit 10: Utility Analysis and Multidimensional Evaluation, Video 6: Dominated Solutions RhMdeFIw1rM 149 Unit 9: Value of Information, Video 2: Value of Test 0CIdzHHvUjQ 150 Unit 10: Utility Analysis and Multidimensional Evaluation, Video 3: Conditions for Value Function xW4TJHhKZiY 151 Unit 10: Utility Analysis and Multidimensional Evaluation, Video 2: Diminishing Marginal Utility Kwg7x9LFsDc 152 Unit 8: Decision Analysis 2, Video 2: Decision Trees piFTZQywm2A 153 Unit 9: Value of Information, Video 1: Concept of Test jl7wEsOZaU8 154 Unit 8: Decision Analysis 3, Video 3: Constructing Trees 1ona5jnRZgw 155 Unit 7: Drivers of Flexibility, Video 1: Five Main Drivers—Uncertainty is Most Important jMPc6-bcnH8 156 Unit 5: Mechanics of Simulation, Video 2: Recommended Process tXXRIwRBTTE 157 Unit 10: Utility Analysis and Multidimensional Evaluation, Video 7: Robustness and Take-aways x2Y9IdbVd9g 158 Unit 9: Value of Information, Video 3: Expected Value of Sample Information Vsxfd97trIk 159 Unit 9: Value of Information, Video 4: Expected Value of Perfect Information XZQxhZT5MaE 160 Unit 5: Mechanics of Simulation, Video 4: Decision Rules and Unit Closure WKW0dZ7Torg 161 Unit 4: Parking Garage Case Example, Video 3: Recognizing Uncertainty, Simulation 12K3PlcicZE 162 Unit 7: Drivers of Flexibility, Video 3: Discount rate and Learning Promote pLYdFdnWozo 163 Unit 5: Mechanics of Simulation, Video 6: Simulation and Value Flexibility "on" Project 12MkdZCr4iQ 164 Unit 4: Parking Garage Case Example, Video 1: Introduction razbxFM7cEQ 165 Unit 4: Parking Garage Case Example, Video 6: Flexibility is Win-Win SPDZbn6QC4c 166 Unit 4: Parking Garage Case Example, Video 4: Adding Flexibility itWklzE8MP0 167 Unit 11: LNG Case 2, Video 3: Initial Analysis zOqIHFqeRyI 168 Unit 8: Decision Analysis 4, Video 4: Multistage Analysis aY7d_-INloc 169 Unit 11: De-Salt and LNG Cases, Video 1: De-Salt Plant Australia lPCoJJHhFP4 170 Unit 7: Drivers of Flexibility, Video 4: Balancing Overall Effect of Drivers RcAkiv8Bkpo 171 S4:Trailer: Chalk Radio Season 4 Trailer wH9nO8_aDSI 172 Lecture 14: Resonance and the S-Matrix N3byulM6JJ8 173 Elephant Toothpaste Reaction h0IfCMqepfM 174 Lecture 16: Fundamental Welfare Theorems ySqVVEBTy2o 175 Lecture 21: Bubbles R8k2x5qJgO4 176 Lecture 14: Real and Financial Flows: Thailand ANprMjSgTZY 177 Exam #1 Review Dqko567cE9I 178 Final Exam Review 3X3b1GMniC4 179 Lecture 13: Walrasian Equilibrium and Trade rWnyP-iZGu4 180 Lecture 19: Identification and Falsification JZplGZVCdN8 181 Exam #2 Review rhOpABGewYA 182 Lecture 2: Consumer Choice FGxxnOLvSfg 183 Lecture 12: Contract Application, Obstacles DGoILxx9KsE 184 Lecture 3: Income and Substitution Effects XSTSfCs74bg 185 Lecture 1: Economic Science s0gfi3OrtQk 186 Lecture 5: Uncertainty and Linear Programs EK1pgrHeqpQ 187 Lecture 7: Pareto Optimality aaLDUlJXXNM 188 Lecture 6: Dynamics and Programming QcUUGlsSXmY 189 Lecture 9: Risk-Sharing with Production 6Tm4bHa28Ck 190 Lecture 8: Risk-Sharing Application lUqwzrkO5fw 191 Lecture 20: Failure of Welfare Theorems pAP1HKzueqc 192 Lecture 18: Aggregation 5rjoqINtRbs 193 Lecture 10: Ledgers and Management O5YwAGe8rmk 194 Lecture 15: Data and Policy in the United States cAFh3oWw6Vc 195 Lecture 11: Contracts and Mechanism Design o8sje-b-BCk 196 Lecture 4: Production and Profit Maximization eBb1BLE4am0 197 Lecture 17: Existence of Equilibria VVCE-6kmyBI 198 4B. DNA 2: Dynamic Programming, Blast, Multi-alignment, Hidden Markov Models lqfKi0Pkt6U 199 11B. Networks 3: The Future of Computational Biology: Cellular, Developmental, Social,... axiNLT3tkqg 200 6A. RNA 2: Clustering by Gene or Condition and Other Regulon Data Sources Nucleic Acid ... 2xONWF0XzOI 201 7A. Protein 1: 3D Structural Genomics, Homology, Catalytic and Regulatory Dynamics, Fun... qiz-ywBpQlo 202 5AB. RNA 1: Microarrays, Library Sequencing and Quantitation Concepts G4skPcnqWZ4 203 4A. DNA 2: Dynamic Programming, Blast, Multi-alignment, Hidden Markov Models _GRVq26jIHs 204 2B. Intro 2: Biological Side of Computational Biology. Comparative Genomics, Models & A... Qa7Xnn7ixpk 205 10A. Networks 2: Molecular Computing, Self-assembly, Genetic Algorithms, Neural Networks 0XjWRilFPQY 206 11A. Networks 3: The Future of Computational Biology: Cellular, Developmental, Social, E... dzGar1Jnf90 207 9B. Networks 1: Systems Biology, Metabolic Kinetic & Flux Balance Optimization Methods u3YMRDjX5Po 208 6B. RNA 2: Clustering by Gene or Condition and Other Regulon Data Sources Nucleic Acid ... l1hzzufdfCo 209 5C. RNA 1: Microarrays, Library Sequencing and Quantitation Concepts b11xP6rhn_I 210 8B. Protein 2: Mass Spectrometry, Post-synthetic Modifications, Quantitation of Protein... 3FVlVP5MKV4 211 3B. DNA 1 : Genome Sequencing, Polymorphisms, Populations, Statistics, Pharmacogenomics... WDUPvNCbLhs 212 3A. DNA 1: Genome Sequencing, Polymorphisms, Populations, Statistics, Pharmacogenomics... a5dXNyO3k0g 213 7B. Protein 1: 3D Structural Genomics, Homology, Catalytic and Regulatory Dynamics, Fun... g4Ype5QTf4s 214 8A. Protein 2: Mass Spectrometry, Post-synthetic Modifications, Quantitation of Protein... eMbKfsi_DwU 215 2A. Intro 2: Biological Side of Computational Biology. Comparative Genomics, Models & A... hWtSvemuN0Y 216 1A. Intro 1: Computational Side of Computational Biology. Statistics; Perl, Mathematica aMfIs9Qmm9Q 217 9A. Networks 1: Systems Biology, Metabolic Kinetic & Flux Balance Optimization Methods y0fDCN5rbMQ 218 1B. Intro 1: Computational Side of Computational Biology. Statistics; Perl, Mathematica cjeXg5rJ9D8 219 Lecture 13: Limits of Functions gv1aMp4YxyA 220 S3:E9: Visualizing Calculus with Prof. Gigliola Staffilani V3Wg_jrMSQY 221 Lecture 19: Differentiation Rules, Rolle's Theorem, and the Mean Value Theorem _HRTdXJgZ0Q 222 Lecture 23: Pointwise and Uniform Convergence of Sequences of Functions f_sNWn7zujU 223 Lecture 17: Uniform Continuity and the Definition of the Derivative QeYUHA0UMVg 224 Lecture 21: The Riemann Integral of a Continuous Function u4qQ1oIQcW8 225 Lecture 25: Power Series and the Weierstrass Approximation Theorem os_XGBNPllM 226 Lecture 8: The Squeeze Theorem and Operations Involving Convergent Sequences RzSp9nIFnbo 227 Lecture 11: Absolute Convergence and the Comparison Test for Series PnDtMfyZSIE 228 Lecture 6: The Uncountability of the Real Numbers smIcuRZybsA 229 Lecture 15: The Continuity of Sine and Cosine and the Many Discontinuities of Dirichlet's Function 0_w-R_g5lRA 230 Lecture 10: The Completeness of the Real Numbers and Basic Properties of Infinite Series ImHAGH_OEow 231 Lecture 20: Taylor's Theorem and the Definition of Riemann Sums ZjjpLMKs7Tc 232 Lecture 12: The Ratio, Root, and Alternating Series Tests gXPX29KfEc4 233 Lecture 24: Uniform Convergence, the Weierstrass M-Test, and Interchanging Limits PuRJ9IgUW-M 234 Lecture 18: Weierstrass's Example of a Continuous and Nowhere Differentiable Function dcUKdwHRSD8 235 Lecture 16: The Min/Max Theorem and Bolzano's Intermediate Value Theorem bBESL68iX6s 236 Lecture 14: Limits of Functions in Terms of Sequences and Continuity M2d4HsBsu8Y 237 Lecture 5: The Archimedian Property, Density of the Rationals, and Absolute Value nbENJ-Ce7Nc 238 Lecture 3: Cantor's Remarkable Theorem and the Rationals' Lack of the Least Upper Bound Property WWZ_CeiRnIo 239 Lecture 22: Fundamental Theorem of Calculus, Integration by Parts, and Change of Variable Formula mlPLLXHZ8_U 240 Lecture 4: The Characterization of the Real Numbers Xn8wL2ItzZw 241 Lecture 9: Limsup, Liminf, and the Bolzano-Weierstrass Theorem 9_xG0AGRa-w 242 Lecture 2: Cantor's Theory of Cardinality (Size) 49Ro2zf9hAc 243 Lecture 7: Convergent Sequences of Real Numbers LY7YmuDbuW0 244 Lecture 1: Sets, Set Operations and Mathematical Induction Mcy-LlcD8jI 245 Lecture 20: Space of Rotations, Regular Tessellations, Critical Surfaces, Binocular Stereo lVfm6C51t_Y 246 Lecture 13: Object Detection, Recognition and Pose Determination, PatQuick (US 7,016,539) J4gbaRyWpoM 247 Lecture 9: Shape from Shading, General Case - From First Order Nonlinear PDE to Five ODEs uiG6KY0Cqd8 248 Lecture 18: Rotation and How to Represent It, Unit Quaternions, the Space of Rotations XSUjp-cDyeY 249 Lecture 10: Characteristic Strip Expansion, Shape from Shading, Iterative Solutions s9wu_z8EKAc 250 Lecture 23: Gaussian Image, Solids of Revolution, Direction Histograms, Regular Polyhedra LP7z6vVmnms 251 Lecture 8: Shading, Special Cases, Lunar Surface, Scanning Electron Microscope, Green's Theorem R1yLwFOfwwc 252 Lecture 15: Alignment, PatMax, Distance Field, Filtering and Sub-Sampling (US 7,065,262) 6SvDRpQeZrA 253 Lecture 14: Inspection in PatQuick, Hough Transform, Homography, Position Determination, Multi-Scale SSlPV1iYjHw 254 Lecture 5: TCC and FOR MontiVision Demos, Vanishing Point, Use of VPs in Camera Calibration -n0cXgPSwOw 255 Lecture 21: Relative Orientation, Binocular Stereo, Structure, Quadrics, Calibration, Reprojection R8O0vlHBeNc 256 Lecture 17: Photogrammetry, Orientation, Axes of Inertia, Symmetry, Orientation tblzZhYZtvU 257 Lecture 16: Fast Convolution, Low Pass Filter Approximations, Integral Images (US 6,457,032) uM5AoUgCA00 258 Lecture 2: Image Formation, Perspective Projection, Time Derivative, Motion Field 3NarS3QpaU0 259 Lecture 4: Fixed Optical Flow, Optical Mouse, Constant Brightness Assumption, Closed Form Solution jLvgNmGuxGk 260 Lecture 12: Blob Analysis, Binary Image Processing, Green's Theorem, Derivative and Integral OOrT17RsVxE 261 Lecture 6: Photometric Stereo, Noise Gain, Error Amplification, Eigenvalues and Eigenvectors Review kjCQ2DUn55Y 262 Lecture 11: Edge Detection, Subpixel Position, CORDIC, Line Detection (US 6,408,109) tY2gczObpfU 263 Lecture 1: Introduction to Machine Vision qqtEQsBjh28 264 Lecture 7: Gradient Space, Reflectance Map, Image Irradiance Equation, Gnomonic Projection t9w_WuyVJ-A 265 Lecture 3: Time to Contact, Focus of Expansion, Direct Motion Vision Methods, Noise Gain kigLhcTm_gg 266 Lecture 19: Absolute Orientation in Closed Form, Outliers and Robustness, RANSAC x4F1oqm7ETk 267 Lecture 22: Exterior Orientation, Recovering Position & Orientation, Bundle Adjustment, Object Shape RhX6iLDpjEQ 268 9: Case Studies (cont.): News Articles tDQ92vMd4Ww 269 19: Safety; Introduction to Narrative Ethics jsyn9UM7obo 270 22: Public Seminar on Narrative Ethics zPGh2bBeIgM 271 17: Recap of Semester so Far; Introduction to Codes of Ethics YFR7UjIy1k8 272 15: Leadership in Engineering and Industry 2AuvCEep4Jc 273 4: Introduction to Philosophy of Engineering I 2PP1QHvBECo 274 16: Competency with Good Character nYNTRl_Hx1c 275 12: First Principles of Engineering Ethics iCexjSqjmDE 276 21: Planning for Public Seminar; Terminology (cont.) XUFJ8iuxfCI 277 24: Student Presentation NBGQy52ubL4 278 10: Case Studies: Chernobyl, Three Mile Island (cont.) 6_SjvA75hqU 279 7: Case Studies: Finish Challenger Case; Ford Pinto Case rid0pVnuDjM 280 6: Introduction to Engineering Ethics: Codes of Ethics, Whistle Blowing, Case Study Methodology Qyqcvh7wDH0 281 3: Introduction to Ethics II; Initial Discussion of B. F. Goodrich Case MsJ31I9umCM 282 14: Individual, Professional, and Institutional Values duLYiTXjofU 283 11: Case Studies: B. F. Goodrich A7D Air Force Brakes iB6SuG7wh5U 284 5: Introduction to Philosophy of Engineering II dT3WhWLi2wI 285 20: Ethical Terminology -dAgY_AMqGk 286 8: Case Studies: Chernobyl, Three Mile Island wKhhpELFyZo 287 23: Human Flourishing Het_nd5x4hs 288 18: Codes of Ethics (cont.) 4N68XQDT38c 289 13: Solving Ethical Problems: Discussion of Heroes, Journeys, and Virtue in Mythology KsHOdr5UYZ0 290 AI 101 with Brandon Leshchinskiy rUl9X6CROTA 291 Lecture 12: Spinal Cord; Autonomic NS BbfTs2o_oHE 292 Lecture 15: Development of CNS, Introduction tAmMHp9vk90 293 Lecture 14: Midbrain and Forebrain 6SGBOZM842A 294 Lecture 23: Rhythms of Activity; Sleep and Waking _gsDTzOpiKo 295 Lecture 19: Motor System, 1 RGSQq7x04p8 296 Lecture 25: Habituation, Novelty Responses Lo_LSZ_R1w4 297 Lecture 09: Evolution (cont.); Reflex and Cerebellar Channels 4KkQ_hICRUs 298 Lecture 13: Hindbrain and Midbrain jR3ac6vHBMw 299 Lecture 28: Visual System 3: Ablation Studies kUtvTc_d_q0 300 Lecture 27: Visual System 2: Physiology (orig: Ablation Effects); Neville Sanjana, Guest lecturer lj66CYRmuNU 301 Lecture 17: Influences on Axon Growth XS1SEINTLy0 302 Lecture 1: Introduction to Brain-behavior Studies k2IFe0n3uvI 303 Lecture 11: Transection Effects; Neocortex IER0CBHl1qs 304 Lecture 26: Visual System 1: Anatomy, Ablations RfRFUizZqTc 305 Lecture 10: Brain Subdivisions; Channels of Conduction 945Cm4obJ5o 306 Lecture 21: Motor System, 3 8Okyz-5hal0 307 Lecture 20: Motor System, 2 iTgy87R9yRE 308 Lecture 3: History and Goals, III KZMHfXW5UwU 309 Lecture 22: Motor 4: Rhythmic Outputs ka0HFtUAxZg 310 Lecture 8: Introduction to CNS and its Evolution 0sY1vIwzrqM 311 Lecture 7: Synapses; Neuroanatomical Techniques ZyDUHHfPBZI 312 Lecture 2: History and Goals, II RSK0cVy0wDQ 313 Lecture 24: Sleep and Waking (cont.); Robert Thomas, M.D., Guest lecturer G9k_SnJH__c 314 Lecture 31: Auditory System 7b55QERrN1I 315 Lecture 29: Visual System 4: Ablations (cont.) (Orig: Electrophysiology) hRhGRuLLB1I 316 Lecture 16: Cell migration; Axon Growth Stages jttAlg60TXw 317 Lecture 4: History and Goals, IV Y-muIQlmKiE 318 Lecture 5: Cellular Mechanisms dq_GGoUqvRg 319 Lecture 18: Axonal Sprouting and Regeneration bA5_-EvxnL4 320 Lecture 6: Neuronal Conduction and Transmission ezy8j24Uric 321 S3:E8: Finding Expertise Everywhere with Prof. Amah Edoh ZyJIW569rww 322 Celebrating OCW's "NextGen" Platform with NPR's Anya Kamenetz uuEZdVPFA4E 323 The Next Generation of OCW is Here! Fj1OICPboCU 324 S3:E7: AI Literacy for All with Prof. Cynthia Breazeal bqBH2pq9fpA 325 How MIT OpenCourseWare and MITx helped Air Force veteran soar SU4RVM15Hfw 326 Save the date for the MIT 24-Hour Challenge! G6xsNP2TE3A 327 Lecture 7 Demonstration: Object Tracking: 1 Dot Slow | MIT 9.00SC Introduction to Psychology o8puRrvCHAc 328 Lecture 7 Demonstration: Object Tracking: 4 Dots Fast | MIT 9.00SC Introduction to Psychology tyRM_cSqbqQ 329 Lecture 7 Demonstration: Object Tracking: 4 Dots Slow | MIT 9.00SC Introduction to Psychology 8IOr7KejV_I 330 S3:E6: Making Ethical Decisions in Software Design with Prof. Daniel Jackson & Serena Booth kAeDRfk6A9w 331 Integrated Water Resources Management / The Water-Energy-Food Nexus brsHU2jA73E 332 The Confederated Salish-Kootenai Tribes - State of Montana Water Compact neBeTYziSLo 333 Singapore-Malaysia Water Conflict KmoodT_3XPQ 334 Enabling Conditions for Transboundary Water Agreements oqOtuChgsz4 335 The Past, Present and Future of the Columbia River Treaty: A Case for Modernization w2HASHQ8nYw 336 Ganges Water Conflicts between India and Bangladesh MbzbbvTlL1Y 337 S3:E5: The Human Element in Machine Learning w Catherine D’Ignazio, Jacob Andreas & Harini Suresh JFIaRtKNP2E 338 Part 6: Finding the Nullspace: Solving Ax = 0 by Elimination vCxqBgcLgNg 339 S3:E4: When There Isn’t a Simple Answer with Prof. Dennis McLaughlin Qf7qXw7sHk4 340 I believe in OpenCourseWare’s mission u-Ms5v20cVw 341 S3:E3: Learning about Life through Laboratory Chemistry with Drs. John Dolhun & Sarah Hewett ml4vCR0_4io 342 Using archives in the context of mobilization for the recognition of Belgium's colonial past f_0NSQj0Dyk 343 Bose AR Unity Workshop GwmkHdPUl_k 344 Student Project: 'Night Hunter' Q6i-gekn__8 345 Example Seminar Discussion (CMS.S63 Playful Augmented Reality Audio Design Exploration) hbBGpXBf3Ig 346 Student Project: 'Going in Blind' n7dryYNOA_U 347 Contributory Audio AR: Practice and Technology yaPEIFAb4W4 348 Student Project: 'INMUSE' fdZ7IFpSo_k 349 State's Responsibility for Historical Injustices before International Institutions / Courts b3szQPSRfjY 350 S3:E2: Re-engineering Education with VP for Open Learning Sanjay Sarma o-Yp8A7BPE8 351 System Dynamics: Systems Thinking and Modeling for a Complex World fEFMn64t76c 352 S3:E1: Sketching a Picture of the Mind with Prof. Nancy Kanwisher FwRj2DL5zIg 353 Chalk Radio - Season 3 (teaser) uMc-j5aQTH8 354 1.1 Course Organization (8.20 Introduction to Special Relativity) MVJzzWfAwNY 355 10.1 Tests of Special Relativity ka99Wu1VlVo 356 6.3 Spacecraft-on-a-Rope Paradox 0OnLn3Ito8o 357 10.6 Creation of Particles 0STE0476EOk 358 7.4 Galaxy Travel 0V93uTCjQKo 359 10.3 Deuteron Production 0YvENlEZwNg 360 13.2 Course Review  24iPsnbS6_0 361 1.5 Categories of Physics 2YPu29d8RZY 362 5.1 Voyager Program 2jHK2MxGoio 363 9.4 Forces and Kinetic Energy 4U9B9YgEqe4 364 12.4 Redshift Tests 5QUe51d_22w 365 4.1 Time Dilation 6fFfT7LhtPw 366 5.4 Regions in Spacetime Diagrams 8rbXjIqF3IA 367 3.3 Michelson-Morley Experiment 8ytpmbkqF54 368 8.3 Proper Velocity CPaFPYeVKoY 369 7.2 Relativistic Doppler Effect EsciE9ws4qw 370 1.4 Guest Lecture: Space, Time, and Spacetime   FscOJbr_bvs 371 5.5 Causality LaTbPEKrE-8 372 11.1 Charge and Current OCQGydLI5LY 373 2.1 Events PV6lhcTfSGU 374 9.3 Collisions Pas_hfAna28 375 7.1 Introduction to the Doppler Effect Pf_PvckSdTg 376 8.2 Introduction to 4-Vector Notation QP-xHC_naJ4 377 3.2 Waves Sa1DMeTf8U8 378 10.7 Compton Effect UQFwsgznP-E 379 8.1 Algebra of Lorentz transformations UxTIYMtNc4g 380 12.1 Equivalence Principle VOlOArfGRqQ 381 10.2 The Large Electron-Positron Collider Wd5s5uLk7xs 382 3.4 Stellar Aberration _S1CREXGfvE 383 1.2. Prof. Klute’s Research aQAhRAn6ewc 384 9.1 Momentum Conservation d8IDtE-Ea0o 385 11.2 Electric and Magnetic Fields f08-SYyjMp0 386 4.2 Muons fW9ZyXvdCwE 387 1.3 History of Special Relativity gtQ046Tu2S4 388 6.1 Pole-in-the-Barn Paradox hZtjMB3Y9ZA 389 12.3 Bending of Light icqwK_WyoII 390 5.2 Velocity Addition ijOnv0DUCPE 391 10.4 Absorption and Emission of Photons lRSMmxJeaKA 392 12.6 Experimental Evidence  lhOaghjCdic 393 7.3 Redshift mBGJOLE7ZUg 394 5.3 Spacetime Diagrams o-CZeUT_Ud4 395 10.8 Global Positioning System v5jffYzm5pg 396 12.5 General Relativity 0lPfTMmyzvk 397 4.4 Invariance 96RHvPVlxN8 398 4.3 Length Contraction Ac-0-yaHsAg 399 10.5 Decay of a Pion Tc7g4iF8pHc 400 9.2 Energy Conservation XAt0dX5M-TA 401 2.2 Galilean Transformation ZmKaHSXDbn0 402 3.1 Light _naTiUQOq34 403 4.5 Lorentz Transformation eF38136N_4c 404 12.2 Time Dilation Effect on Earth rlC8mLGvong 405 6.2 Twin Paradox X9xv3ISHN7M 406 Relevance of a transitional justice framework to address Belgium’s colonial past ba-HMvDn_vU 407 1. Introduction to the Human Brain 9Bz-5-RC690 408 15. Hearing and Speech B4a0WdGp52g 409 24. Attention and Awareness W2PY6z1Wddg 410 13. Number pfZY5aDJazA 411 20. Theory of Mind & Mentalizing MuRVOQY8KoY 412 8. Navigation I Nk0H3o-hRMA 413 6. Introduction to the Human Brain SchmVoc5NzY 414 21. Brain Networks XRdJ5mXBo8A 415 18. Language I YD7QG4G7WVg 416 5. Cognitive Neuroscience Methods II YVHM8dSkimo 417 16. Music bAkuNXtgrLA 418 2. Neuroanatomy kAX_PRnliMo 419 10. Development, Nature & Nurture I otriwYhNtm0 420 7. Category Selectivity, Controversies, and MVPA ppxK4R8XWfU 421 9. Navigation II vFZY--lgmHs 422 4. Cognitive Neuroscience Methods I xA00vkxG3lE 423 11. Development, Nature & Nurture II (2018) gchvLiH3gHU 424 The Magic Behind OCW o7h_sYMk_oc 425 1. Introduction and Matrix Multiplication 9syvZr-9xwk 426 1. Introduction, Finite Automata, Regular Expressions IycOPFmEQk8 427 5. CF Pumping Lemma, Turing Machines KAySmSEGc9U 428 3. Regular Pumping Lemma, Conversion of FA to Regular Expressions N28g_YBXY8Y 429 9. Reducibility 1VhnDdQsELo 430 14. P and NP, SAT, Poly-Time Reducibility 7J1HD9rqEB4 431 24. Probabilistic Computation (cont.) q3xvno_KgRY 432 20. L and NL, NL = coNL 4dFPVJrNLDs 433 19. Games, Generalized Geography TSI3LR5WZmo 434 25. Interactive Proof Systems, IP cT_qwkTigv4 435 17. Space Complexity, PSPACE, Savitch's Theorem 4MgN6uxd4i4 436 7. Decision Problems for Automata and Grammars eEXSv0jChO4 437 26. coNP is a subset of IP Vp_AzDGQyrA 438 23. Probabilistic Computation, BPP asjAc90L8rE 439 12. Time Complexity TTArY7ojshU 440 6. TM Variants, Church-Turing Thesis 3PzuSPQPEU4 441 8. Undecidability N-_XmLanPYg 442 11. Recursion Theorem and Logic 6Az1gtDRaAU 443 16. Cook-Levin Theorem MGqoLm2aAgc 444 10. Computation History Method N32bnUliSzo 445 22. Provably Intractable Problems, Oracles aVv9WXwW95w 446 18. PSPACE-Completeness iZPzBHGDsWI 447 15. NP-Completeness m9eHViDPAJQ 448 4. Pushdown Automata, Conversion of CFG to PDA and Reverse Conversion oNsscmUwjMU 449 2. Nondeterminism, Closure Properties, Conversion of Regular Expressions to FA vqFRAWeEcUs 450 21. Hierarchy Theorems 2feI17qlPOQ 451 What do we mean by reparations? 2LbzSIwFtXw 452 Openings for Seeking Justice for Colonial Violence in Algeria j5XdY5wkVTA 453 Lecture 1: Introduction and Overview I (14.13 Psychology and Economics, Spring 2020) bBOBSC16NLU 454 Lecture 5: Time Preferences (Applications) I pwFsPEPPUGU 455 Lecture 7: Risk Preferences I 3UTfFMTqH70 456 Lecture 17: State-Dependent Preferences, Projection, and Attribution Bias 5C-Wp6sL8lg 457 Lecture 18: Gender, Discrimination, and Identity 8WhNaFsFC8I 458 Lecture 6: Time Preferences (Applications) II JXRd60knm-A 459 Lecture 10: Social Preferences I K7QVIqV2QMk 460 Lecture 13: Social Preferences IV Lhtf6jFM8Vo 461 Lecture 8: Risk Preferences II Re2lkF0vgQw 462 Lecture 21: Poverty through the Lens of Psychology S-BaPQR1ZRU 463 Lecture 19: Defaults, Nudges, and Frames S6JHQ3-bsHk 464 Lecture 11: Social Preferences II SC8K6gNAIL4 465 Lecture 9: Reference-Dependent Preferences UI4Hjug3rEc 466 Lecture 23: Policy with Behaviorial Agents UbRlSqmN4uM 467 Lecture 3: Time Preferences (Theory) I Z0vdSf8m13k 468 Lecture 20: Malleability and Inaccessibility of Preferences _LJnCFFyF-M 469 Lecture 22: Happiness and Mental Health _iNqssktTto 470 Lecture 4: Time Preferences (Theory) II ik1gdNwHLiY 471 Mid-Term Review j9Zeole0bYg 472 Lecture 15: Utility from Beliefs; Learning I l7mu7-YNSg0 473 Lecture 12: Social Preferences III lD_73cro7wc 474 Lecture 2: Introduction and Overview II qk0mVzI1L78 475 Lecture 16: Utility from Beliefs; Learning II szy8tLyFS-Q 476 Lecture 14: Limited Attention ZA-tUyM_y7s 477 1. Algorithms and Computation CHhwJjR0mZA 478 2. Data Structures and Dynamic Arrays 4nXw-f6NJ9s 479 21. Algorithms—Next Steps U1JYwHcFfso 480 7. Binary Trees, Part 2: AVL Xnpo1atN-Iw 481 8. Binary Heaps f9cVS_URPc0 482 12. Bellman-Ford l_A-ig1n8CM 483 Problem Session 8 5cF5Bgv59Sc 484 11. Weighted Shortest Paths JbafQJx1CIA 485 19. Complexity KLBCUx1is2c 486 16. Dynamic Programming, Part 2: LCS, LIS, Coins TDo3r5M1LNo 487 17. Dynamic Programming, Part 3: APSP, Parens, Piano WO6vQJ6Rhm8 488 Problem Session 7 ZLdooNwP7Pw 489 Problem Session 5 e98MPnMHLxE 490 Quiz 1 review oFVYVzlvk9c 491 9. Breadth-First Search oS9aPzUNG-s 492 3. Sets and Sorting yndgIDO0zQQ 493 5. Linear Sorting 2NMtS1ecb3o 494 20. Course Review 76dhtgZt38A 495 6. Binary Trees, Part 1 EmSmaW-ud6A 496 14. APSP and Johnson IBfWDYSffUU 497 10. Depth-First Search IPSaG9RRc-k 498 Introduction to Algorithms - Problem Session 1: Asymptotic Behavior of Functions and Double-ended... KlQiwkhLBg0 499 Problem Session 2 (MIT 6.006 Introduction to Algorithms, Spring 2020) MAyraVVYB64 500 Problem Session 4 NSHizBK9JD8 501 13. Dijkstra Nu8YGneFCWE 502 4. Hashing g0bXSXuLVb0 503 Problem Session 3 i9OAOk0CUQE 504 18. Dynamic Programming, Part 4: Rods, Subset Sum, Pseudopolynomial kshe8d8rxHo 505 Problem Session 6 r4-cftqTcdI 506 15. Dynamic Programming, Part 1: SRTBOT, Fib, DAGs, Bowling vCIa2h1C9UQ 507 Quiz 2 Review wEKFGdo4Sck 508 Quiz 3 Review Bcxyr_yBBQg 509 Lesson 8 Kanji M7oHikLia0I 510 Lesson 6 Kanji RrPfRygcwFA 511 Lesson 10 Kanji TdcQPpHF5bo 512 Lesson 7 Kanji hRPRQVG8Tw0 513 Lesson 9 Kanji EQjwWn-WrdI 514 20. Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees KLb5CmPM7YY 515 12. Carbohydrates/Introduction to Membranes 33w-baH49rA 516 26. Oxidative Phosphorylation/Photosynthesis I 3fSY92mJwQY 517 23. TCA Cycle II 7Z1CfKUOQVs 518 30. Nitrogen/Amino Acid Metabolism I NTPCKnYLacw 519 29. Lipid Synthesis Z2ScgFh81Dc 520 21. Glycolysis II/Regulation m8-I1iey_4U 521 19. Introduction Metabolism/Polysaccharides/Bioenergetics/Intro Pathways o1pSk-sgFCA 522 27. Photosynthesis II/CO2 Assimilation t0eXy4RKEys 523 24. Lipids and Fatty Acid Oxidation xxydY73V9bQ 524 20. Bioenergetics/Intro Pathways/Glycolysis I 2Q1GUhhc9is 525 25. Oxidative Phosphorylation 7uCfPTwwYIc 526 31. Amino Acid Metabolism II Ed0Wg-5YYCk 527 32. Nucleotide Metabolism PwrmTuwSX0Y 528 28. Pentose Phosphate Pathway i6GlN02PDr8 529 22. Glucogenesis/Carbohydrate Storage/TCA Cycle I MdUnh4PaGKw 530 24. Robustness to Dataset Shift -WIAoAG4SyA 531 L0.1 Introduction to Nuclear and Particle Physics: Course Overview -hgRkC_uUzU 532 L6.3 Weak Interactions: Pion Decay 16iPrwJMvSs 533 L1.5 Fermions, Bosons, and Fields: Reactions 1LBAOxm8QOE 534 L10.1 Instrumentation: Particle Interaction with Matter 1jf3xnhKVh4 535 L2.1 Symmetries: Introduction 2KQrWenxujU 536 L7.2 Higgs Physics: Fermion Masses 2UHUg1OjYnE 537 L4.6 QED: Examples 2YpdnHLvsyw 538 L3.4 Feynman Calculus: Higher-Order Diagrams 3GHk5vlb26o 539 L1.4 Fermions, Bosons, and Fields: Decays 4H0EHje2QbQ 540 L2.3 Symmetries: Parity 4lUVayy53V4 541 L7.4 Higgs Physics: Current Status 6xzjJ5ncGxY 542 L1.2 Fermions, Bosons, and Fields: Feynman Diagram 8-HU6SwL9jo 543 L4.5 QED: Feynman Rules for QED 9QPqYAr-Zsc 544 L8.5 Neutrino Physics: Results of Neutrino Oscillation Experiments AQkCZmhu0aA 545 L6.2 Weak Interactions: Electroweak Unification B53W30-GJ10 546 L0.5 Introduction: Early History and People in Nuclear and Particle Physics BCQ9h1PxW08 547 L9.2 Nuclear Physics: Binding Energies BqZ8TiM-UVs 548 L9.4 Nuclear Physics: Nuclear Force J6L9uQ-IO90 549 L8.4 Neutrino Physics: Experimental Study wB5BYYEOPVA 550 L9.8 Nuclear Physics: Fusion FEK07tdpX3I 551 L6.5 Weak Interactions: Neutral Current HynldX56FHI 552 L1.1 Fermions, Bosons, and Fields: Quantum Field and Matter pCoDwHg5Vh8 553 L2.5 Symmetries: CP quSdhgX3NB8 554 L0.6 Introduction to Nuclear and Particle Physics: Particles tnxXcxiJnho 555 L0.7 Introduction to Nuclear and Particle Physics: Units DXf8JrCEaNk 556 L4.4 QED: Photon EO9OVMFuWvw 557 L8.6 Neutrino Physics: Mass Scale and Nature FW4H4mIeqnQ 558 L0.3 Introduction to Nuclear and Particle Physics: Teaching Staff HnRoq5Pc8Z4 559 L5.4 QCD: Deep Inelastic Scattering I5yQgNyBYb8 560 L9.5 Nuclear Physics: Shell Model IgqwfvODZIE 561 L5.3 QCD: Feynman Rules in QCD JSlXpd9zm6Q 562 L4.8 QED: Cross Sections JWnQZrnRUGM 563 L10.3 Instrumentation: Calorimetry LGm2fvo-M9g 564 L0.9 Introduction to Nuclear and Particle Physics: Spin MlBL7hSUeWE 565 L2.2 Symmetries: Flavor Symmetry ORG6YD9P8WM 566 L4.3 QED: Antiparticles QDIdZR9G2UU 567 L1.3 Fermions, Bosons, and Fields: Ranges of Forces RFiXkal1vfM 568 L5.6 QCD: Hadron Collider RmbJBq9kpbI 569 L5.2 QCD: Elastic Electron-Positron Scattering T-FQQVhPoNo 570 L4.9 QED: Renormalization and Higher-Order QED Diagrams X4Y9n_c1ej8 571 L0.4 Introduction to Nuclear and Particle Physics: Literature Xwr97XAqaaU 572 L9.6 Nuclear Physics: Gamma Decay YLrCiurZTOE 573 L3.5 Feynman Calculus: Divergency ZYQBSJn6n6o 574 L9.7 Nuclear Physics: Fission b5DKpnHXuUU 575 L10.4 Instrumentation: Accelerators bltHh3K2_Gs 576 L10.2 Instrumentation: Tracking Detectors cuUIPyD2pkU 577 L8.2 Neutrino Physics: Mass dTAIYaSBols 578 L7.1 Higgs Physics: Higgs Mechanism dksNHMhiXVQ 579 L9.1 Nuclear Physics: Introduction ecIB8DWNyWA 580 L4.2 QED: Dirac Equation Solutions fdIJzQl60ys 581 L2.4 Symmetries: Charge Conjugation fsvkE3cR1Aw 582 L8.1 Neutrino Physics: In the Standard Model hgrhfkcXlAQ 583 L4.10 QED: Noether's Theorem jC96H8qT3DQ 584 L5.5 QCD: Asymptotic Freedom jtA3Hxww7FQ 585 L6.1 Weak Interactions: Feynman Rules jtSfWlQbmNY 586 L3.2 Feynman Calculus: Fermi's Golden Rule k2-dTdj5wkk 587 L3.3 Feynman Calculus: Toy Theory lF-LM9CdiVk 588 L0.2 Introduction to Nuclear and Particle Physics: Course Organization nXzur-2hbkI 589 L8.3 Neutrino Physics: Mixing olxlB5mW1CI 590 L5.1 QCD: Hadron Production qHq6ndGK0To 591 L7.3 Higgs Physics: Production and Decay s-QcRrGppsk 592 L4.7 QED: Casimir's Trick u46_GiV2iFc 593 L3.1 Feynman Calculus: Introduction vICUY43i190 594 L6.4 Weak Interactions: Quarks vrLClnmpaeA 595 L0.8 Introduction to Nuclear and Particle Physics: Relativistic Kinematics ygls16dl8Sc 596 L4.1 QED: Free Wave Equation gPGwsDdtBTA 597 OCW Reaching Out to The World – Livestreamed Event omdqRLVehrw 598 S2E8: Building Our Muscle for Democracy (Prof. Ceasar McDowell) l1hMkDTg2lg 599 1. Introductory Lecture to 5.310 EuVpZmQ5v6A 600 2. The Ferrocene Lecture oc7sODbVGuA 601 10. Fischer Esterification Part 1 J23egLCM2tc 602 3. Writing Up the Lab Report JIw9mnVeFig 603 7. Ellen Swallow Richards, Part 3 -l9SfGuZJYE 604 6. Ellen Swallow Richards, Part 2 Ea2YTXJrhkM 605 15. NMR Spectroscopy Esterification Lecture Part 3 LNCLrmAvSlU 606 8. Essential Oils Lecture Part 1 OQq7qH74T5E 607 5. Ellen Swallow Richards, Part 1 TgrNa_Guigs 608 11. Catalase Part 1 dgRLgf4oO2s 609 14. Mass Spectroscopy Esterification Lecture Part 2 sV_yiHbMUF8 610 4. What's Significant in Laboratory Measurement? Error Analysis Lecture sukzgrxfSx8 611 9. Essential Oils Lecture Part 2 yiSZecIWBIc 612 12. Catalase Acid Part 2 pmI0Bl3ozWU 613 You're Invited to OCW Reaching Out to The World dARl_gGrS4o 614 8. Constraints: Search, Domain Reduction jwJrF6kBuJ4 615 S2E7: In Climate Conversations, Empathy is Everything (Brandon Leshchinskiy) 0aAEamhJHUI 616 MIT OpenCourseWare at 20 8O2EPwUtWyY 617 Celebrating 20 Years of MIT OCW Event jq7d4fE39aM 618 Course conclusion 6sXqF5pz0bs 619 Transfer of respiratory pathogens: Droplet formation IJyboHTpBws 620 Beyond the well-mixed room: Airborne transmission indoors NXquyoAX1_M 621 Airborne disease transmission in a well-mixed room: Chapter 2 overview Oh8aK-0N-9M 622 Safety guideline for COVID-19: Vaccination and immunity Sp6rcXifyAo 623 Beyond the well-mixed room: Forced convection ZqEKYbzgz4s 624 Transfer of respiratory pathogens: Indoor airborne spreading of COVID-19 i_F7ndSmVGE 625 Beyond the well-mixed room: Aerosol transport j--zfB6AIpo 626 Epidemiological models: Indoor disease spreading lFDL2Qif2vE 627 Transfer of respiratory pathogens: Modes of transmission lo-5afXPHx0 628 Safety guideline for COVID-19: Reopening schools or businesses nOW0xBef6rg 629 Airborne disease transmission in a well-mixed room: Respiration and ventilation nbJRDPcJTWk 630 Transfer of respiratory pathogens: Drop size–dependent infectivity (ASIDE) o75BCkQL5Co 631 Safety guideline for COVID-19: Case studies qjUR8WJWRgQ 632 Transfer of respiratory pathogens: Escape time of virions 0VppWRGt0uk 633 Safety guideline for COVID-19: Role of prevalence of infection 7io-8_I6ZXA 634 Transfer of respiratory pathogens: Equilibrium size of respiratory aerosols F0sz463hx3U 635 Epidemiological models: Incubation-enhanced spreading k_VJo1Vrl6E 636 Transfer of respiratory pathogens: Bacteria nyuKHTzr6xA 637 Beyond the well-mixed room: Ventilation vQYQR8iNU-o 638 Safety guideline for COVID-19: Cumulative exposure time -Yt7LQ4k1IU 639 Airborne disease transmission in a well-mixed room: Airborne transmission rate -nAt3BJQ2xY 640 Beyond the well-mixed room: Social distancing 2Y__Z_PgAxQ 641 Course overview of physics of COVID-19 transmission 71dUZmywpOM 642 Transfer of respiratory pathogens: Aerosolized pathogen deactivation 9hdNPVEQLFE 643 Transfer of respiratory pathogens: Wells curve derivation (ASIDE) Gcb0zp82BtA 644 Epidemiological models: Chapter 3 overview Gxefx9BDCq0 645 Airborne disease transmission in a well-mixed room: Sedimentation and deactivation Jd1BTtUqLBA 646 Safety guideline for COVID-19: Chapter 4 overview K10Q4EUFE6k 647 Transfer of respiratory pathogens: Chapter 1 overview MRdNlTEoIFE 648 Beyond the well-mixed room: Short-range transmission NJST-IUGBUA 649 Transfer of respiratory pathogens: Viral deactivation in aerosols (ASIDE) Nt44I1OYkFw 650 Beyond the well-mixed room: Chapter 5 overview P9hTSTZAxqs 651 Safety guideline for COVID-19: Transient transmission rate QbueCxKUUTo 652 Beyond the well-mixed room: Respiratory puffs and jets X1or8Ish5OU 653 Beyond the well-mixed room: Natural convection _jz3HWBmruo 654 Safety guideline for COVID-19: Transient aerosol buildup _sNtz_Z5MA4 655 Airborne disease transmission in a well-mixed room: Drop-size distributions eAHDiT40fkU 656 Epidemiological models: Disease spreading in a population ePKxMVfPmws 657 Safety guideline for COVID-19: Risk scenarios fdbeCmYRVzA 658 Safety guideline for COVID-19: Transmission rate hAUFAN8Ceac 659 Safety guideline for COVID-19: Safety guideline as a simple formula kmpde1ZIqKA 660 Safety guideline for COVID-19: Steady transmission rate peZLMv1Qk8A 661 Transfer of respiratory pathogens: Viruses t4P_zSJbods 662 Transfer of respiratory pathogens: Release of viral load from a drop (ASIDE) w6pWbzkTap4 663 Airborne disease transmission in a well-mixed room: Air filtration versus masks wfLISAzXYns 664 Safety guideline for COVID-19: Analysis of superspreading events yfxD7JKUxFQ 665 Beyond the well-mixed room: Turbulent jets (ASIDE) ysEeFyNjnkQ 666 Transfer of respiratory pathogens: Airborne droplets jdGcDyyu2MA 667 MIT OpenCourseWare: Origins, Pathways, and Possibilities pA_YU7EttIo 668 S2E6: Visualizing the Future of Spaceship Earth (Professor Dava Newman) 5HfMEUO9vlY 669 Instructor Insights: Facilitating a Blended Learning Experience Q8bGQAAooY8 670 S2E5: Encountering Each Other (Essayist Garnette Cadogan) 57o2JJSLNxI 671 S2E4: Seeing the Big Picture from Space (Astronaut Jeff Hoffman) n068fel-W9I 672 Special Lecture: F-22 Flight Controls QyElbUb1QjI 673 Closing Speech (Intro to Solid-State Chemistry) cSER5tjagqE 674 Goodie Bag 8: Reactions (Intro to Solid-State Chemistry) iLCVVag7Z7M 675 Goodie Bag 3: Ionic Solids (Intro to Solid-State Chemistry) s2QJtkcA1Uk 676 Goodie Bag 4: VSEPR (Intro to Solid-State Chemistry) u0h5IUouNk0 677 Goodie Bag 5: Electronic Materials (Intro to Solid-State Chemistry) vewtUlemzto 678 Goodie Bag 1: Atoms and Reactions (Intro to Solid-State Chemistry) wFuIzicEWD8 679 Goodie Bag 6: Crystallography (Intro to Solid-State Chemistry) BbascVoYf_E 680 Goodie Bag 7: Defects (Intro to Solid-State Chemistry) Gqic72B-1MU 681 Goodie Bag 9: Polymers (Intro to Solid-State Chemistry) KBgF_4xmahM 682 Goodie Bag 2: Electronic Transitions (Intro to Solid-State Chemistry) Ao41FrJFgvQ 683 1. Introduction (Intro to Solid-State Chemistry) LMSTMBX_2F4 684 32. Polymers I (Intro to Solid-State Chemistry) LV3l9yqJwio 685 8. Ionization Energy and Potential Energy Surface (PES) (Intro to Solid-State Chemistry) P34zaLtmsn0 686 Additional Lecture 1. Phases (Intro to Solid-State Chemistry 2019) 7NqA49Lb4nU 687 Personal Energy Storage (Intro to Solid-State Chemistry) 4gSOn3_rBWs 688 Rejected Energy (Intro to Solid-State Chemistry) 8KQPpl77fuk 689 The Age of Atomic Design (Intro to Solid-State Chemistry) 0tQP4Qh0jjI 690 Carbon Dioxide Concentration (Intro to Solid-State Chemistry) uOEXP2WEo3M 691 Additional Lecture 2. The Chemistry of Batteries (Intro to Solid-State Chemistry 2019) -qwVo9RrMl4 692 Wire Drawing (Intro to Solid-State Chemistry) 4Dr3Q-ezMZk 693 6. Electron Shell Model, Quantum Numbers, and PES (Intro to Solid-State Chemistry) 4EcVts56MCU 694 The Shape of Smells (Intro to Solid-State Chemistry) 5jW7OA3pjSI 695 Haber-Bosch and Human Population (Intro to Solid-State Chemistry) 7_IoLAXtQ3k 696 24. Point and Line Defects II (Intro to Solid-State Chemistry) 9ayyzdIKaps 697 Hard and Soft Water (Intro to Solid-State Chemistry) AH26nVIv4TQ 698 High Tech Concrete (Intro to Solid-State Chemistry) J4jMT49oaPI 699 Grid-scale Energy Storage (Intro to Solid-State Chemistry) KPJvO_00LKQ 700 26. Engineering Glass Properties (Intro to Solid-State Chemistry) V4uZz6OO2bM 701 Cars and Carbon Dioxide (Intro to Solid-State Chemistry) btZ-VFW4wpY 702 Why Are You Here? Introduction to the Course, "Intro to Solid-State Chemistry" (Fall 2018) e_WABkM-Kxo 703 3. Atomic Models (Intro to Solid-State Chemistry) pUp7jJcp8p4 704 Utilizing Abundant Resources (Intro to Solid-State Chemistry) OMFpHmfC1pY 705 14. Intermolecular Forces (Intro to Solid-State Chemistry) HBMHHwkTEJg 706 Danish Wind and Ions (Intro to Solid-State Chemistry) SkT7VIul_8A 707 Crystals (Intro to Solid-State Chemistry) UBGcs9r4U40 708 Quantum Domination (Intro to Solid-State Chemistry) UzDqh-1Koyc 709 13. Hybridization (Intro to Solid-State Chemistry) Yap0AKRczf0 710 17. Metals (Intro to Solid-State Chemistry) 9SvAZgd0J_A 711 28. Introduction to Aqueous Solutions (Intro to Solid-State Chemistry) Ep7mkm_T0Po 712 16. Doping (Intro to Solid-State Chemistry) HaL1Q8f7M_o 713 2. The Periodic Table (Intro to Solid-State Chemistry) Q5W3J0NChwA 714 How to Make Blue LEDs (Intro to Solid-State Chemistry) S1kqa_qGmHs 715 22. X-ray Diffraction Techniques II (Intro to Solid-State Chemistry) UF94OiDYgBY 716 36. Diffusion II (Intro to Solid-State Chemistry) aCJECIYz8gM 717 10. Lewis Structures II (Intro to Solid-State Chemistry) g9v8zj6VObw 718 11. Shapes of Molecules and VSEPR (Intro to Solid-State Chemistry) qpT5gDAQtD0 719 Television Screens (Intro to Solid-State Chemistry) vGvnfTk5BFk 720 Hemodialysis (Intro to Solid-State Chemistry) xALiVHvc7EU 721 Imaging with Electrons (Intro to Solid-State Chemistry) AqCz_b7VJK8 722 21. X-ray Diffraction Techniques I (Intro to Solid-State Chemistry) Crut4GvgU6g 723 Moseley's Law (Intro to Solid-State Chemistry) SDrn8A4IzrA 724 The Battery Revolution (Intro to Solid-State Chemistry) wX32hH138Ws 725 Refrigerators and CFCs (Intro to Solid-State Chemistry) 5i4fd-BhAt0 726 Drinking Water (Intro to Solid-State Chemistry) P19jcEvALl4 727 Transistors & Semiconductors (Intro to Solid-State Chemistry) R0sw85RkKCY 728 18. Introduction to Crystallography (Intro to Solid-State Chemistry) cMIRECEsKHM 729 33. Polymers II (Intro to Solid-State Chemistry) fuo2j6f8yok 730 Materials Problems (Intro to Solid-State Chemistry) g4lxRZ7T5_o 731 19. Crystallographic Notation (Intro to Solid-State Chemistry) q9D2zR5q0Sc 732 Properties of Benzene (Intro to Solid-State Chemistry) 1Sjt9QDNDYU 733 Catalytic Converters (Intro to Solid-State Chemistry) 1rgmGwAqMYc 734 31. Exam Review (Intro to Solid-State Chemistry) AbyrF4VtlYY 735 25. Introduction to Glassy Solids (Intro to Solid-State Chemistry) DtTchZtor3g 736 'Weak' Forces Are Strong (Intro to Solid-State Chemistry) GhwBpZx3LjI 737 27. Reaction Rates (Intro to Solid-State Chemistry) _vA3IT2KZs0 738 Polymer Strength (Intro to Solid-State Chemistry) gUrBP6ei4fs 739 Ocean Acidification (Intro to Solid-State Chemistry) omPD_LtrpGU 740 Nature + Arrhenius (Intro to Solid-State Chemistry) tKyaGnPni3U 741 20. X-ray Emission and Absorption (Intro to Solid-State Chemistry) uVGQayrQ9JA 742 Two Ways to Separate Pasta (Intro to Solid-State Chemistry) CxAkraYlBuE 743 15. Semiconductors (Intro to Solid-State Chemistry) DvGNpuan4rw 744 9. Lewis Structures I (Intro to Solid-State Chemistry) Ji20_qhjk2Y 745 4. Atomic Spectra (Intro to Solid-State Chemistry) L0b9wq0js4I 746 12. Molecular Orbitals (Intro to Solid-State Chemistry) YROT1JTNLWs 747 23. Point and Line Defects I (Intro to Solid-State Chemistry) ZSv_gYLBi8E 748 29. Acids and Bases I (Intro to Solid-State Chemistry) bhPMi2IvZXs 749 7. Aufbau Principle and Atomic Orbitals (Intro to Solid-State Chemistry) iPzRbK3wApI 750 34. Introduction to Organic Chemistry (Intro to Solid-State Chemistry) j4m0Ye5Qgcg 751 35. Diffusion I (Intro to Solid-State Chemistry) rkFY8WB8tfs 752 5. Shell Models and Quantum Numbers (Intro to Solid-State Chemistry) xrf39mMxPZg 753 30. Acids and Bases II (Intro to Solid-State Chemistry) lKihMJaJR9Y 754 S2E3: Making Solid State Chemistry Matter (Prof. Jeffrey Grossman) TzHbu221zMY 755 S2E2: Searching for the Oldest Stars (Prof. Anna Frebel) 3zuEzPzbNPg 756 Video 6: Ohm's Law (online class) Dy4KEXJsVIY 757 Video 7: Graph Theory (online class) yIpzVIt1Iuo 758 S2E1: Paying it Forward with FinTech (Prof. Gary Gensler) 59Dd5T6crKw 759 Class 5: Blockchain Technology & Cryptocurrencies iahUTx27HUg 760 Class 11: Coronavirus Crisis & Finance 4FGNLl9Btfw 761 Class 6: Payments 90JWoR9MfYU 762 Class 1: Intro and Key Technological Trends Affecting Financial Services JuKKBf-uSDI 763 Class 7: Credit & Lending LaP0Ut84GzI 764 Class 4: Open APIs & Marketing Channels OUAMdi281mQ 765 Class 3: Artificial Intelligence in Finance kZ1EqqnUw6M 766 Class 12: Conclusion nq8la9qknx8 767 Class 2: Artificial Intelligence, Machine Learning, and Deep Learning oYR6xdcFNwc 768 Class 8: Challenger Banks pA-AgV8wo0o 769 Class 10: Insurance uHUA6M1OEwk 770 Class 9: Trading & Capital Markets vof7x8r_ZUA 771 1. What Makes Healthcare Unique? 0UFwGJe6ubg 772 3. Deep Dive Into Clinical Data 2ZXYM1h9pgY 773 13. Machine Learning for Mammography Td01vFP3uJo 774 21. Automating Clinical Work Flows aJqgO8e37_g 775 19. Disease Progression Modeling and Subtyping, Part 2 gRkUhg9Wb-I 776 14. Causal Inference, Part 1 kZrb6ZIwJqg 777 20. Precision Medicine lkO2ocJBsmI 778 8. Natural Language Processing (NLP), Part 2 wDLzLN1tArA 779 25. Interpretability zYgkr0KfWM0 780 23. Fairness g5v-NvNoJQQ 781 15. Causal Inference, Part 2 DS97JV_o0Fs 782 2. Overview of Clinical Care IiD3YZkkCmE 783 7. Natural Language Processing (NLP), Part 1 MoEaRpLNo9A 784 10. Application of Machine Learning to Cardiac Imaging PKCMH5KOcxQ 785 12. Machine Learning for Pathology VuKOW8d4KHw 786 11. Differential Diagnosis YZ5pOgY5hEE 787 16. Reinforcement Learning, Part 1 ZQu2B3GyI_k 788 9. Translating Technology Into the Clinic _shuV1tJbTU 789 4. Risk Stratification, Part 1 k95abdkdCPk 790 22. Regulation of Machine Learning / Artificial Intelligence in the US lLhfDSOwWtU 791 6. Physiological Time-Series wqI_z1yumzY 792 5. Risk Stratification, Part 2 yYWyLZrdRRI 793 18. Disease Progression Modeling and Subtyping, Part 1 zdotUAxiPGM 794 17. Reinforcement Learning, Part 2 gC5QRayrYD4 795 Fall 2020 Update from Dean Krishna Rajagopal to the OCW community hvcYz4yzS0w 796 Introduction to Ethics in Machine Learning 3f98wYIWsN0 797 Case Study: Identifying and Mitigating Unintended Demographic Bias in Machine Learning for NLP 6EPDzvUNCd0 798 Protected Attributes and 'Fairness through Unawareness,' Exploring Fairness in Machine Learning CaoJ_Z4g7FQ 799 Exploring Fairness in Machine Learning: Background Nc2qMVsHkgc 800 Case Studies with Data: Mitigating Gender Bias on the UCI Adult Dataset RQLsnWwjcNY 801 USAID Appropriate Use Framework, Exploring Fairness in Machine Learning euwc0va-7Vo 802 Fairness Criteria, Exploring Fairness in Machine Learning neG4seg61VU 803 Solar Lighting Example, Exploring Fairness in Machine Learning zrB6pocJSI8 804 Pulmonary Health Case Study: Bias Exploration, Exploring Fairness in Machine Learning iRVfaR3N5K4 805 1. Introduction and the geometric viewpoint on physics. TiHHz3sKDbY 806 2. Introduction to tensors. H6eR3sG524M 807 3. Tensors continued. h9xaoGkyHwg 808 4. Volumes and volume elements; conservation laws. OOmZkNa72t4 809 5. The stress energy tensor and the Christoffel symbol. 6MssatXXAzc 810 6. The principle of equivalence. gnWKpHUj11w 811 7. Principle of equivalence continued; parallel transport. LoIq6KElVxs 812 8. Lie transport, Killing vectors, tensor densities. 4QPKWFme0k4 813 9. Geodesics. JWSdeg4jkoY 814 10. Spacetime curvature. d1dtqw7f6pw 815 11. More on spacetime curvature. OIjLUzS6SQA 816 12. The Einstein field equation. JNWXzIFcf3g 817 13. The Einstein field equation (variant derivation). 9lIgAPvppk0 818 14. Linearized gravity I: Principles and static limit. Oxk2nnuC130 819 15. Linearized gravity II: Dynamic sources R2vL2wLqGYg 820 16. Gravitational radiation I pUqA_iHLBWQ 821 17. Gravitational radiation II wBvXOb59l-k 822 18. Cosmology I p_10lgn2BiI 823 19. Cosmology II PVYTNKZDHBo 824 20. Spherical compact sources I K1vpc9YwlQI 825 21. Spherical compact sources II ZqF-7bjnzCU 826 22. Black holes I _uNWqE3LS1E 827 23. Black holes II fwThhaZk5WQ 828 Introduction to Getting up to Speed in Biology HdV_r6aIcew 829 Lecture 1.1: The Molecules of Life — Representing Molecules yDu_xhkKwnQ 830 Lecture 1.2: The Molecules of Life — Polar and Non-polar Molecules GsoPFDvIHB8 831 Lecture 1.3: The Molecules of Life — Types of Bonds ziSgaFhG2VU 832 Lecture 1.4: The Molecules of Life — Recognizing Macromolecules JLkEM9tQ2jE 833 Lecture 4.5: Inheritance and Genetics — Conclusion dAl5bNNr8mQ 834 Lecture 4.4: Inheritance and Genetics — Pedigrees 6az6JlvTtOM 835 Lecture 3.1: Information Transfer in Biology — DNA Rules KqAYOtPNtN8 836 Lecture 3.2: Information Transfer in Biology — DNA Replication 8umr89M6YgQ 837 Lecture 2.2: The Cell and How it Works — Free Energy and Reaction Kinetics mLV-LEonxOE 838 Lecture 1.6: The Molecules of Life — Protein Polarity 87_aoFA748s 839 Lecture 2.1: The Cell and How it Works — Condensation and Hydrolysis KG0vOWQm1ZI 840 Lecture 2.6: The Cell and How it Works — Conclusion c2D8EDGsw7E 841 Lecture 4.2: Inheritance and Genetics — Allele Segregation 8E3Dziafqkg 842 Lecture 1.7: The Molecules of Life — Conclusion dhMAf7qhVLY 843 Lecture 5.2: Building with DNA — Compatible Ends -to-7OIJyQ0 844 Lecture 1.5: The Molecules of Life — Nucleic Acid Polarity 1Pzk-UqilW4 845 Lecture 4.1: Inheritance and Genetics — Genes to Proteins 20GI4ds31nY 846 Lecture 3.3: Information Transfer in Biology — Transcription LhjPZo1YKIg 847 Lecture 5.4: Building with DNA — Conclusion NSaucwkypPI 848 Lecture 5.1: Building with DNA — Restriction Digests S7oxN3cPOkY 849 Lecture 2.5: The Cell and How it Works — Cell Division WDzRrlTlv5o 850 Lecture 5.3: Building with DNA — Polymerase Chain Reaction (PCR) bp9QR86IQag 851 Lecture 3.4: Information Transfer in Biology — Translation eqXSJ1I-nRA 852 Lecture 2.3: The Cell and How it Works — Pathways gNfFw1iDblE 853 Lecture 4.3: Inheritance and Genetics — Punnet Squares h25xARj3lb8 854 Lecture 3.5: Information Transfer in Biology — Conclusion rTIzwUEqI8k 855 Lecture 2.4: The Cell and How it Works — Organelles -4C9-OgKLCY 856 What Cameras Can Do for You… and How They Do It! A4IC92HVLLU 857 Image Processing KhY97qoDPMg 858 SWE (Society of Women Engineers) OJPqzP54KiY 859 Closing Remarks bnYD88uNtwY 860 Engineering M13 Bacteriophage NIR-II Platforms for Tumor Imaging Applications fp7wylcPRKM 861 Inspiring the Next Generation: Women's Technology Program at MIT gXalqmV5ZEU 862 Instructor Insights: Image Processing Activity mTOi3SpJCjw 863 Welcome to Girls Who Build Cameras, Summer 2016 ow2TNmzadXc 864 Girls Who Build Cameras Promo tJj6YN8peXU 865 Intro to Digital Cameras _OkTw766oCs 866 1. Introduction and Supply & Demand RnN2rgCrIzs 867 16. Input Markets II—Labor and Capital BF1ZtGIjTik 868 22. Government Redistribution and Taxation B6wI0CE4GjM 869 18. Increasing Savings & Introduction to Trade F0ulAkrfvzo 870 8. Competition II TSYNHb6YBEE 871 6. Costs BUnUOv_INyM 872 17. Making Choices Over Time ZLnj2cnCPGE 873 23. Market Failures I: Externalities 1UtJGRojmIg 874 9. Supply and Demand & Consumer/Producer Surplus 0kA91PvS3sk 875 13. Oligopoly DxXB8Q5AWvw 876 19. International Trade: Welfare and Policy a9Uz7tXETq4 877 20. Uncertainty jHEPQpSKdbg 878 3. Budget Constraints and Constrained Choice FJVOh57UxL8 879 11. Monopoly I hm5zqBPsRJM 880 24. Market Failures II: Informational Asymmetry PC3qooaF5Xs 881 10. Welfare Economics tCKk22kaZi4 882 2. Preferences and Utility Functions ufrYzoR_4xE 883 12. Monopoly II x0scPosOsoI 884 4. Demand Curves and Income/Substitution Effects 6XhkCU8Rw_0 885 15. Input Markets I—Labor Market BNy84DCRxzo 886 7. Competition I RJi1GsObmWQ 887 23. Market Failures I: Externalities ftmvsahQ6Wo 888 5. Production Theory jsiCft5v2dk 889 25. Health Economics oFL2Hxqg7eo 890 14. Oligopoly II osaVeUBA0Qk 891 21. Efficiency and Equity JGCSdBMU1uA 892 S1E10: The Power of OER with Profs. Mary Rowe and Elizabeth Siler PnJEj6TokDA 893 1: Course Overview and Ionic Currents - Intro to Neural Computation smHwRzk81b0 894 10: Time Series - Intro to Neural Computation fCqt07IXUPI 895 9: Receptive Fields - Intro to Neural Computation 4ip-4ai6kN8 896 11: Spectral Analysis Part 1 - Intro to Neural Computation Hf1Ma9YkOMY 897 12: Spectral Analysis Part 2 - Intro to Neural Computation N-49t1j-XWY 898 17: Principal Components Analysis_ - Intro to Neural Computation dNHqd6nGr5o 899 6: Dendrites - Intro to Neural Computation K1pxJVdqlxw 900 5: Hodgkin-Huxley Model Part 2 - Intro to Neural Computation 3GC721pNRLE 901 2: Resistor Capacitor Circuit and Nernst Potential - Intro to Neural Computation 5KhcA454er0 902 14: Rate Models and Perceptrons - Intro to Neural Computation 88tKZLGOr3M 903 4: Hodgkin-Huxley Model Part 1 - Intro to Neural Computation EpPtCLkCGOk 904 18: Recurrent Networks - Intro to Neural Computation KXnHxZdn8NU 905 3: Resistor Capacitor Neuron Model - Intro to Neural Computation Oq_k8F2T1Jc 906 15: Matrix Operations - Intro to Neural Computation VQXxs59Eiak 907 13: Spectral Analysis Part 3 - Intro to Neural Computation Yjeexoq_WAI 908 16: Basis Sets - Intro to Neural Computation gt52wUN3VrQ 909 20: Hopfield Networks - Intro to Neural Computation osYGG7TKcz8 910 8: Spike Trains - Intro to Neural Computation r1VX3WXrYUw 911 7: Synapses - Intro to Neural Computation vQpo3rTwUjc 912 19: Neural Integrators - Intro to Neural Computation t4K6lney7Zw 913 1. Artificial Intelligence and Machine Learning RpPlj2HnuWg 914 2. Cyber Network Data Processing; AI Data Architecture oMWvVcKdtco 915 S1E9: Thinking Like an Economist with Prof. Jonathan Gruber PUOXaLYiQNg 916 S1E8: Learning to Fly with Drs. Philip Greenspun & Tina Srivastava L8N_KZBHeIA 917 Welcome for Volunteers (for EarthDNA's Climate 101) g6Ksr5sJ0sM 918 Climate 101 Live BN4lexqVoEM 919 S1E7: Unpacking Misconceptions about Language & Identities with Prof. Michel DeGraff Pz7U-AEi8v0 920 Spring 2020 Update from Dean Rajagopal 7EnnSachgeQ 921 Special Episode: Teaching Remotely During Covid-19 with Prof. Justin Reich RDO6Py97IDg 922 1. A bridge between graph theory and additive combinatorics P3tGiT72APw 923 14. Graph limits I: introduction MlYhHsq_tOU 924 25. Structure of set addition V: additive energy and Balog-Szemerédi-Gowers theorem 4LYom0ekars 925 4. Forbidding a subgraph III: algebraic constructions Rlvwagd2BmY 926 12. Pseudorandom graphs II: second eigenvalue oLwZFBZylUw 927 21. Structure of set addition I: introduction to Freiman's theorem RwikpgvkN_o 928 22. Structure of set addition II: groups of bounded exponent and modeling lemma EnPjyNsEHQM 929 13. Sparse regularity and the Green-Tao theorem vcsxCFSLyP8 930 6. Szemerédi's graph regularity lemma I: statement and proof nCWwhF0TkVI 931 16. Graph limits III: compactness and applications 3IxWLibV_tU 932 9. Szemerédi's graph regularity lemma IV: induced removal lemma TgPcNnUrE24 933 11. Pseudorandom graphs I: quasirandomness 50oEJs-HZHQ 934 19. Roth's theorem II: Fourier analytic proof in the integers YAo1sd4kuOQ 935 2. Forbidding a subgraph I: Mantel's theorem and Turán's theorem 9gy-CAwx0Ls 936 15. Graph limits II: regularity and counting BatYGepHsnc 937 23. Structure of set addition III: Bogolyubov's lemma and the geometry of numbers DUA6lk7X2VY 938 20. Roth's theorem III: polynomial method and arithmetic regularity IfwfCe-JZaI 939 24. Structure of set addition IV: proof of Freiman's theorem NpMv0Nqmy3c 940 5. Forbidding a subgraph IV: dependent random choice RD9AWDdj-Yk 941 7. Szemerédi's graph regularity lemma II: triangle removal lemma buEtwpGvQpI 942 18. Roth's theorem I: Fourier analytic proof over finite field hDwkKrWqdZE 943 3. Forbidding a subgraph II: complete bipartite subgraph mJziV7sAZm4 944 17. Graph limits IV: inequalities between subgraph densities oiKLWa_0dhs 945 8. Szemerédi's graph regularity lemma III: further applications rBUFitIoE14 946 10. Szemerédi's graph regularity lemma V: hypergraph removal and spectral proof ydyiq1Z22gc 947 26. Sum-product problem and incidence geometry KlVHqq38KJU 948 1. Introduction, Course Organization of MIT 7.016 Introductory Biology, Fall 2018 LhbtCTwtdDU 949 29. Cell Imaging Techniques 83-yKXuRDGc 950 18. SNPs & Human genetics hDppkpYcBdg 951 28. Visualizing Life - Fluorescent Proteins Qfw0C0Ac-Tk 952 19. Cell Trafficking and Protein Localization 7xJPSuSVmSk 953 10. Translation Chv8dlBVXpw 954 9. Chromatin Remodeling and Splicing rZjwF5z-Xfw 955 12. Genetics 1 – Cell Division & Segregating Genetic Material s1MoBTEcVYY 956 6. Nucleic Acids jeNPvqRXI9I 957 14. Genetics 3 – Linkage, Crossing Over aKTOS0Nrlug 958 2. Chemical Bonding and Molecular Interactions; Lipids and Membranes mvjXFh4P08I 959 21. Cell Signaling 2 – Examples _fWt9yHslDo 960 35. Reproductive Cloning and Embryonic Stem Cells oOya3cFmAMc 961 3. Structures of Amino Acids, Peptides, and Proteins 6rOvXGoXoJc 962 26. Cancer 2 qtGHKiAROig 963 13. Genetics 2 – Rules of Inheritance 8jLy33vbtYM 964 7. Replication E8BihX2hGss 965 33. Bacteria and Antibiotic Resistance SA8dRTq3qUA 966 11. Cells, the Simplest Functional Units 7afYLl70cO0 967 22. Neurons, Action Potential, & Optogenetics 5ejPI6QqKBU 968 20. Cell Signaling 1 – Overview L4tEwAsVW0I 969 25. Cancer 1 nvxvcbaoayM 970 27. Visualizing Life – Dyes and Stains 68KXOYTc1mk 971 15. Genetics 4 – The power of model organisms in biological discovery CALYA11terw 972 5. Carbohydrates and Glycoproteins JuwErrBz3b4 973 17. Genomes and DNA Sequencing QTdJiG7mV40 974 4. Enzymes & Metabolism SqGmQ6CFYHw 975 31. Immunology 2 – Memory, T cells, & Autoimmunity kVu37T6sB_E 976 16. Recombinant DNA, Cloning, & Editing apP5SWitnyw 977 8. Transcription FpXIGTFD8Qs 978 30. Immunology 1 – Diversity, Specificity, & B cells iz7rWK5cqjE 979 23. Cell Cycle and Checkpoints Ao-r2nsib_Y 980 34. Viruses and Anti-Viral Resistance EJ6Sjn1c04Y 981 24. Stem Cells, Apoptosis, & Tissue Homeostasis 7gLcuMtM_HY 982 32. Infectious Disease, Viruses, and Bacteria YrHlHbtiSM0 983 Intro: A New Way to Start Linear Algebra azzrfdysfI0 984 Part 1: The Column Space of a Matrix GyC3gl6weYo 985 Part 4: Eigenvalues and Eigenvectors IHO7_n7Y09s 986 Part 5: Singular Values and Singular Vectors j8hEnyOiwhw 987 Part 3: Orthogonal Vectors rwLOfdfc4dw 988 Part 2: The Big Picture of Linear Algebra 6EqHlKhGcc4 989 S1E6: Hand-on, Minds On with Dr. Christopher Terman jeI3wpulyPw 990 Lecture 1: Introduction 6oZL2c3tgps 991 Special Lecture: The How and the Why of IFR AYF3spOVbBk 992 Lecture 4: Aircraft Systems Nts_8ZLIxwo 993 Lecture 5: Charts and Airspace kiCNa95DnnE 994 Lecture 21: Weather Minimums and Final Tips 802a1jvk5Ck 995 Lecture 18: Weight and Balance geJHchWUYQk 996 Lecture 17: Small UAS Operations shHvE6yV4IM 997 Lecture 6: The Flight Environment xsO2Ip6eiaY 998 Lecture 16: Seaplanes Th2N_rDfkDw 999 Lecture 7: Navigation -dOX_4lI6HY 1000 Lecture 13: Interpreting Weather Data OlQie93CwLY 1001 Lecture 8: Helicopter Aerodynamics edLnZgF9mUg 1002 Lecture 2: Airplane Aerodynamics RSuztJUlgOM 1003 Lecture 14: Human Factors EvcoYJtoQVw 1004 Lecture 15: Flight Planning 3sB64Au76h0 1005 Lecture 12: Aircraft Performance EuNXVy5-KgA 1006 Lecture 20: Flying at Night MNIYBTHc6mg 1007 Lecture 11: Aircraft Ownership and Maintenance PHtPau1c5sU 1008 Lecture 3: Learning to Fly alLh1Jdqwvg 1009 Lecture 10: Communication and Flight Information ksyY5wa5_50 1010 Lecture 19: Multi-Engine and Jets s67DO7fFM14 1011 Special Lecture: Oshkosh 2018 xPEqTH-c9Cc 1012 Lecture 9: Meteorology hmJMaVYiqwM 1013 S1E5: Film is for Everyone with Prof. David Thorburn VhBcJUnEL20 1014 S1E4: Social Impact at Scale, One Project at a Time with Dr. Anjali Sastry AHS9nATdgdU 1015 S1E3: Making Deep Learning Human with Prof. Gilbert Strang aHsRJS1BiNs 1016 Support OCW Today A60oNJ7mxXY 1017 A Day in the Life of MIT OpenCourseWare oxPhYmQdwaQ 1018 S1E2: How Africa Has Been Made to Mean with Prof. Amah Edoh fLKNjWXk71s 1019 S1E1: Nuclear Gets Personal with Prof. Michael Short rIMCTzC1A3c 1020 Chalk Radio, A Podcast about Inspired Teaching at MIT (Teaser) EH6vE97qIP4 1021 1. Introduction for 15.S12 Blockchain and Money, Fall 2018 iWpQpPbo7rM 1022 19. Primary Markets, ICOs & Venture Capital, Part 1 0UvVOMZqpEA 1023 3. Blockchain Basics & Cryptography GLVrOlHLJ1U 1024 7. Technical Challenges l0vD_FBWk0g 1025 10. Financial System Challenges & Opportunities -cZPoqnRZq4 1026 21. Post Trade Clearing, Settlement & Processing 5auv_xrvoJk 1027 2. Money, Ledgers & Bitcoin 7EXcHqLg7BI 1028 20. Primary Markets, ICOs & Venture Capital, Part 2 CJCKTixMb70 1029 24. Conclusion DsSzQfejwMk 1030 22. Trade Finance & Supply Chain JPkgJwJHYSc 1031 6. Smart Contracts and DApps KHBi3n0hUSU 1032 17. Secondary Markets & Crypto-Exchanges ObGYNQLG3us 1033 12. Assessing Use Cases W06Le8fw0vU 1034 23. Digital ID _Ycy0Dy-B1c 1035 14. Payments, Part 2 _eGNSuTBc60 1036 11. Blockchain Economics lPD9fx8fK1k 1037 15. Central Banks & Commercial Banking, Part 1 ojcOUtUwIe4 1038 13. Payments, Part 1 sMnBl0g3Ev4 1039 8. Public Policy uNqMBBbb6UI 1040 16. Central Banks & Commercial Banking, Part 2 vPJ8oQ99r9c 1041 9. Permissioned Systems w7HDA8gUbpQ 1042 4. Blockchain Basics & Consensus zGDTt9Q3vyM 1043 5. Blockchain Basics & Transactions, UTXO and Script Code Unzc731iCUY 1044 How to Speak YeyrH-Oc2p4 1045 Course Introduction | MIT 18.06SC Linear Algebra pSIAK5hzJeI 1046 Diversity Training: Addressing Stereotype Threat in the Classroom IzTRzMf8kKE 1047 Diversity Training: Introduction Video FTyWonMLLaA 1048 Fall 2019 Update from the Dean zqXBZ81bWOc 1049 Ep. 6: Element Production (Fusion) -- Part 1 -KUXPcs2Di4 1050 Ep. 3: Early Chemical Evolution 4bwMeTKC0M4 1051 Ep. 2: What the Universe Is Made of 8FtCg_bbdW0 1052 Ep. 11: Summary JM8vAGReKkc 1053 Ep. 10: Telescopes and Observing QTJuzevTGkQ 1054 Ep. 1: Introduction and Overview (RES.8-007 Cosmic Origin of the Chemical Elements) SwW1K7Dibc8 1055 Ep. 4: The First Chemical Enrichment Events _GmzGci0Cpw 1056 Ep. 7: Element Production (Fusion) -- Part 2 f2j567E1Zqo 1057 Ep. 8: Spectroscopy lB0PosKEFYc 1058 Ep. 9: Formation of the Heaviest Elements lEnolaQmkMw 1059 Ep. 5: Stellar Archaeology qHPp458m1cs 1060 16. Nuclear Reactor Construction and Operation 0MtwqhIwdrI 1061 17. Orthogonal Matrices and Gram-Schmidt 0h43aV4aH7I 1062 31. Change of Basis; Image Compression J7DzL2_Na80 1063 1. The Geometry of Linear Equations QuZL5IKpO_U 1064 24b. Quiz 2 Review TSdXJw83kyA 1065 28. Similar Matrices and Jordan Form TX_vooSnhm8 1066 29. Singular Value Decomposition UCc9q_cAhho 1067 25. Symmetric Matrices and Positive Definiteness cdZnhQjJu4I 1068 21. Eigenvalues and Eigenvectors lGGDIGizcQ0 1069 24. Markov Matrices; Fourier Series 5sZo3SrLrGA 1070 17. Synchronization Without Locks 6I26_r1BKd8 1071 8. Analysis of Multithreaded Algorithms 6JcMuFgnA6U 1072 23. High Performance in Dynamic Languages H-1-X9bkop8 1073 2. Bentley Rules for Optimizing Work IT_4fw6gfJw 1074 22. Graph Optimization L1ung0wil9Y 1075 4. Assembly Language & Computer Architecture LvX3g45ynu8 1076 10. Measurement and Timing SS5KfIFzfEE 1077 21. Tuning a TSP Algorithm Z7r4aAZ9Vqo 1078 13. The Cilk Runtime System ZusiKXcz_ac 1079 3. Bit Hacks a_R_DpsENfk 1080 7. Races and Parallelism bd-mavr5YlA 1081 18. Domain Specific Languages and Autotuning d5e_YJGXXFU 1082 12. Parallel Storage Allocation dx98pqJvZVk 1083 6. Multicore Programming euO8bqSW_Ow 1084 19. Leiserchess Codewalk gyaqXwi4BDk 1085 20. Speculative Parallelism & Leiserchess mXkPCaZUXhg 1086 16. Nondeterministic Parallel Programming nmMUUuXhk2A 1087 11. Storage Allocation ulJm7_aTiQM 1088 9. What Compilers Can and Cannot Do wt7a5BOztuM 1089 5. C to Assembly xDKnMXtZKq8 1090 14. Caching and Cache-Efficient Algorithms xwE568oVQ1Y 1091 15. Cache-Oblivious Algorithms Hz7ouec7dKo 1092 30. Radiation Dose, Dosimetry, and Background Radiation 3yqpirzxudw 1093 21. Neutron Transport 7LyvAVjQUR8 1094 1. Radiation History to the Present — Understanding the Discovery of the Neutron 9uqKU5ZDwfM 1095 28. Chernobyl Trip Report by Jake Hecla CjZjVUWMEz0 1096 27. Nuclear Materials — Radiation Damage and Effects in Matter G8LHGY3i01Q 1097 35. Food Irradiation and Its Safety Gd0QPYVYnQg 1098 3. Nuclear Mass and Stability, Nuclear Reactions and Notation, Introduction to Cross Section HSm76SpZl7o 1099 34. Radiation Hormesis HfRpkTG7Iow 1100 32. Chemical and Biological Effects of Radiation, Smelling Nuclear Bullshit Ijst4g5KFN0 1101 26. Chernobyl — How It Happened KWaGHCjsSAM 1102 25. Review of All Nuclear Interactions and Problem Set 7 Help KhT9m9kFzv8 1103 22. Simplifying Neutron Transport to Neutron Diffusion NXrGOd7gdMw 1104 2. Radiation Utilizing Technology ORbfdLUl0ik 1105 13. Practical Radiation Counting Experiments RCSCg40NgD4 1106 23. Solving the Neutron Diffusion Equation, and Criticality Relations RW2DPHAoXiQ 1107 20. How Nuclear Energy Works SgM2wxELF4U 1108 4. Binding Energy, the Semi-Empirical Liquid Drop Nuclear Model, and Mass Parabolas UDAuMq-0mEo 1109 29. Nuclear Materials Science Continued YLp8RziRbpg 1110 8. Radioactive Decay — Modes, Energetics, and Trends b2VMwG1MTHg 1111 19. Uses of Photon and Ion Nuclear Interactions — Characterization Techniques es6f90JcJ2k 1112 10. Radioactive Decay Continued i3CzkU4Ft9U 1113 24. Transients, Feedback, and Time-Dependent Neutronics jJSwWRaU9rA 1114 12. Numerical Examples of Activity, Half Life, and Series Decay kJu5qVfSphw 1115 17. Ion-Nuclear Interactions I — Scattering and Stopping Power Derivation, Ion Range kZAFntUFx8I 1116 6. The Q-Equation — The Most General Nuclear Reaction kjX4HCtlJBY 1117 14. Photon Interactions with Matter I — Interaction Methods and Gamma Spectral Identification kzOFhSJFihI 1118 31. Frontiers in Nuclear Medicine, Where One Finds Ionizing Radiation (Background and Other Sources) mJ54DfN95Zo 1119 5. Mass Parabolas Continued, Stability, and Half Life nAtTW8ZW33s 1120 7. Q-Equation Continued and Examples qAVtgc3I6ig 1121 15. Photon Interaction with Matter II — More Details, Shielding Calculations rsDEuRpOHqs 1122 18. Ion-Nuclear Interactions II — Bremsstrahlung, X-Ray Spectra, Cross Sections yYto-sIfHjo 1123 33. Long-Term Biological Effects of Radiation, Statistics, Radiation Risk z_xyx-z6arc 1124 11. Radioactivity and Series Radioactive Decays -J_xL4IGhJA 1125 Lecture 1A: Overview and Introduction to Lisp DrFkf-T-6Co 1126 Lecture 2B: Compound Data PEwZL3H2oKg 1127 Lecture 3A: Henderson Escher Example QVEOq5k6Xi0 1128 Lecture 7B: Metacircular Evaluator, Part 2 _fXQ1SwKjDg 1129 Lecture 4A: Pattern Matching and Rule-based Substitution cIc8ZBMcqAc 1130 Lecture 9A: Register Machines qp05AtXbOP0 1131 Lecture 6B: Streams, Part 2 rCqMiPk1BJE 1132 Lecture 8A: Logic Programming, Part 1 AbK4bZhUk48 1133 Lecture 10B: Storage Allocation and Garbage Collection GReBwkGFZcs 1134 Lecture 8B: Logic Programming, Part 2 JkGKLILLy0I 1135 Lecture 6A: Streams, Part 1 OscT4N2qq7o 1136 Lecture 4B: Generic Operators TqO6V3qR9Ws 1137 Lecture 10A: Compilation V_7mmwpgJHU 1138 Lecture 1B: Procedures and Processes; Substitution Model Z8-qWEEwTCk 1139 Lecture 9B: Explicit-control Evaluator aAlR3cezPJg 1140 Lecture 7A: Metacircular Evaluator, Part 1 bV87UzKMRtE 1141 Lecture 3B: Symbolic Differentiation; Quotation dO1aqPBJCPg 1142 Lecture 5A: Assignment, State, and Side-effects eJeMOEiHv8c 1143 Lecture 2A: Higher-order Procedures yedzRWhi-9E 1144 Lecture 5B: Computational Objects t36jZG07MYc 1145 An Interview with Gilbert Strang on Teaching Matrix Methods in Data Analysis, Signal Processing,... 7UJ4CFRGd-U 1146 An Interview with Gilbert Strang on Teaching Linear Algebra BZX8qSrMNyo 1147 4.2.6 Multiplexers 5BVGTxRKwOw 1148 R6. Macromolecular Electron Microscopy Applied to Fatty Acid Synthase G0pi_kU22lQ 1149 29. Metal Ion Homeostasis 5 HOXw6_ztAqQ 1150 R10. Metal-Binding Studies and Dissociation Constant Determination JB1YIT1Z-oE 1151 24. Cholesterol Homeostasis 4 RBH2RVDrJYI 1152 R2. Pre-Steady State and Steady-State Kinetic Methods Applied to Translation RfEmF7LgU7Y 1153 20. Cholesterol Biosynthesis 2 046HoQGN5F4 1154 18. PK and NRP Synthases 4 0dJS3YUxeXI 1155 4. Protein Synthesis 3 0fm50-F9934 1156 19. Cholesterol Biosynthesis 1 3cwTBMI346I 1157 35. Nucleotide Metabolism 2 6QK1PUjCkDY 1158 23. Cholesterol Homeostasis 3 9zqKwTpT0eA 1159 26. Metal Ion Homeostasis 2 CCbvqDuPr_I 1160 12. Protein Degradation 1 Dz8G2XoPrkM 1161 34. Reactive Oxygen Species 4 & Nucleotide Metabolism 1 EHtOYlvWE6k 1162 R4. Purification of Native and Mutant Ribosomes, Protein Purification H0ubjnHa5rY 1163 10. Protein Folding 3 IcyblGdCVr4 1164 32. Reactive Oxygen Species 2 JbV0aUHvROc 1165 33. Reactive Oxygen Species 3 Klw2POjgzVo 1166 15. PK and NRP Synthases 1 O1_f7Pu60Bk 1167 25. Cholesterol Homeostasis 5 & Metal Ion Homeostasis 1 PgMAfWpOuf0 1168 7. Protein Synthesis 6 PoFDK7Kwx1o 1169 1. Introduction to Biological Chemistry II UYGXwem3vN0 1170 22. Cholesterol Homeostasis 2 UzMEzYQOFRA 1171 31. Metal Ion Homeostasis 7 & Reactive Oxygen Species 1 WEH-ttvMmxc 1172 28. Metal Ion Homeostasis 4 _Rcd-NZwoi4 1173 R5. Overview of Cross-Linking, Including Photo-Reactive Cross-Linking Methods _kx9OzsCL4I 1174 R3. Pre-Steady State and Steady-State Kinetic Methods Applied to Translation itczDSdRY00 1175 R13. Fluorescence Methods jg7XtfWa_Yg 1176 R9. Cholesterol Homeostasis and Sensing jrCjdjLTQKk 1177 2. Protein Synthesis 1 q9nCI-8gYVE 1178 17. PK and NRP Synthases 3 siP7IXbPGmw 1179 9. Protein Folding 2 u5uvIbaIl3U 1180 21. Cholesterol Biosynthesis 3 & Cholesterol Homeostasis 1 uS42vSWEGTU 1181 13. Protein Degradation 2 w4nmIfPJe9E 1182 27. Metal Ion Homeostasis 3 zLJZY6VOO6w 1183 16. PK and NRP Synthases 2 0mdGZG9DDJY 1184 R7. Application of Single Molecule Methods 60m8qBOD_nM 1185 R11. Mass Spectrometry D9QJ44zENbU 1186 5. Protein Synthesis 4 Jn-Bkwf77SQ 1187 36. Nucleotide Metabolism 3 OrCYxJz2Hlc 1188 6. Protein Synthesis 5 Tl9wrTWiFQY 1189 30. Metal Ion Homeostasis 6 VUGsZgQaAZs 1190 8. Protein Folding 1 aCdDB6AsnSY 1191 14. Protein Degradation 3 j8ygU5VT8BQ 1192 R8. Application of CRISPR to Study Cholesterol Regulation noKXLhp6jbk 1193 11. Protein Folding 4 qDBdd9-T8lg 1194 3. Protein Synthesis 2 tEMkDHV2uU8 1195 R1. Determining, Analyzing, and Understanding Protein Structures vVkrHN-wnQM 1196 R12. Mass Spectrometry of the Cysteine Proteome nykOeWgQcHM 1197 1. What is Computation? Y4f7K9XF04k 1198 7. Eckart-Young: The Closest Rank k Matrix to A 74_BKWR3n0k 1199 23. New Directions in Crypto 7o5shPC0R2k 1200 12. Transaction Malleability and Segregated Witness IJquEYhiq_U 1201 1. Signatures, Hashing, Hash Chains, e-cash, and Motivation U2yAcsj7P_E 1202 8. Forks mhQebe1Y4d0 1203 6. Wallets and SPV wXWbdiOBW5w 1204 11. Fees 0Q5IimX-AAc 1205 3. Signatures 1Qws70XGSq4 1206 5. Synchronization Process and Pruning BFwc2XA8rSk 1207 17. Anonymity, Coinjoin and Signature Aggregation CCeq5PChvuk 1208 7. Catena: Efficient Non-equivocation via Bitcoin Hzv9WuqIzA0 1209 13. Payment Channels and Lightning Network P6AX8KdXAts 1210 15. Discreet Log Contracts UySc4jxbqi4 1211 18. Confidential Transactions VT2o4KCEbes 1212 4. Transactions and the UTXO model gF4Mkkhyz1Q 1213 16. MAST, Taproot, Graftroot hNR3WTboo_U 1214 14. Lightning Network and Cross-chain Swaps mBdrvfytLDQ 1215 22. Alternative Consensus Mechanisms muwNEvhy6Po 1216 10. PoW Recap, Other Fork Types yKa-KxY-YJk 1217 24. zkLedger zYzEmBlJ77s 1218 2. Proof of Work and Mining 3eQh_W8YF_g 1219 12.2.2 Activation Records and Stacks zZfr7Zqfqm4 1220 4.2.8 Worked Examples: Gates and Boolean Logic Z3-WzUhl9nQ 1221 6.2.7 Worked Examples: FSM Implementation -OduZBd1aHw 1222 16.2.6 MMU Improvements 3HIV4MnLGCw 1223 7.2.1 Latency and Throughput 3VGZANOQXAM 1224 9.2.9 Jumps 3YjMdixww4c 1225 4.2.2 Useful Logic Gates 4PkKI_S9TIQ 1226 20.2.6 Communication Topologies 5mJd--JCwBI 1227 6.2.1 Finite State Machines 7dhuZ6V9tcY 1228 18.2.4 Real Time 9M0dd86FUoA 1229 8.2.1 Power Dissipation AlT3zLxcHmw 1230 2.2.2 Analog Signaling B7F6vh_plHw 1231 20.2.4 Point-to-point Communication IbKCGrVGpco 1232 21.2.4 Shared Memory & Caches JSm74ghAvJc 1233 9.2.4 Storage JuvrTQapI_k 1234 1.2.9 Huffman Code LWE5p2sCI6o 1235 18.2.2 SVCs for Input/Output QBcQJdJk9r8 1236 13.2.5 Exceptions QCo-RtfLzyc 1237 21.2.2 Data-level Parallelism RbJV-g9Lob8 1238 1.2.6 Signed Integers: 2's complement TSmui37yrL8 1239 5.2.6 Timing Example UDow47-q5KI 1240 6.2.2 State Transition Diagrams -Zg3fxOmjVs 1241 12.2.4 Compiling a Procedure -bWtembpQjU 1242 11.2.4 Compiler Frontend 00KTZ7t_rWw 1243 12.2.3 Stack Frame Organization 0LqS5QtpSVE 1244 15.2.4 Control Hazards 0OX-DkYPB3c 1245 8.2.4 Binary Multiplication 0Q6kYWnhaks 1246 13.2.2 ALU Instructions 1eIFnKOZ-oY 1247 4.2.1 Sum of Products 1shiN7898cc 1248 10.2.6 Computability, Universality 2JxUXSG9rKo 1249 3.2.3 CMOS Recipe 3LQUrpSADx8 1250 5.2.5 Sequential Circuit Timing 56QUjMD3xoI 1251 7.2.2 Pipelined Circuits 5jZ8VZ6G2uY 1252 20.2.2 Wires 5oOdsbRPb2Y 1253 16.2.1 Even More Memory Hierarchy 6OKvJRyeKUQ 1254 14.2.1 Memory Technologies 6XV3uLfKzog 1255 15.2.3 Data Hazards 70auqrv84y8 1256 19.2.2 Semaphores 776ZuSOo6hg 1257 19.2.3 Atomic Transactions 781P9Ixmi0g 1258 9.2.2 Programmable Datapaths 8MWU1PxvaDY 1259 18.2.1 OS Device Handlers 8yO2FBBfaB0 1260 16.2.2 Basics of Virtual Memory CLiy3m2Jt-M 1261 2.2.6 Voltage Transfer Characteristic CbcJFO6VtsY 1262 10.2.2 Symbols and Labels EnmOjVUSfdY 1263 3.2.7 Lenient Gates F5-87RM_zHA 1264 11.2.1 Iterpretation and Compilation GBL28_Tw6UQ 1265 14.2.2 SRAM Ht_tyuAWmpM 1266 6.2.5 Equivalent States; Implementation IK9OVbj_Ir0 1267 21.2.1 Instruction-level Parallelism ISaYWm8T8n4 1268 21.2.5 Cache Coherence J5Mg_tqT18g 1269 3.2.5 CMOS Gates K1dbnQDAG8Q 1270 20.2.5 System-level Interconnect LW-8wbtPQIE 1271 7.2.3 Pipelining Methodology LiO-HMhxAtY 1272 5.2.2 D Latch MpJe7SMzi0E 1273 7.2.4 Circuit Interleaving Ouk7t7ViTfI 1274 10.2.4 Assembly Wrap-up P_YdbHBRzC4 1275 11.2.3 Compiling Statements PmOq8G_hs4o 1276 18.2.6 Strong Priorities R7U0Xezxo_0 1277 17.2.3 Timesharing RFu2N_6lkmw 1278 13.2.3 Load and Store RrZ8-1w7iok 1279 16.2.3 Page Faults S2c7pAFdP84 1280 8.2.2 Carry-select Adders SlwUHJ4kgjI 1281 2.2.5 Dealing with Noise TV6AtNbmLBE 1282 14.2.6 Caches UW9k06c63ts 1283 17.2.2 Processes VdRC2raV8fA 1284 4.2.5 Karnaugh Maps VxVF6QzwtwI 1285 19.2.4 Semaphore Implementation Ykep0YaxgYw 1286 17.2.5 Supevisor Calls Z8jR--1_2e4 1287 4.2.3 Inverting Logic ZPpuDMk9BOU 1288 6.2.6 Synchronization and Metastability ZUWb9HHXGHM 1289 12.2.1 Procedures 63QXdU9pliI 1290 7.2.5 Self-timed Circuits R6EzJKevAE8 1291 21.2.6 6.004 Wrap-up UuUPG_amkWc 1292 8.2.6 Part 1 Wrap-up 0h3SCozKaR4 1293 13.2.7 Worked Examples: A Better Beta 58edfKe-LO8 1294 4.2.7 Read-only Memories 5BRcFgMJLCs 1295 11.2.6 Worked Examples 9eWKuWyXYKY 1296 14.2.3 DRAM CDUH8T6Yg8A 1297 20.2.3 Buses IE9cFQ9b33U 1298 15.2.1 Improving Beta Performance M278hILkZlE 1299 10.2.8 Worked Examples: Beta Assembly OaT9zGXjAmQ 1300 2.2.3 Using Voltages Digitally RiD2xxcrsxg 1301 7.2.6 Control Structures S1PUUyVdC9M 1302 9.2.7 Memory Access Teo5DweypWU 1303 19.2.5 Deadlock Um6UH_PRJ4k 1304 13.2.1 Building Blocks VHVsCE9XmQk 1305 4.2.8 Worked Examples: Truth Tables br3mu-IK9N8 1306 3.2.6 CMOS Timing i1tUBZLWD3o 1307 8.2.3 Carry-lookahead Adders iQR_6f5Jdns 1308 15.2.5 Exceptions and Interrupts j35fYO_ASeY 1309 10.2.1 Intro to Assembly Language luHnuoDkAtU 1310 6.2.4 Roboant Example nlKV2hX1AZs 1311 14.2.10 Write Strategies q30W7ApRqjI 1312 14.2.9 Associative Caches sz4kq_ltDrM 1313 16.2.4 Building the MMU tjIFsdM-hBA 1314 4.2.8 Worked Examples: Karnaugh Maps uUKJPnwlbRI 1315 3.2.8 Worked Examples: CMOS Functions xvojobO-1Hw 1316 3.2.2 MOSFET: Electrical View yRvgtY49eXE 1317 9.2.5 ALU Instructions -RqKDpeILyU 1318 15.2.7 Worked Examples: Beta Junkyard 0aMDzMhf528 1319 18.2.8 Worked Examples: Devices and Interrupts 185WS_ZzobA 1320 9.2.6 Constant Operands 2IQxigpPMns 1321 1.2.12 Worked Examples: Error Correction 3KJeK-UUADA 1322 19.2.6 Worked Examples: Semaphores 4fTOrb1yBFU 1323 1.2.10 Error Detection and Correction 6mS1BHgm4u8 1324 15.2.7 Worked Examples: Pipelined Beta 7XEUB_dTaK0 1325 3.2.8 Worked Examples: CMOS Logic Gates 7ufoYYj15cU 1326 1.2.3 Entropy Bzqpuuoq4bI 1327 2.2.8 Worked Examples: The Static Discipline CcInkh1mKZA 1328 5.2.3 D Register Fi62zvlY2o4 1329 3.2.4 Beyond Inverters FkFYxaWhn8g 1330 1.2.11 Error Correction H0xGKKpKaRE 1331 9.2.3 The von Neumann Model J6rzqMwDUmM 1332 4.2.8 Worked Examples: Combinational Logic Timing LN0k-boDvOk 1333 5.2.8 Worked Example 2 M-ZgVhzvh24 1334 14.2.5 The Locality Principle O6yw1qkECig 1335 9.2.10 Worked Examples: Programmable Architectures R0tFDXBZvKI 1336 1.2.1 What is Information? Sj18t7hdbt8 1337 6.2.7 Worked Examples: FSM States and Transitions Sqhb-TGC4aQ 1338 11.2.2 Compiling Expressions VdLJMPppocU 1339 7.2.7 Worked Examples: Pipelining VkVe_wNU6RI 1340 5.2.4 D Register Timing WXlcxHX0R_Y 1341 2.2.4 Combinational Devices YEZUywtDJQ4 1342 12.2.6 Worked Examples: Procedures and Stacks YOABS3tTHVc 1343 14.2.8 Block Size; Cache Conflicts Y_PNOmL_yqY 1344 19.2.1 Interprocess Communication Z7pKkCDmHh0 1345 16.2.5 Contexts aR6X3OUAKkI 1346 18.2.7 Example: Priorities in Action! aheyquidLO8 1347 6.2.3 FSM States b-jgbeTojrk 1348 13.2.7 Worked Examples: Beta Control Signals cTU43KgGLFw 1349 1.2.12 Worked Examples: Huffman Encoding cVEj5p9GiBA 1350 1.2.5 Fixed-length Encodings ckZo366TWGk 1351 18.2.3 Example: Match Handler with OS d4Auh7uWEjY 1352 5.2.7 Worked Example 1 dLeI7A7VezQ 1353 18.2.5 Weak Priorities e8eEyYmLx98 1354 11.2.5 Optimization and Code Generation f866lUTRXE4 1355 1.2.8 Huffman's Algorithm ff2hWbJAipY 1356 13.2.6 Summary ffgPLOLPCYU 1357 10.2.3 Instruction Macros fg6QYiiF_c8 1358 1.2.12 Worked Examples: Quantifying Information gxU2Eo3oBPg 1359 14.2.11 Worked Examples: Cache Benefits hmPiuS0PqCs 1360 7.2.7 Worked Examples: Pipelining 2 jsJ0nR38zvo 1361 17.2.6 Worked Examples: Operating Systems m42nkRJwCKY 1362 9.2.8 Branches m_G3z-C1C2g 1363 1.2.12 Worked Examples: Two's Complement Representation muLn57VrGAA 1364 17.2.1 Recap: Virtual Memory oi1Jb-dGsWU 1365 9.2.1 Datapaths and FSMs p2DReFbW35c 1366 14.2.7 Direct-mapped Caches p2j16ebu14U 1367 15.2.6 Pipelining Summary pUmMZqwzZ10 1368 2.2.1 Concrete Encoding of Information q38KAGAKORk 1369 An Interview with Christopher Terman on Teaching Computation Structures qSLkk5o1Mc8 1370 10.2.7 Uncomputable Functions qY5Rr-PTMMc 1371 2.2.7 VTC Example qyBuzeUYs2M 1372 1.2.2 Quantifying Information r3c31nh_iOc 1373 8.2.5 Multiplier Tradeoffs r6Tk1-jZxzg 1374 4.2.4 Logic Simplification sd-ZVAw8qB0 1375 20.2.1 System-level Interfaces swdDzsfFflo 1376 16.2.7 Worked Examples: Virtual Memory uh5zxZCp70c 1377 1.2.4 Encoding usMPXTDOIn0 1378 17.2.4 Handling Illegal Instructions v-5w8ZDIa4w 1379 13.2.4 Jumps and Branches v2X-sTKCVMs 1380 14.2.11 Worked Examples: Caches vJqBBh2XFTM 1381 10.2.5 Models of Computation wP-ODG_e1i0 1382 3.2.1 MOSFET: Physical View wPwWtFMkxLo 1383 1.2.7 Variable-length Encoding xd35dftjRrc 1384 12.2.5 Stack Detective y5gPFB6uiYA 1385 21.2.3 Thread-level Parallelism yauQ7o1ZAAw 1386 15.2.2 Basic 5-Stage Pipeline ydboHy_yNts 1387 1.2.12 Worked Examples: Two's Complement Addition z3DEmSG8kPk 1388 5.2.1 Digital State zvQPV1j7SSU 1389 14.2.4 Non-volatile Storage; Using the Hierarchy Ayvwr28VKBk 1390 Class 3, Part 2: The Competitive Challenge to U.S. Manufacturing L-Y4K7LfHms 1391 Class 5, Part 1: Innovation Systems at Institutional Level & Organization of Federal Science Sup... RDvMzWDzZkc 1392 Class 1, Part 1: Economic Growth Theory and the Direct Elements in Innovation YcxHJcGU8u0 1393 Class 4, Part 2: The Challenge from Globalization for Advanced Manufacturing and New Services cvBIpLYtj1U 1394 Class 11, Part 1: Improving the Talent Base With New Education and Training Models lemfZDGJQaQ 1395 Class 3, Part 1: The Competitive Challenge to U.S. Manufacturing w6_KvH6fFe0 1396 Class 9, Part 1: The Life Science R&D Model and National Institutes of Health (NIH) 44z4NAj-dEw 1397 Class 8, Part 1: DARPA as the Connected Model & Government-Private Sector Interaction AGFamePtVUI 1398 Class 10, Part 2: The Challenge of Energy Technology Transform FY1QmZb_LDs 1399 Class 12, Part 1: The Future of Work and the Employment-Productivity Debate H-ym4rSciTM 1400 Class 6, Part 2: Public-Private Partnership & "The Valley of Death" Between Research and Devel... QcXr9NShqnw 1401 Class 4, Part 1: The Challenge from Globalization for Advanced Manufacturing and New Services Qo2B2y6cLf4 1402 Class 2, Part 1: Innovation Systems and Direct/Indirect Elements in the Innovation Ecosystem Rs3Ll0KYfcA 1403 Class 11, Part 2: Improving the Talent Base With New Education and Training Models UFu_shvdwlE 1404 Class 9, Part 2: The Life Science R&D Model and National Institutes of Health (NIH) UbwGHnn3B_M 1405 Class 5, Part 2: Innovation Systems at Institutional Level & Organization of Federal Science Sup... XGyUFPCwlPI 1406 Class 2, Part 2: Innovation Systems and Direct/Indirect Elements in the Innovation Ecosystem bnEPjrsCaYg 1407 Class 6, Part 1: Public-Private Partnership & "The Valley of Death" Between Research and Devel... dCw-x9ZOljY 1408 Class 7, Part 2: The Organization of Innovation Systems at the Face-to-Face Level j563wGImp9U 1409 Class 12, Part 2: The Future of Work and the Employment-Productivity Debate lwSNTxl4b4Y 1410 Class 7, Part 1: The Organization of Innovation Systems at the Face-to-Face Level mCxtdohSJZQ 1411 Class 10, Part 1: The Challenge of Energy Technology Transform n0QLcw-CHmk 1412 Class 1, Part 2: Economic Growth Theory and the Direct Elements in Innovation on1rmY3Tw5U 1413 Class 8, Part 2: DARPA as the Connected Model & Government-Private Sector Interaction gSfc4GhlZ44 1414 2 Million Subscribers! THANK YOU!!! 3Kn1LzkT5sA 1415 Please be one of the 1,000 donors MIT OCW needs today! -7_Q3G1za30 1416 Studentenvideo: Quantenzeitentwicklung mit dem Fourier-Transformations-Algorithmus des Split-Ope... 1Ed3U4rmyXU 1417 Student Video: Heat Transfer in a Material 5An3DOfA0Zk 1418 Student Video: Particle in a Tube 6mndLA1SceA 1419 Student Video: Finding the Perfect Diamond: Why It's Impossible 80hnG8EH5tA 1420 Student Video: Simulation of Vacancy Diffusion LqwvVAtEIx8 1421 Student Video: A Visualisation of Crystallographic Point Groups a2xqcqRYosg 1422 Student Video: Creating Mathematica Functions to Determine Degree of Crystallinity from XRD Plots aOiW2XRxEcY 1423 Student Video: Modeling & Energy Analysis of Liquid Crystals cFZaKWiBD6I 1424 Student Video: Liquid Crystals o96K8fkOrG8 1425 Student Video: Quantum Time Evolution Using the Split Operator Fourier Transform Algorithm odOULv5UqAg 1426 Student Video: Nanoparticle-polymer Network pRmUADgEf98 1427 Student Video: Crystallography, a Visualisation Tool for CS, BCC and FCC Bravais Lattice Structures. peJUDjHJGb4 1428 Student Video: Spherical Distribution Problem qNzfiYTo50I 1429 Student Video: Potential Energy Surfaces vGyHgaXnAMA 1430 Student Video: Tight Binding Model yb-cS9xeNqs 1431 Video del estudiante: Una introducción básica y divertida a las estructuras cristalinas (español) zH76mIS0ARs 1432 Student Video: Mohr's Circles -MJrb7xScbU 1433 Student Video: 2D Brillouin Zones 0sGhEhOffUE 1434 Video de l'estudiant: superfícies d'energia potencial 4-YaJUUTrNw 1435 Student Video: Thin Film Rainbows EmeWBxXlzKA 1436 Student Video: Mohr’s Circle MloLY1k3rLg 1437 Vidéo étudiante: Transfert de chaleur dans un matériau Sml2lkWfd1g 1438 Student Video: A Basic and Fun Introduction to Crystalline Structures (English) Tj3Hpf_HMk4 1439 Student Video: Real and Reciprocal Space in 2D and 3D koHirQQ-Td0 1440 Student Video: Hooke's Law in Cubic Solids n9eMl6uLZeU 1441 Student Video: Fluid Flow in Pipes and Rivers xdm3Jz3IgwE 1442 Student Video: Visualizing the Energies of Screw Dislocations rZS2LGiurKY 1443 Lecture 36: Alan Edelman and Julia Language cxTmmasBiC8 1444 35. Finding Clusters in Graphs 0Qws8BuK3RQ 1445 34. Distance Matrices, Procrustes Problem L3-WFKCW-tY 1446 33. Neural Nets and the Learning Function hwDRfkPSXng 1447 Lecture 32: ImageNet is a Convolutional Neural Network (CNN), The Convolution Rule 1pFv7e9xtHo 1448 31. Eigenvectors of Circulant Matrices: Fourier Matrix p-bXJIa7QVI 1449 Lecture 30: Completing a Rank-One Matrix, Circulants! sx00s7nYmRM 1450 26. Structure of Neural Nets for Deep Learning lZrIPRnoGQQ 1451 27. Backpropagation: Find Partial Derivatives k3AiUhwHQ28 1452 25. Stochastic Gradient Descent feb9j65Iz4w 1453 24. Linear Programming and Two-Person Games wrEcHhoJxjM 1454 23. Accelerating Gradient Descent (Use Momentum) AeRwohPuUHQ 1455 22. Gradient Descent: Downhill to a Minimum nvXRJIBOREc 1456 Lecture 21: Minimizing a Function Step by Step nrDkb2MAwSA 1457 20. Definitions and Inequalities 2K7CvGnebO0 1458 19. Saddle Points Continued, Maxmin Principle xaSL8yFgqig 1459 Lecture 18: Counting Parameters in SVD, LU, QR, Saddle Points 9BYsNpTCZGg 1460 Lecture 17: Rapidly Decreasing Singular Values AdTvkFsqcDc 1461 16. Derivatives of Inverse and Singular Values z3SmljnD_nQ 1462 15. Matrices A(t) Depending on t, Derivative = dA/dt XhSk_Lw2X_U 1463 14. Low Rank Changes in A and Its Inverse z0ykhV15wLw 1464 Lecture 13: Randomized Matrix Multiplication d32WV1rKoVk 1465 12. Computing Eigenvalues and Singular Values MuEW9pG9oxE 1466 Lecture 11: Minimizing ‖x‖ Subject to Ax = b Z_5uLqcwDgM 1467 Lecture 10: Survey of Difficulties with Ax = b ZUU57Q3CFOU 1468 9. Four Ways to Solve Least Squares Problems NcPUI7aPFhA 1469 Lecture 8: Norms of Vectors and Matrices rYz83XPxiZo 1470 6. Singular Value Decomposition (SVD) xsP-S7yKaRA 1471 5. Positive Definite and Semidefinite Matrices k095NdrHxY4 1472 4. Eigenvalues and Eigenvectors Xa2jPbURTjQ 1473 3. Orthonormal Columns in Q Give Q'Q = I or6C4yBk_SY 1474 Lecture 2: Multiplying and Factoring Matrices YiqIkSHSmyc 1475 Lecture 1: The Column Space of A Contains All Vectors Ax Cx5Z-OslNWE 1476 Course Introduction of 18.065 by Professor Strang 6ROuKtm5zds 1477 34. Electronic Spectroscopy and Photochemistry G1sBybS2M48 1478 24. Baumol's Disease K7lqWX6fq-Q 1479 22. Public Transportation Systems CJehtdXHR7Q 1480 21. Fare Policy, Structure, and Technology I2K5WnG_TLs 1481 20. Transit Service Reliability K2g0trGAfgo 1482 19. Transit Signal Priority mp7Nz8CUPBM 1483 17. Customer Information Strategies _FTwuE36SUA 1484 13. Vehicle Scheduling avWOCswUJyI 1485 10. Origin, Destination, and Transfer Inference Tsn0xSQjo14 1486 9. Performance Models Wlz_17id1BM 1487 8. Ridership Forecasting YGpxOuDJdJw 1488 7. Cost Estimation dttSgzTJKK4 1489 6. Modal Capacities and Costs aLqEG43nKVE 1490 5. Short-range Planning (cont.) h5x7-zejY8c 1491 4. Short-range Planning MlDdfgjpBe0 1492 3. Modal Characteristics and Roles JPCA2qE9MSw 1493 2. Data Collection Techniques and Program Design wzB8Rhm3xCU 1494 1. Introduction (for 1.258J Public Transportation Systems, Spring 2017) 1XiS4VlEFt8 1495 Spring 2019 Update from the Dean Ek90ivXyusk 1496 Innovations Across the Agriculture Value Chain: An Opportunity for Entrepreneurs YEkx5ZKWM4s 1497 Innovación en tecnología pública con implementación en el mundo real EZCmSXZnT6Q 1498 Using Technology to Improve Small Farming in Brazil HaySEpWEsdU 1499 An Interview with Anjali Sastry on Facilitating a Customized Learning Experience for Sloan Fellows omuDD2rZqlE 1500 Public Tech Innovation with Real-world Implementation sv6oW4AEVOY 1501 Usando a tecnologia para melhorar a agricultura de pequeno porte no Brasil ek8uUMmoziU 1502 Happy Pi Day! EBYsEEcMFmY 1503 Pi Day is almost here! FykIDSC3bik 1504 Pi is... _OZXEb8FxZQ 1505 L1.1 General problem. Non-degenerate perturbation theory 2-Td1mID8oQ 1506 L4.2 The uncoupled and coupled basis states for the spectrum 5s6rUYpVYjg 1507 L13.1 Transition rates induced by thermal radiation 7Y3qcKzO_mY 1508 L14.1 Gauge invariance of the Schrödinger Equation 8Uh0qSp_Vck 1509 L22.2 First Born Approximation. Calculation of the scattering amplitude 41ee6EsHchA 1510 L19.2 Energy eigenstates: incident and outgoing waves. Scattering amplitude 4BM58741VOg 1511 L6.5 Semiclassical approximation and local de Broglie wavelength 83lPKkTfGlY 1512 L7.4 Connection formula stated and example 868odGqmB1E 1513 L19.4 Differential as a sum of partial waves 9JhX_UNcQvE 1514 L2.3 Degenerate Perturbation theory: Example and setup 9lc7mxULRF0 1515 L17.4 Molecules and energy scales A4-kg_F34qc 1516 L3.3 Degeneracy resolved to second order FIef9sP-Yq8 1517 L16.5 Landau-Zener transitions (continued) G-5KHKrNPMs 1518 L24.3 The symmetrization postulate GZzrMyY01tE 1519 L19.1 Elastic scattering defined and assumptions Tcv3_Gk1Ysg 1520 L16.3 Error in the adiabatic approximation YulNobAZgkA 1521 L12.5 Atom-light interactions: dipole operator _WwudFI6YRs 1522 L9.2 The interaction picture equation in an orthonormal basis _bTZbn7M2Hc 1523 L1.4 First order correction to the state. Second order correction to energy _p3NpyfNp78 1524 L2.1 Remarks and validity of the perturbation series bD0CFnI9eug 1525 L8.1 Airy functions as integrals in the complex plane BTru_P0ruYQ 1526 L21.2 Phase shifts and impact parameter BiLtNbncW8o 1527 L8.4 Deriving the connection formulae (continued) logical arrows FA11OqJYnaE 1528 L10.3 Integrating over the continuum to find Fermi's Golden Rule FXRRP-PB4Bk 1529 L4.1 Scales and zeroth-order spectrum NSac7cMQnJw 1530 L6.3 Weak-field Zeeman effect; the projection lemma NjhuAak0jmM 1531 L23.4 Symmetric and Antisymmetric states of N particles Prx5mnE7BUM 1532 L9.1 The interaction picture and time evolution R6RePgr4oBo 1533 L3.1 Remarks on a 'good basis' RWPfOV0CV5Y 1534 L17.3 Properties of Berry's phase TDYMriH63us 1535 L11.4 Ionization of hydrogen: matrix element for transition U4zZhQz1Xqc 1536 L14.2 Quantization of the magnetic field on a torus Ug0HxeKGC8s 1537 L20.2 The one-dimensional analogy for phase shifts Uux0VkKaoxY 1538 L14.4 Landau levels (continued). Finite sample WlZf4aOkNMQ 1539 L6.1 Zeeman effect and fine structure Y5oTQvNt47I 1540 L5.2 Interpretation of the Darwin correction from nonlocality _85xTt0cU3s 1541 L2.4 Degenerate Perturbation Theory: Leading energy corrections aY8iTiAfRzs 1542 L18.2 Effective nuclear Hamiltonian. Electronic Berry connection dodj1I-IjWM 1543 L1.2 Setting up the perturbative equations gXj4irGhxuo 1544 L21.1 General computation of the phase shifts -pMowqywuIY 1545 L1.3 Calculating the energy corrections 0AM6arPSszI 1546 L15.4 Instantaneous energy eigenstates and Schrodinger equation 2N0OXAiX-BM 1547 L21.3 Integral equation for scattering and Green's function 33kB8JQRpjI 1548 L5.5 Assembling the fine-structure corrections 67yCE-yt0T8 1549 L5.1 Evaluating the Darwin correction 7Y5me3mwXpA 1550 L7.1 The WKB approximation scheme gRlrh4lRapM 1551 L20.1 Review of scattering concepts developed so far kPxBd_S5tsA 1552 L10.1 Box regularization: density of states for the continuum loVzNly0Gyw 1553 L7.2 Approximate WKB solutions lr4HqQ_sLO0 1554 L4.4 Dirac equation for the electron and hydrogen Hamiltonian mas9avjieP0 1555 L5.4 Spin-orbit correction nYlmkoiq4CI 1556 L3.4 Degeneracy resolved to second order (continued) nd_sryUc1tc 1557 L10.4 Autoionization transitions o10QADeeK04 1558 L22.3 Diagrammatic representation of the Born series. Scattering amplitude for spherically symm... omqSBV--uQ4 1559 L18.3 Example: The hydrogen molecule ion papfq4sdC3w 1560 L19.3 Differential and total cross section qk6l3z5ab0o 1561 L10.2 Transitions with a constant perturbation tmKD8T_Lm2I 1562 L14.3 Particle in a constant magnetic field: Landau levels vK7T72HPQ10 1563 L23.1 Permutation operators and projectors for two particles wULHVefheCU 1564 L6.4 Strong-field Zeeman wWPh_6ex8qw 1565 L11.1 Harmonic transitions between discrete states yHfFsuYGgaQ 1566 L13.5 Charged particles in EM fields: Schrodinger equation zUHOeWom7qs 1567 L24.4 The symmetrization postulate (continued) 6CeljmHgd0w 1568 L24.1 Symmetrizer and antisymmetrizer for N particles BkCyJ6Nr7qU 1569 L15.3 Phase space and intuition for quantum adiabatic invariants DYJM_P4sG-c 1570 L15.1 Classical analog: oscillator with slowly varying frequency Du9eDHwGeAw 1571 L3.2 Degeneracy resolved to first order; state and energy corrections Kk7cc15gWF8 1572 L16.2 Analysis with an orthonormal basis of instantaneous energy eigenstates pBvHt3Nea6Q 1573 L12.3 Einstein's argument: the need for spontaneous emission pgEFvhkEp-c 1574 L16.1 Quantum adiabatic theorem stated VaBMK5JSz2I 1575 L23.2 Permutation operators acting on operators IqyTq4n1f2g 1576 L11.3 Ionization of hydrogen: conditions of validity, initial and final states KbAgNwrpUTw 1577 L24.2 Symmetrizer and antisymmetrizer for N particles (continued) MtK9rIbdlis 1578 L20.4 Cross section in terms of partial cross sections. Optical theorem OyZbj4_P7JM 1579 L12.1 Ionization rate for hydrogen: final result PAlB9kA7c-s 1580 L12.4 Einstein's argument: B and A coefficients UOoKUdjVP78 1581 L18.1 Born-Oppenheimer approximation: Hamiltonian and electronic states YT4ODWpKmGY 1582 L20.5 Identification of phase shifts. Example: hard sphere ZzUkt-UQCX8 1583 L22.4 Identical particles and exchange degeneracy a4Qtf5D0rso 1584 L20.3 Scattering amplitude in terms of phase shifts dNKAsbdHDCs 1585 L9.4 Setting up perturbation theory eRFQL3o4DO4 1586 L7.3 Validity of the WKB approximation iGG9EG3SNz0 1587 L17.2 Berry's phase and Berry's connection jhIU1msmvaY 1588 L2.2 Anharmonic Oscillator via a quartic perturbation qaj4u42XZLg 1589 L8.2 Asymptotic expansions of Airy functions sv1hK_dLVzE 1590 L11.2 Transition rates for stimulated emission and absorption processes tl7q_VZ3eIQ 1591 L4.3 The Pauli equation for the electron in an electromagnetic field yg3NGFpZr4w 1592 L16.4 Landau-Zener transitions KYabRbRR-dU 1593 L5.3 The relativistic correction N9f0MIzNcmI 1594 L6.2 Weak-field Zeeman effect; general structure OCbC7fRsL7k 1595 L13.2 Transition rates induced by thermal radiation (continued) YWxY6mZwRSQ 1596 L23.3 Permutation operators on N particles and transpositions fFSii5VxO4I 1597 L13.3 Einstein's B and A coefficients determined. Lifetimes and selection rules gX2y3PHMmnk 1598 L22.1 Setting up the Born Series lw5ka_lJFkU 1599 L8.3 Deriving the connection formulae oEBwIJZ3RNM 1600 L17.1 Configuration space for Hamiltonians oyU5uvPqzkE 1601 L9.3 Example: Instantaneous transitions in a two-level system qxBhW2DRnPg 1602 L15.2 Classical adiabatic invariant xHE5uf-S9Iw 1603 L12.2 Light and atoms with two levels, qualitative analysis xVZ-lIuIi7A 1604 L13.4 Charged particles in EM fields: potentials and gauge invariance BOryXuUMjI0 1605 28. Modern Electronic Structure Theory: Basis Sets 3RGYj06NSTI 1606 9. The Harmonic Oscillator: Creation and Annihilation Operators BEs4K6LSGzo 1607 36. Time Dependence of Two-Level Systems: Density Matrix, Rotating Wave Approximation N4vMgwWT-80 1608 8. Quantum Mechanical Harmonic Oscillator 8kM9quINTHI 1609 20. Hydrogen Atom I 6dJnvu3-LeU 1610 29. Modern Electronic Structure Theory: Electronic Correlation MAbnZhFX3nk 1611 31. Time-Dependent Perturbation Theory II: H is Time-Dependent: Two-Level Problem QkMB_0jOvVA 1612 32. Intermolecular Interactions by Non-Degenerate Perturbation Theory S-_PFdnImLM 1613 5. Quantum Mechanics: Free Particle and Particle in 1D Box YmP1BADSAnc 1614 7. Classical Mechanical Harmonic Oscillator geKBtyDcZZY 1615 3. Two-Slit Experiment; Quantum Weirdness lfH99vfhiI4 1616 17. Rigid Rotor I; Orbital Angular Momentum mPSDaN4AJl8 1617 25. Molecular Orbital Theory II; H2+, A2, AB Diatomics sZlTriaYRM0 1618 26. Qualitative MO Theory: Hückel 4bfrkd8_zPo 1619 6. 3-D Box and QM Separation of Variables 6wbWEDAg3B0 1620 18. Rigid Rotor II. Derivation by Commutation Rules 9WthWtTxdj0 1621 10. The Time-Dependent Schrödinger Equation DpNZ70Uam0M 1622 22. Helium Atom IZ405_YLKJQ 1623 11. Wavepacket Dynamics for Harmonic Oscillator and PIB IoED49Ha8-o 1624 24. Molecular Orbital Theory I; Variational Principle and Matrix Mechanics JzW4RYICOdA 1625 23. Many-Electron Atoms RGskPrZopRE 1626 35. Delta-Functions, Eigen-Functions of X, Discrete Variable Representation SSVdDcC2LrQ 1627 4. Classical Wave Equation and Separation of Variables YKfoSx16mXk 1628 16. Non-Degenerate Perturbation Theory II: HO using a,a† Z0ALwCckM24 1629 27. Non-Degenerate Perturbation Theory III _TEMQhpsGFg 1630 2. Wave Nature of the Electron and the Internal Structure of an Atom _iSqhxWjkq8 1631 19. Spectroscopy: Probing Molecules with Light dHXZ2bFV6EE 1632 12. Catch Up and Review & Postulates gkRRlmes_jE 1633 33. Electronic Spectroscopy: Franck-Condon yBCdnNIAiQg 1634 15. Non-Degenerate Perturbation Theory I zR6vXHHQZZA 1635 30. Time-Dependent Perturbation Theory I: H is Time-Independent, Zewail Wavepacket. zq0KO8Gmrm0 1636 21. Hydrogen Atom II; Rydberg States zwH9MjZl3v4 1637 14. From Hij Integrals to H Matrices II zwz9M1XNn-c 1638 13. From Hij Integrals to H Matrices I XxRjzphItU0 1639 1. Quantum Mechanics—Historical Background, Photoelectric Effect, Compton Scattering 9T89uDdO7UI 1640 When Curriculum Becomes Art Practice: Art Education as Engagement with the World TtaWB0bL3zQ 1641 Making Something From Nothing: Intentional Public Disruptions, Art, and Social Responsibility pXQLdl4KUUU 1642 Double Taking and Troublemaking: Socially Engaged Practice Enabling Difficult Conversations II vAuJO7rv92U 1643 When Curriculum Becomes Art Practice: Educational Experience as Intentionally Disruptive Pedagogy w7Eao7aBIlw 1644 Making Something from Nothing: Community, Water, Pedagogy, and Learning JrP0kUuZv20 1645 Double Taking and Troublemaking: Reflecting and Disrupting K0_VieRmuq4 1646 When Curriculum Becomes Art Practice: Conventional Practice and Conceptual Explorations SvfXfwOWv8A 1647 Double Taking and Troublemaking: Socially Engaged Practice Enabling Difficult Conversations I W5AMaIxtHZc 1648 When Curriculum Becomes Art Practice: Performing Explorations of Context and Meaning Making S5HmxtARo8Q 1649 Making Something from Nothing: Appropriate Technology as Intentionally Disruptive Responsibility CaLv-IWX5vo 1650 5.2.12 An Introduction to Text Analytics - Video 7: Predicting Sentiment 1-_pwzJ8nPw 1651 5.3.3 How IBM Built a Jeopardy Champion - Video 2: The Game of Jeopardy D-9R7zfUTWw 1652 4.3.1 Healthcare Costs - Video 1: The Story of D2Hawkeye D2FQ-JnltPw 1653 2.3.9 Sports Analytics - Video 5: Winning the World Series Kdbia6SXSFA 1654 7.3.3 Visualization for Law and Order - Video 2: Visualizing Crime Over Time -mW-DYFyGqg 1655 1.2.1 The Analytics Edge - Video 1: Introduction to The Analytics Edge 0RaZe62Rg2A 1656 8.2.8 An Introduction to Linear Optimization - Video 5: Visualizing the Problem 3cN7bSffVm4 1657 4.2.5 An Introduction to Trees - Video 3: Splitting and Predictions 4bsc1II5KK0 1658 7.4.5 R7. Visualization - Video 4: A Better Visualization 7MAVWhOUTGU 1659 2.2.13 An Introduction to Linear Regression - Video 7: Making Predictions ByiCbXfwGbc 1660 7.1.1 Welcome to Unit 7 - Visualizing the World: An Introduction to Visualization D8HcmzYnBv0 1661 3.2.10 Introduction to Logistical Regression - Video 6: ROC Curves E_KUHMuoPLE 1662 1.3.4 Working with Data - Video 2: Getting Started in R Goo1EUY-Y8M 1663 1.3.10 Working with Data - Video 5: Data Analysis - Summary Statistics and Scatterplots H5uEHZBRWtc 1664 3.3.11 The Framingham Heart Study - Video 6: Overall Impact HIIclMih_zQ 1665 4.3.5 Healthcare Costs - Video 3: The Variables J9-3p_J9o2Y 1666 9.4.3 R9. Operating Room Scheduling - Video 2: An Optimization Model NZbQZVMDeEc 1667 2.4.2 R2. Moneyball in the NBA - Video 1: The Data QDzTeo6n0Q8 1668 1.2.6 The Analytics Edge - Video 6: This Class 08Ih9GGB5-c 1669 1.2.5 The Analytics Edge - Video 5: Example 4 - D2Hawkeye 6m4l2k9hBZw 1670 8.2.4 An Introduction to Linear Optimization - Video 3: The Problem Formulation WYrDTn37m-I 1671 4.3.3 Healthcare Costs - Video 2: Claims Data kYjwB3vfnZg 1672 2.3.3 Sports Analytics - Video 2: Making It to the Playoffs 12KzzzmaYrw 1673 4.3.13 Healthcare Costs - Video 7: Baseline Method and Penalty Matrix 4MhGi6JSGbA 1674 7.3.5 Visualization for Law and Order - Video 3: A Line Plot U57wvHVpe-8 1675 3.2.4 Introduction to Logistical Regression - Video 3: Logistic Regression Vd6yR63nfHY 1676 1.2.2 The Analytics Edge - Video 2: Example 1 - IBM Watson W5zVgQ4SbX8 1677 4.2.3 An Introduction to Trees - Video 2: CART Y8dMlEv-epg 1678 1.4.2 R1. Understanding Food - Video 1: The Importance of Food and Nutrition aDdkt8rRWGs 1679 8.2.10 An Introduction to Linear Optimization - Video 6: Sensitivity Analysis ayrdDJPAD5M 1680 9.4.4 R9. Operating Room Scheduling - Video 3: Solving the Problem cT3KA-QLEI0 1681 9.2.5 Sports Scheduling - Video 3: Solving the Problem lm_qReHVm0A 1682 3.4.4 R3. Election Forecasting - Video 3: A Sophisticated Baseline Method n19qLvOY-rc 1683 5.2.4 An Introduction to Text Analytics - Video 3: Creating the Dataset ril5Z4UxI3w 1684 8.4.4 R8. Google AdWords - Video 3: Prices and Queries xEjZjz7oxbI 1685 6.2.5 An Introduction to Clustering - Video 3: Movie Data and Clustering 1r6cLE2BoTA 1686 7.4.1 Welcome to Recitation 7 - The Good, the Bad, and the Ugly in Visualization 7QJyMB9qGQg 1687 8.3.11 Radiation Therapy - Video 6: The Analytics Edge UjbutTp3z3I 1688 8.3.5 Radiation Therapy - Video 3: Solving the Problem VDtL2g9Viik 1689 8.1.1 Welcome to Unit 8 - Airline Revenue Management: An Introduction to Linear Optimization WCb-_SRDzKE 1690 4.4.1 Welcome to Recitation 4 - Location, Location, Location: Regression Trees for Housing Data WTuwV-rWxUc 1691 6.2.1 An Introduction to Clustering - Video 1: Introduction to Netflix d2CfWJkklvo 1692 1.3.2 Working with Data - Video 1: History of R exav1FKMfbw 1693 1.4.3 R1. Understanding Food - Video 2: Working with Data in R fsF79kN9G28 1694 6.3.5 Predictive Diagnosis - Video 3: Predicting Heart Attacks Using Clustering fuUC0WVeKsg 1695 6.2.9 An Introduction to Clustering - Video 5: Hierarchical Clustering gE1wRDQMR8E 1696 2.2.11 An Introduction to Linear Regression - Video 6: Correlation and Multicollinearity pj_Ro7sFpUE 1697 7.2.9 An Introduction to Visualization - Video 5: Advanced Scatterplots Using ggplot vsAzc7GvQSs 1698 4.4.3 R4. Regression Trees- Video 2: The Data Goi9xfybb80 1699 4.3.9 Healthcare Costs - Video 5: CART to Predict Cost WacNWdXhvVM 1700 2.3.2 Sports Analytics - Video 1: The Story of Moneyball 8jpO-p1YvdM 1701 6.4.3 R6. Segmenting Images - Video 2: Clustering Pixels 9lMOz_7bIGU 1702 1.2.3 The Analytics Edge - Video 3: Example 2 - eHarmony CROEh9u0VLM 1703 4.2.11 An Introduction to Trees - Video 6: Cross-Validation DCcPG4aS5I0 1704 8.2.12 An Introduction to Linear Optimization - Video 7: Connecting Flights E16wcCKx89w 1705 2.4.5 R2. Moneyball in the NBA - Video 4: Making Predictions FqiB9tmtdSc 1706 5.2.8 An Introduction to Text Analytics - Video 5: Pre-Processing in R IZ0qGEZkTIw 1707 4.4.5 R4. Regression Trees - Video 4: Regression Trees MK3DduTjcrA 1708 8.2.2 An Introduction to Linear Optimization - Video 2: A Single Flight S-UZTbRqjeo 1709 5.4.3 R5. Predictive Coding - Video 2: The Data _L315IjxyUM 1710 5.3.7 How IBM Built a Jeopardy Champion - Video 4: How Watson Works - Steps 1 and 2 _ozQJncmJYk 1711 1.4.5 R1. Understanding Food - Video 4: Creating Plots in R ag4Qe2uheP0 1712 4.3.11 Healthcare Costs - Video 6: Claims Data in R BvZlP1ZyToo 1713 8.4.5 R8. Google AdWords - Video 4: Modeling the Problem DU0_NM0mZPE 1714 7.3.7 Visualization for Law and Order - Video 4: A Heatmap Du0HgYO3E6U 1715 2.2.7 An Introduction to Linear Regression - Video 4: Linear Regression in R EXYgISgOw0g 1716 8.3.3 Radiation Therapy - Video 2: An Optimization Problem JcAB1JeDs8Y 1717 5.2.10 An Introduction to Text Analytics - Video 6: Bag of Words in R JcKvI821H0c 1718 3.2.6 Introduction to Logistical Regression - Video 4: Logistic Regression in R MYcoFYXPba4 1719 5.1.1 Welcome to Unit 5 - Turning Tweets into Knowledge: An Introduction to Text Analytics R250-aMpyAo 1720 6.4.8 R6. Segmenting Images - Video 6: Detecting Tumors S0g0ad4zX7A 1721 8.2.14 An Introduction to Linear Optimization - Video 8: The Edge of Revenue Management SSzcvj2biAQ 1722 9.4.2 R9. Operating Room Scheduling - Video 1: The Problem UQHz2U1ik9c 1723 6.2.11 An Introduction to Clustering - Video 6: Getting the Data YaEufT_7EbU 1724 4.2.13 An Introduction to Trees - Video 7: The Model v. The Experts ag7TLcT7VPQ 1725 1.1.1 Welcome to Unit 1: An Introduction to Analytics akNw8CEHC_c 1726 8.4.6 R8. Google AdWords - Video 5: Solving the Problem bzxoBEh4is8 1727 9.3.7 eHarmony - Video 4: The Analytics Edge c_2RtTEkyo8 1728 3.2.8 Introduction to Logistical Regression - Video 5: Thresholding -G_d3A0x_0Y 1729 9.1.1 Welcome to Unit 9: An Introduction to Integer Optimization 2rnsbodsJVc 1730 7.4.6 R7. Visualization - Video 5: World Maps in R eUZHMoJ1EJE 1731 5.2.14 An Introduction to Text Analytics - Video 8: Conclusion isTQo2B_1Ng 1732 3.4.3 R3. Election Forecasting - Video 2: Dealing with Missing Data j1d4_wrUEVs 1733 6.4.2 Recitation 6 - Video 1: Image Segmentation kTOfGiScMsI 1734 7.2.3 An Introduction to Visualization - Video 2: The World Health Organization (WHO) mi-pl3_fIfc 1735 3.3.9 The Framingham Heart Study - Video 5: Interventions plpDQpjB044 1736 7.3.9 Visualization for Law and Order - Video 5: A Geographical Hot Spot Map t8nLB1AmUgE 1737 6.4.4 R6. Segmenting Images - Video 3: Hierarchical Clustering 05DWB1NzozM 1738 9.2.7 Sports Scheduling - Video 4: Logical Constraints 0fWDzzMSk8I 1739 8.4.7 R8. Google AdWords - Video 6: A Greedy Approach 0x4PfWpy-ls 1740 3.3.5 The Framingham Heart Study - Video 3: A Logistical Regression Model 1G6iJmM64LA 1741 2.3.11 Sports Analytics - Video 6: The Analytics Edge in Sports 1i5TDkri78Y 1742 8.4.8 R8. Google AdWords - Video 7: Sensitivity Analysis 2wtc5Su-fZA 1743 7.2.5 An Introduction to Visualization - Video 3: What is Data Visualization? 35kwBJQwmLg 1744 6.4.6 R6. Segmenting Images - Video 4: MRI Image 4YP38f2u36E 1745 2.4.3 R2. Moneyball in the NBA - Video 2: Playoffs and Wins cllmFIIbzrc 1746 4.4.6 R4. Regression Trees - Video 5: Putting it all Together e8yvJp0VqtI 1747 5.2.6 An Introduction to Text Analytics - Video 4: Bag of Words ee6E6aUGpm0 1748 6.2.3 An Introduction to Clustering - Video 2: Recommendation Systems iJvEgQkLjow 1749 4.3.15 Healthcare Costs - Video 8: Predicting Healthcare Cost in R jcvxkX2V-SM 1750 4.4.4 R4. Regression Trees - Video 3: Geographical Predictions m0Yce2rtZJ8 1751 3.2.14 Introduction to Logistical Regression - Video 8: The Analytics Edge mw0jJm_3KXs 1752 3.4.6 R3. Election Forecasting - Video 5: Test Set Predictions o8Zdk_3wVSo 1753 3.2.12 Introduction to Logistical Regression - Video 7: Interpreting the Model uo0EmonbUhU 1754 3.4.5 R3. Election Forecasting - Video 4: Logistic Regression Models va-mL-_jui4 1755 6.3.9 Predictive Diagnosis - Video 5: The Analytics Edge wYcMru4gYF4 1756 3.2.1 Introduction to Logistical Regression - Video 1: Replicating Expert Assessment xeszYyi9ooM 1757 4.3.7 Healthcare Costs- Video 4: Error Measures zasCvIWLyRA 1758 8.4.3 R8. Google AdWords - Video 2: How Online Advertising Works 5CExAUWzHEQ 1759 4.4.7 R4. Regression Trees - Video 6: The CP Parameter 6Rl8scykyEQ 1760 5.3.5 How IBM Built a Jeopardy Champion - Video 3: Watson's Database and Tools 6m39f8lDONs 1761 5.4.7 R5. Predictive Coding - Video 6: Evaluating the Model 8T248H2ax8c 1762 8.3.9 Radiation Therapy - Video 5: Sensitivity Analysis 8hBr-bpykso 1763 7.3.11 Visualization for Law and Order - Video 6: A Heatmap on the United States 8ryWylXv0WE 1764 6.4.9 R6. Segmenting Images - Video 7: Comparing Methods BKsi-Khu7Bs 1765 4.1.1 Welcome to Unit 4 - Judge, Jury, and Classifier: An Introduction to Trees En0xvjBnmfU 1766 7.4.4 R7. Visualization - Video 3: Bar Charts in R FYXIRXnQ8Fc 1767 1.3.12 Working with Data - Video 6: Data Analysis - Plots and Summary Tables IXwPD4R6V6M 1768 4.4.8 R4. Regression Trees - Video 7: Cross-Validation 5tCSR5L4nWI 1769 2.2.5 An Introduction to Linear Regression - Video 3: Multiple Linear Regression 8fW7ooZLIuc 1770 5.2.1 An Introduction to Text Analytics - Video 1: Twitter 8p_4qP03AM0 1771 8.3.1 An Application of Linear Optimization - Video 1: Introduction to Radiation Therapy 98cyATFdwIk 1772 8.3.7 Radiation Therapy - Video 4: A Head and Neck Case 9aKidJvppF0 1773 9.2.1 Sports Scheduling - Video 1: Introduction 9i1sOSIccgw 1774 3.4.2 R3. Election Forecasting - Video 1: Election Prediction AByfsx3Dkek 1775 8.4.2 R8. Google AdWords - Video 1: Introduction AlDhA-NY5IA 1776 9.3.3 eHarmony - Video 2: Using Integer Optimization CLaRAzHxJGo 1777 4.2.1 An Introduction to Trees - Video 1: The Supreme Court Cfx7hyAoGL4 1778 1.3.8 Working with Data - Video 4: Loading Data Files Cks6Wn29TLg 1779 5.4.6 R5. Predictive Coding - Video 5: Building Models D32g7Vv3_gA 1780 1.4.7 R1. Understanding Food - Video 6: Summary Tables EGDQfE7MREw 1781 8.4.9 R8. Google AdWords - Video 8: Extensions and the Edge EOWyWHTA_vQ 1782 9.2.9 Sports Scheduling - Video 5: The Edge EQYlOQjzYOA 1783 5.4.5 R5. Predictive Coding - Video 4: Bag of Words GPOUGpF-Sno 1784 6.2.13 An Introduction to Clustering - Video 7: Hierarchical Clustering in R JAmiDL8pBhg 1785 7.4.2 R7. Visualization - Video 1: Introduction JtIa7ofeXIY 1786 7.4.8 R7. Visualization - Video 7: Using Line Charts Instead JvtqThS69bw 1787 4.2.7 An Introduction to Trees - Video 4: CART in R Mge-sj1UVFM 1788 5.3.1 How IBM Built a Jeopardy Champion - Video 1: IBM Watson f-EN4QySwAs 1789 2.2.1 An Introduction to Linear Regression - Video 1: Predicting the Quality of Wine MvERdFp8mvI 1790 1.3.6 Working with Data - Video 3: Vectors and Data Frames NAQhRc3OQAw 1791 6.3.7 Predictive Diagnosis - Video 4: Understanding Cluster Patterns RS4Ol9PzxCM 1792 6.3.1 Predictive Diagnosis - Video 1: Heart Attacks SBWns1XNcuY 1793 1.4.4 R1. Understanding Food - Video 3: Data Analysis WIKsL9tPoAE 1794 6.4.7 R6. Segmenting Images - Video 5: K-Means Clustering aktu4aRQ5X4 1795 5.2.2 An Introduction to Text Analytics - Video 2: Text Analytics dDHsLmwd9No 1796 1.3.14 Working with Data - Video 7: Saving with Script Files dgjhoPD1FA0 1797 9.2.3 Sports Scheduling - Video 2: The Optimization Problem fEXkGiLYDug 1798 5.3.11 How IBM Built a Jeopardy Champion - Video 6: The Results hqiH39PShmA 1799 5.4.2 R5. Predictive Coding - Video 1: The Story of Enron iR1nRg-jm1o 1800 7.4.7 R7. Visualization - Video 6: Scales O7AoQhYEdLA 1801 3.3.1 The Framingham Heart Study - Video 1: Evaluating Risk Factors to Save Lives PLRK4oOkXuI 1802 6.1.1 Welcome to Unit 6 - An Introduction to Clustering R8SQafbqR1w 1803 6.2.7 An Introduction to Clustering - Video 4: Computing Distances RmUVz9jEnzg 1804 2.4.4 R2. Moneyball in the NBA - Video 3: Points Scored Sn-5Dwt_1qw 1805 2.1.1 Welcome to Unit 2 - An Introduction to Linear Regression UA3QA3KE4sw 1806 8.2.1 An Introduction to Linear Optimization - Video 1: Introduction UVeZhQBNvkE 1807 6.3.3 Predictive Diagnosis - Video 2: The Data VKFwl-T7Hs0 1808 3.4.1 Recitation 3 - Election Forecasting: Predicting the Winner Before Any Votes Are Cast X3dLfxatijE 1809 9.4.1 Welcome to Recitation 9 - Operating Room Scheduling: Making Hospitals Run Smoothly X_reyHNRYws 1810 3.3.3 The Framingham Heart Study - Video 2: Risk Factors _EtlZAMQ2gc 1811 7.4.3 R7. Visualization - Video 2: Pie Charts _JGetImYLis 1812 5.4.9 R5. Predictive Coding - Video 8: Predictive Coding Today cYGYTNZTP7M 1813 7.2.1 An Introduction to Visualization - Video 1: The Power of Visualizations fQXFHIsvV-c 1814 5.3.9 How IBM Built a Jeopardy Champion - Video 5: How Watson Works - Steps 3 and 4 kntypWFmyyM 1815 8.4.1 Welcome to Recitation 8 - Google AdWords: Optimizing Online Advertising ktGKsoTGIho 1816 1.4.1 Welcome to Recitation 1 - Understanding Food: Nutritional Education with Data lkrsGRNsoEU 1817 9.4.5 R9. Operating Room Scheduling - Video 4: The Solution n80gFc12u60 1818 3.3.7 The Framingham Heart Study - Video 4: Validating the Model nqqYjtK1zIk 1819 7.2.7 An Introduction to Visualization - Video 4: Basic Scatterplots Using ggplot o5bqy_5T07Y 1820 6.4.1 Welcome to Recitation 6 - Seeing the Big Picture: Segmenting Images to Create Data ykiTs5MipJU 1821 4.2.9 An Introduction to Trees - Video 5: Random Forests 2Yl5IkDMoUU 1822 7.3.13 Visualization for Law and Order - Video 7: The Analytics Edge B0d9FBokqvY 1823 1.4.7 R1. Understanding Food - Video 6: Summary Tables HJGwmvpZOyI 1824 1.4.6 R1. Understanding Food - Video 5: Adding Variables Q-nk311H-Fw 1825 1.4.5 R1. Understanding Food - Video 4: Creating Plots in R iq7cPtJzgZM 1826 3.2.2 Introduction to Logistical Regression - Video 2: Building the Dataset j9sl8e7wLnc 1827 2.3.7 Sports Analytics - Video 4: Using the Model to Make Predictions jXu7NEuZED4 1828 1.4.4 R1. Understanding Food - Video 3: Data Analysis mwL__eKs3fI 1829 2.3.5 Sports Analytics - Video 3: Predicting Runs oAW8AgU0FE4 1830 1.2.4 The Analytics Edge - Video 4: Example 3 - The Framingham Heart Study oTnXMW4mx-c 1831 1.4.3 R1. Understanding Food - Video 2: Working with Data in R pelPpuYUAho 1832 9.3.5 eHarmony - Video 3: Predicting Compatibility Scores qhOVXxNXAug 1833 5.4.4 R5. Predictive Coding - Video 3: Pre-Processing rg0TYEdU0TA 1834 1.4.2 R1. Understanding Food - Video 1: The Importance of Food and Nutrition ruFpq-_wpc0 1835 3.1.1 Welcome to Unit 3: Modeling the Expert - An Introduction to Logistical Regression sJalJ1A9NDg 1836 6.2.15 An Introduction to Clustering - Video 8: The Analytics Edge of Recommendation Systems suHTm7R7kfQ 1837 9.3.1 eHarmony - Video 1: The Goal of eHarmony uxNfDiKmZ5M 1838 1.4.6 R1. Understanding Food - Video 5: Adding Variables vhkBbC9qp1M 1839 7.3.1 Visualization for Law and Order - Video 1: Predictive Policing wQvjFfMvXrk 1840 8.2.6 An Introduction to Linear Optimization - Video 4: Solving the Problem wT3Y2K-fxXw 1841 2.2.3 An Introduction to Linear Regression - Video 2: One-variable Linear Regression ww-S4khiumM 1842 5.4.1 Welcome to Recitation 5 - Predictive Coding: Bringing Text Analytics to the Courtroom xAuh5VptDQ4 1843 2.4.1 R2. Playing Moneyball in the NBA - Welcome to Recitation 2 xPneVSOZERk 1844 4.4.2 R4. Regression Trees - Video 1: Boston Housing Data xYnq8nVcN4g 1845 2.2.15 An Introduction to Linear Regression - Video 8: Comparing the Model to the Experts xglWbWk_swE 1846 5.4.8 R5. Predictive Coding - Video 7: The ROC Curve xxjhXhhcg74 1847 2.2.9 An Introduction to Linear Regression - Video 5: Understanding the Model xyZEB6vkPb8 1848 4.3.17 Healthcare Costs - Video 9: Results Mbz648H3IEw 1849 Rooted in the Personal KO6GiBAK7cY 1850 Key Learning Q2uUFNDuRFk 1851 Sharing with Teachers TZ0tcovkOp8 1852 Inspiration for the Course _62YvNU_yOM 1853 Valuing Teachers from the Diaspora xCpg54xUzLE 1854 Real-World Learning Outcomes aRZax7Y2t7g 1855 Facilitating Meaningful Classroom Discussions vHflY7UBg70 1856 Oral Presentations 3WrHSdaC9-A 1857 2. How much variation in space and in time through the history of Haitian Creole? JDRa0SwOf2k 1858 6. Language, culture, identity and "authenticity" in post-colonial communities Qm6ykShr0Pg 1859 4. Post-colonial discourses of power & identity; the making of socio-economic & cultural hierarchies R5o6Yr-9om8 1860 Ki sa ki enspire kou a (Inspiration for the Course) ZAMQEaG1WLk 1861 Entèvyou ak pwofesè a: Fasilite brase lide ki djanm nan sal klas (Facilitating Discussions) eduHyoNHi4s 1862 Prezantasyon oral etidyan yo: Konekte analiz abstrè ak esperyans ke yo viv (Oral Presentations) g0KqIIEjXiM 1863 7. Feedback to students who led class discussion m6PnN-aEYbc 1864 9. Against Creole Exceptionalism, Part 2: Creole formation is normal language change mAhtll45Yz8 1865 1. Do "Pidgins" exist? Do Creole languages come from Pidgins? p8BXCDrYliY 1866 8. Against Creole Exceptionalism, Part 1: Creole languages are perfectly normal languages v0c2_iigwwM 1867 Chache konprann ki moun nou ye: Kesyon etidyan yo sou idantite (Rooted in the Personal) z6kTOFSZZmQ 1868 Meet the Educator z_YXJLMpxoM 1869 10. Against Creole Exceptionalism (3): Creole formation is language acquisition plus social factors 1Ukb9KNTNkA 1870 A Different Way to View the World 8fAGSwTwzxI 1871 5. Language & discourses of power in the making of "authentic" identities in post-colonial soc... MT3LjjdODHA 1872 12. A brief & partial history of anti-Creole myths at the core of imperialism—linguistic & oth... NawhRQ7tZU4 1873 Korije vye lide sou lang kreyòl e sou fòmasyon idantite (Unpacking Misconceptions) OKAsxiE8ziY 1874 11. "Birth certificates" of languages created via migration & population contact—Kreyòl, E... SRp9W3T_sHQ 1875 Unpacking Misconceptions T8IjB94ka2g 1876 3. On "Kreyolofoni": Why do we still use the label "Creole" to refer to "Creole languages"? WikAwM9Uyas 1877 Pataje ak anseyan pou ankouraje chanjman sosyal tou patou (Sharing with Teachers) fh1bvrJN4Fc 1878 Using Student Surveys qGr5sdlobCQ 1879 Brase lide ak edikatè a (Meet the Educator) w-zdunIsHUU 1880 Advice for Educators: Help Students Read the Word and the World w4h7ZZd-cI0 1881 Sèvi ak sondaj pami etidyan yo pou n byen kadre ansèyman an selon pwofil etidyan yo (Surveys) wuews7bQrAg 1882 Enpak aprantisaj la nan lavi tou lè jou etidyan yo (Real-World Learning Outcomes) 0sKPkJME2Jw 1883 Lecture: Mathematics of Big Data and Machine Learning N-VHewPgPP8 1884 Providing Science Communication Practice c5zGa2Yt7mw 1885 Developing Students' Science Communication Skills hZ3bVZPUVAU 1886 Building Up to an Audience kHPWYeJ1ISI 1887 Student Challenge #2: Encountering a Multidimensional Learning Surface oyRIkmEU-J0 1888 Pedagogical Iteration uyZkD_6fd9c 1889 J-Lab: A Space to Figure Things Out xvv_edVc-ME 1890 On Grading Student Papers ylH5uD3mGDo 1891 The Role of Iteration in Developing Oral Communication Skills 7AEqqdUtopA 1892 Advice for Women in Physics: Be Confident A77qVe-U0iw 1893 Building Up to an Audience B6mK4IyRYiA 1894 Student Challenge #1: Unlearning How to do Experiments N1PimixqqXQ 1895 Developing New Experiments: Behind the Scenes OIF-J1-Afs8 1896 Flipping the Classroom OWoeymcWpPw 1897 Meet the Educator SDTtTSHr_yE 1898 Tips for Educators YcuKaphreT0 1899 An Invitation to New Students g8BXCaXo6fg 1900 Unique Aspects of the Course gcs7PQaQeS4 1901 Time Management Tip: Don’t Procrastinate! lSUET2RmOh4 1902 Using the Concept of Metadiscourse to Improve Students’ Oral Presentations lpclkNdPQP0 1903 Tips for Partnering with Technical Faculty pGqJkKxpBl0 1904 Supporting Students with Individual Conferences rub-xoQzlwQ 1905 Meet the Educator w_Ufl9paaBc 1906 Take this Course, Even if You Want to be a Theoretical Physicist zHcHGFvd7Vw 1907 Teaching as Coaching -XivhU1V6KY 1908 Improving Early Physics Education NwbPgoCW5Ro 1909 Flipping the Classroom WUTak0K4F-Q 1910 Providing Productive Feedback XLuIf68TJBI 1911 Tips for Educators vcnmiPAeNFE 1912 Meet the Educator xYi0bz-QgEw 1913 The Role of Teamwork in "Junior Lab" 3DizXXZ5qN8 1914 Positioning Communication Instructors as Coaches, Not Graders 6yXA-M8WAY8 1915 Faster than the Speed of Light: A Future Junior Lab Experiment 79noW-0WuAI 1916 Eliciting Cognitive Dissonance 7Wplllt_7xE 1917 Teaching as Coaching GA5UVgowUKc 1918 Tips for Educators cP0IeaqnAjU 1919 Keys to Success in the Course: Perseverance and Data Analysis -JtATRj2EG4 1920 Assessing Learning through Student Talks 4Y9OO9AepgU 1921 Student Challenge #3: Learning Data Analysis 4sgPXcoN59w 1922 Meet the Educator 7S5c25yYjTM 1923 Tips for Partnering with Technical Faculty 8eOshgFmmgA 1924 Advice for Students: Be Persistent BH64jOFmxuw 1925 Advice about Teamwork: Take Time to Verify Your Partner’s Work ECmy2HP1gwA 1926 J-Lab Offers a Wide Range of Experiments RzbWSnb3kHs 1927 An Active Learning Example _yornlzBHL4 1928 Helping Students Cultivate Identities as Scientists bHTpiafiYsY 1929 On the Flipped Classroom Format fSxEbNrIj2M 1930 Science is Communication fuHgW6Z4nW0 1931 How Students Develop as Physicists over the Course of the Semester qTFV2g-4YxQ 1932 Multiple Perspectives on Teaching and Learning d7_bZxCErjo 1933 Experimental Physics I: Final Presentation: Galactic rotation curve and structure of the Milky Way. -GXIkn_ecKY 1934 Experimental Physics I: Final Presentation: Optical Trapping. Measuring the Boltzmann Constant. 57uqU8G_z0E 1935 Experimental Physics I: Final Presentation: Rutherford Scattering Detection through Gold Foil DdPNsGRIw6o 1936 Advanced 3. Image Classification via Deep Learning I2uSCTUHsUI 1937 Advanced 7: Probabilistic and Infinite Horizon Planning Tmhe33f9mWA 1938 Advanced 6. Planning with Temporal Logic 0wxS1iBHG9U 1939 Advanced 2. Semantic Localization qgL0cA7GkJo 1940 Advanced 5. Reachability xmImNoDc9Z4 1941 Advanced 4. Monte Carlo Tree Search _4u9W1xOuts 1942 Advanced 1. Incremental Path Planning r2_-2KW76ec 1943 How We Teach: Infusing Active Learning into 6.033 Recitations 2uDvRUowBzg 1944 Linear Transformations 55AoWKZZtww 1945 Properties of Determinants D8u1LV9CnCk 1946 Computing the Four Fundamental Subspaces QQpvGlF_1Qo 1947 Subspaces of Three Dimensional Space S8DQZjE4V8U 1948 Vector Subspaces VYS9EYZ3gCo 1949 Complex Matrices h0m2tsmSPTI 1950 Graphs and Networks 4PnArrxCZLE 1951 Final Exam Problem Solving My5w4MXWBew 1952 Geometry of Linear Algebra cfn2ZUuWPd0 1953 Positive Definite Matrices and Minima fjsPjh0B2tU 1954 Solving Ax=b lpnY5QVjU5w 1955 Symmetric Matrices and Positive Definiteness pz3zyUO2gpM 1956 Exam #2 Problem Solving 3cMyj8EKFGo 1957 Solving Ax=0 5IGTFgPqlkw 1958 Powers of a Matrix fiSp3Ss-Yo8 1959 微分方程指数矩阵 (At) -eA2D_rIcNA 1960 LU Decomposition AMLekTJR5_U 1961 Exam #1 Problem Solving AmQcoopBUTk 1962 Least Squares Approximation B17h10EF59g 1963 Determinants HEQuN0QELSQ 1964 Gram-Schmidt Orthogonalization KUuxdk_V7To 1965 Similar Matrices MMWqGD4Urso 1966 Basis and Dimension OsHY7ycgbaE 1967 Exam #3 Problem Solving ThxvK9t7DNo 1968 第二次考试例题求解 VyPIQ_8QqEk 1969 三维空间的子空间 ZuWAwCEMeWE 1970 行列式和体积 ZyYGJc9jNno 1971 行列式 h9aDgvW59TU 1972 Orthogonal Vectors and Subspaces hSRcHTafkjE 1973 Pseudoinverses mVeuZzJdd1w 1974 Eigenvalues and Eigenvectors mgbjhzDndOY 1975 线性代数的几何表示 pSbafxDHdgE 1976 Computing the Singular Value Decomposition qEBi0K5wfOs 1977 Determinants and Volume rMv2rDiOTsI 1978 Change of Basis t-n4a18AW08 1979 Projection into Subspaces wuyAeWE3iIM 1980 Markov Matrices BaBoztM9Q1w 1981 Matrix Spaces FzncDO1eSNI 1982 Differential Equations and exp (At) GLFg2UBMAxc 1983 Elimination with Matrices OZxzHcW663g 1984 An Overview of Key Ideas zWxhmBCdvFs 1985 Inverse Matrices zOmTVlqqdEU 1986 Getting Started: Introducing Introductions (Design, Expression w Arduino Microcontrollers) yqE5O1ef1wY 1987 25. Neoliberalism and the End of History - Part 1: Introduction -SUNntP3dWo 1988 An Interdisciplinary Approach CvT9dMwuHhQ 1989 Framing Cultural Phenomena as Technologies RMONbz_0-Rk 1990 Political Context for the Course apWRSZbJCyM 1991 26. Part 1: Student Presentation 'Language, Resistance and Liberation' axW7DSLHO8U 1992 Unlocking Knowledge o4xIlEt71Pw 1993 Advancing Social Justice -Cve_SI6LQs 1994 25. Neoliberalism and the End of History - Part 7: Human Rights and Voting Rights 3XF8HRxS-5g 1995 25. Neoliberalism and the End of History - Part 2: Immigration 5iD590uppi8 1996 Teaching a Wider Audience HF4hKftgWxg 1997 Leveraging the Humanities to Break Walls and Build Bridges TFLHRW3ldOA 1998 Course Materials that Develop Understanding UmbsTnQ39a4 1999 25. Neoliberalism and the End of History - Part 4: Polarized Politics WGgH9wpDs5c 2000 Critical Computational Empowerment WdQUiCPvcvw 2001 Anchoring the Course with #StayWoke aSk7YbhON_0 2002 25. Neoliberalism and the End of History - Part 8: What Can We Do? avJ65YYAfD4 2003 Important Language Issues Today f9YGQZVxJ9I 2004 26. Part 2: Student Perspectives on the Course oEUo2faDJNA 2005 25. Neoliberalism and the End of History - Part 6: Populism & Big Data, Facebook Dark Posts oIp0_rAEMIs 2006 25. Neoliberalism and the End of History - Part 3: Enlightenment, Neoliberalism and Racism pP7mt_Ie04Y 2007 25. Neoliberalism and the End of History - Part 5: Neoliberalism to Populism sY-Hxq1-_Xo 2008 Building on the Personal 14UlXIZzwE4 2009 Puzzle 1: You Will All Conform 1_0WwiUUsTc 2010 Puzzle 5: Keep Those Queens Apart 9TtLlVBjvR0 2011 Puzzle 9: The Disorganized Handyman Fp7usgx_CvM 2012 Puzzle 4: Please Do Break the Crystal Pe1MBDbGfwc 2013 Puzzle 6: A Profusion of Queens eSRNeIyX5dY 2014 Puzzle 7: Tile that Courtyard, Please zDHhHPZm2rc 2015 Puzzle 3: You Can Read Minds (with a little calibration) 6FYk-3vt4FE 2016 Puzzle 11: Memory Serves You Well a1RaIqkdG0c 2017 Puzzle 2: The Best Time to Party auK3PSZoidc 2018 Puzzle 8: You Won't Want to Play Sudoku Again zgk93CwMVk8 2019 Puzzle 10: A Weekend To Remember j4b9U9m9MQA 2020 Session 1.1: Climate Science Meets Community Science 9UDkcGjF4jU 2021 Session 3: Methane Leak Field Trip "Safari" 8C2M48Bc5Fw 2022 Session 4.3: Debrief on Methane Leak Safari GRc5GKMNuho 2023 Session 4.2: Fixing the Carbon Footprint _uq3aNIM-IU 2024 Session 2.1: More About Methane Leaks jBoDIObtJQw 2025 Session 4.1: Environmental Legal Action, Scientific Evidence and Citizen Data lsf0_6DAFOM 2026 Session 1.2: Stories from the Field: Methane Leaks wbAC6IQtgAU 2027 Session 2.2: Methane Leak Measurement Hackathon 1uW3qMFA9Ho 2028 L01.1 Lecture Overview -T34yGp4T7A 2029 L13.5 Forecast Revisions 0xuRh3dz_Nc 2030 S01.10 Bonferroni's Inequality BW_EHmZf2pM 2031 L26.8 Mean First Passage Time JYI5xKlH_MU 2032 L21.3 Stochastic Processes -630YTQEuCI 2033 S01.0 Mathematical Background Overview -k8WU-KB0rk 2034 L04.2 The Counting Principle 17Z89x_ZWQ4 2035 L07.1 Lecture Overview 1R4IzkWSNgI 2036 L16.3 LMS Estimation of One Random Variable Based on Another 27d9Gew3llM 2037 L10.10 Detection of a Binary Signal 3vMZtGUdTVw 2038 S23.2 Poisson Arrivals During an Exponential Interval 5A_H1eHbOCY 2039 L04.9 Multinomial Probabilities 5CHUuMZZzSY 2040 L09.3 Conditioning Example 7B3cDe39lwY 2041 L03.5 Conditional Independence 8Zq9TKaCV-A 2042 L20.8 Other Natural Estimators 99yuPxvdfP8 2043 L25.7 Steady-State Probabilities and Convergence 9QJt03983Gg 2044 S01.7 About the Order of Summation in Series with Multiple Indices AsSQdpZdP8U 2045 L01.7 A Discrete Example B5y6fy5iUtg 2046 L02.1 Lecture Overview Bj3sA7vGpYo 2047 L19.4 Illustration of the CLT FOFtMqCxZt0 2048 L08.6 Exponential Random Variables G11r4Srh4u8 2049 L09.1 Lecture Overview GDJFLfmyb20 2050 S18.2 Jensen's Inequality Hmm9IqosCv4 2051 L19.1 Lecture Overview IrKUM3nNXJE 2052 L19.2 The Central Limit Theorem JoQDJMZA7F8 2053 L05.5 Uniform Random Variables KPF8owESMdo 2054 L17.5 LLMS Example f_BHF-OYwr4 2055 L17.9 The Representation of the Data Matters in LLMS uGGTX2ypzKI 2056 L01.10 Interpretations & Uses of Probabilities LBiYeL4qD2M 2057 L24.1 Lecture Overview LJuVb-sxzoo 2058 L22.6 A Simple Example Lgacew5BjDI 2059 S01.4 When Does a Sequence Converge MPRKc4UPoJk 2060 L02.2 Conditional Probabilities MWcO8ZTOQQQ 2061 S18.3 Hoeffding's Inequality N61FzRr2so0 2062 L25.1 Brief Introduction (RES.6-012 Introduction to Probability) Ne2lmAZI4-I 2063 L26.9 Gambler's Ruin SgM16HNeC3o 2064 L13.11 Variance of the Sum of a Random Number of Random Variables TbRh71BMJvw 2065 L06.8 Linearity of Expectations & The Mean of the Binomial WTyLg_I1oFY 2066 L01.5 Simple Properties of Probabilities XsowwurOvH0 2067 L26.4 A Numerical Example - Part III ZgCBmERwZlI 2068 L20.9 Maximum Likelihood Estimation aXFbBcabaQA 2069 L10.6 Stick-Breaking Example cCmWW7Hu43A 2070 S01.6 The Geometric Series cph71QcwHeQ 2071 L25.3 Markov Chain Review h2w1tTTltrU 2072 L24.7 Generic Convergence Questions iBqEF1cB7nE 2073 L18.8 Related Topics iQ2edOqEQAs 2074 L01.2 Sample Space ipSdsosGJBs 2075 L17.7 LLMS with Multiple Observations kz2tvO_ZAKI 2076 L02.8 Bayes' Rule mImHCY0A3a0 2077 L20.6 Confidence Intervals for the Estimation of the Mean mKcWk_DmS7M 2078 L10.3 Comments on Conditional PDFs mUxg3j_h5GM 2079 L01.9 Countable Additivity pA83XtLeVig 2080 L01.4 Probability Axioms rZKUmNvCjis 2081 L03.2 A Coin Tossing Example sD0i6bWxmRY 2082 L18.1 Lecture Overview uL31gpFdarc 2083 L02.5 A Radar Example and Three Basic Tools vEsUsaK1HBk 2084 L26.6 Absorption Probabilities -0pzpXHq_io 2085 L13.8 A Simple Example 0IJFBMIU6x4 2086 L05.11 Linearity of Expectations 0cD-tcITuck 2087 L10.4 Total Probability & Total Expectation Theorems 0w_4QcvBYII 2088 L14.4 The Bayesian Inference Framework 11iF2ovjKOg 2089 L11.3 A Linear Function of a Continuous Random Variable 2BttG14vI7c 2090 S13.1 Conditional Expectation Properties 2f9EfEga4Oo 2091 L04.6 A Coin Tossing Example 3kxnPEDecIA 2092 L09.4 Memorylessness of the Exponential PDF 4CkWjk40TBY 2093 L17.6 LLMS for Inferring the Parameter of a Coin 4QeL1ma_XJ0 2094 L08.7 Cumulative Distribution Functions 5kdv3r-YgK0 2095 L21.6 Example: The Distribution of a Busy Period 7wqaa4uqwao 2096 L23.1 Lecture Overview 8QyQSZQ4uKQ 2097 L25.4 The Probability of a Path 8llkkbCPHb4 2098 L04.5 Binomial Probabilities AH5jnR3RxJU 2099 S18.1 Convergence in Probability of the Sum of Two Random Variables wOmfOJyxZ6M 2100 L08.4 Means & Variances xi_iT9Rh434 2101 L21.5 The Fresh Start Property yqdcK6-9kv8 2102 L17.4 Remarks on the LLMS Solution and on the Error Variance yvHu34mEXzk 2103 S11.1 Simulation z1lAn4GMaFs 2104 L14.2 Overview of Some Application Domains 2_KBeHiUDiY 2105 L06.4 Conditional PMFs & Expectations Given an Event 363JQxFwLXg 2106 L10.9 Mixed Bayes Rule 47W1ApSRUqs 2107 S01.1 Sets 6UMv4vb4y7c 2108 L08.8 Normal Random Variables 7_livg-uaVs 2109 L06.3 The Variance of the Bernoulli & The Uniform 8QFpZ3FndBc 2110 L08.2 Probability Density Functions yDkm9AYaczk 2111 L13.3 The Law of Iterated Expectations zM39sZL9oGE 2112 L11.7 The Intuition for the Monotonic Case zbu8KQx9bqM 2113 L12.2 The Sum of Independent Discrete Random Variables BjjkSM1Dasg 2114 L13.9 Section Means and Variances BlO3xyeaZME 2115 L16.8 Properties of the LMS Estimation Error CdrVM6MGnGo 2116 L16.4 LMS Performance Evaluation CipR1Jypkz0 2117 L15.5 The Mean Squared Error Cw2Lz5I3wk0 2118 L19.3 Discussion of the CLT GH7dwoXSD0s 2119 L12.7 The Variance of the Sum of Random Variables GkD5tIgc-Bo 2120 L23.9 Different Sampling Methods can Give Different Results JsEvwRGa1JA 2121 L07.5 Example KSrPJe7y9oA 2122 S09.1 Buffon's Needle & Monte Carlo Simulation AVVbUKstn8A 2123 L09.10 Joint CDFs ArfHGPHL8kU 2124 L05.1 Lecture Overview AyCLokHV774 2125 L21.8 Merging of Bernoulli Processes DrBIORgOzSA 2126 L08.9 Calculation of Normal Probabilities F6H50Hbulbk 2127 L07.4 Independence of Random Variables FMrYw7sgyxQ 2128 L15.1 Lecture Overview FT0ptFu6dVA 2129 L15.4 The Case of Multiple Observations GARQ31BrKQA 2130 L05.9 Elementary Properties of Expectation GOmLwHaa8Ik 2131 S07.3 Independence of Random Variables Versus Independence of Events GnEyIawrWBg 2132 L06.5 Total Expectation Theorem GwOklYjwHDI 2133 L21.4 Review of Known Properties of the Bernoulli Process HDvYPl8D8Bs 2134 L21.1 Lecture Overview HTs6Zhc2S1M 2135 L12.8 The Correlation Coefficient IC-pnm6PEGk 2136 L04.8 Each Person Gets An Ace J3aMHIajtFc 2137 L12.10 Interpreting the Correlation Coefficient J8L9kRGSvSY 2138 L05.4 Bernoulli & Indicator Random Variables JCQnsPggTp8 2139 L10.5 Independence JZkT3NU2mPM 2140 L03.4 Independence of Event Complements K-ck5dOsPgQ 2141 L24.2 Introduction to Markov Processes K2Tlj27nkjs 2142 L12.5 Covariance KdAsNQVdaNk 2143 L25.11 Birth-Death Processes - Part II Kj6iEzXsFkI 2144 L10.2 Conditional PDFs KrjZyCRi29o 2145 L04.3 Die Roll Example Kycmb2IwV-Y 2146 L07.8 The Hat Problem L_pEeYLGaP0 2147 L02.4 Conditional Probabilities Obey the Same Axioms MuqLI4otMIQ 2148 L06.6 Geometric PMF Memorylessness & Expectation Mv8tuMBQk-g 2149 L09.5 Total Probability & Expectation Theorems NRnAuKxx6XA 2150 L11.2 The PMF of a Function of a Discrete Random Variable NbYB0fiHoCs 2151 L01.8 A Continuous Example P5rZKt3SgNM 2152 L20.1 Lecture Overview PJExYLw0qtc 2153 L22.3 Applications of the Poisson Process QXKgTPR_8wk 2154 L03.1 Lecture Overview RgGFvOpcQXY 2155 L15.2 Recognizing Normal PDFs TAyA-rjmesQ 2156 L03.6 Independence Versus Conditional Independence T_Q3M_HV94w 2157 L07.2 Conditional PMFs UcKhhEc_LyQ 2158 L25.5 Recurrent and Transient States: Review MlsVWPWIxHI 2159 L16.1 Lecture Overview MvGuBQZZuLM 2160 L22.10 An Example N3I2ZLbh6zQ 2161 L01.6 More Properties of Probabilities NInNhFm046w 2162 L20.5 Confidence Intervals O-dyKz5dpeY 2163 L16.5 Example: The LMS Estimate O4QYcoxuLHE 2164 L09.7 Joint PDFs OlKmZj2TKnk 2165 L14.6 Discrete Parameter, Continuous Observation PaI-oaOBHKU 2166 L11.6 The Monotonic Case R4nGGs0m7lo 2167 L07.6 Independence & Expectations RQKJBpaCCeo 2168 L12.6 Covariance Properties RVc5hXzVFc4 2169 L22.1 Lecture Overview TWedESDFcLQ 2170 L25.6 Periodic States UDkq_cLVSmc 2171 L03.9 Reliability UbQcqFH33G0 2172 L03.7 Independence of a Collection of Events UwwqPwp16_0 2173 L24.5 N-Step Transition Probabilities WSrVCCBOeg4 2174 L10.8 Bayes Rule Variations XKYpKYspe1w 2175 L25.10 Birth-Death Processes - Part I Xa6-qJvZkUg 2176 L26.1 Brief Introduction (RES.6-012 Introduction to Probability) Xwd4ABlO0Dc 2177 S05.1 Supplement: Functions YQ26hzI4OJk 2178 L07.7 Independence, Variances & the Binomial Variance _hDfZF64wic 2179 L14.10 Summary _l9y2Kv8VHw 2180 L18.7 Convergence in Probability Examples aNLEnFtWwhg 2181 L14.1 Lecture Overview aYg2je06Cpg 2182 L14.5 Discrete Parameter, Discrete Observation d5mV88S2fNY 2183 L11.1 Lecture Overview VJhDWandNwc 2184 L09.6 Mixed Random Variables WFMTus20mz4 2185 L09.9 Continuous Analogs of Various Properties X-AzW70e2M0 2186 L11.5 The PDF of a General Function X04gTpC7wAs 2187 L13.6 The Conditional Variance XWKXOUvqC-U 2188 L23.3 Merging Independent Poisson Processes YIZd23zGV3M 2189 S01.9 Proof That a Set of Real Numbers is Uncountable YenDB3yOfDc 2190 L02.3 A Die Roll Example Yh5bR7X3ch8 2191 L18.4 The Weak Law of Large Numbers ZWo1XgAQE5k 2192 L06.2 Variance _HL7qwWvON4 2193 L17.2 LLMS Formulation _IX_9ajyOxI 2194 L23.2 The Sum of Independent Poisson Random Variables _yJsO5955ZE 2195 L05.8 Expectation aGbP_7yAiEk 2196 L12.4 The Sum of Independent Normal Random Variables aJXfyfQs2Mc 2197 L03.8 Independence Versus Pairwise Independence aS1o7uTaLF0 2198 L23.8 Random Incidence in a Non-Poisson Process bXmDp8R8n8U 2199 L08.5 Mean & Variance of the Uniform byGWKoOc6EM 2200 L17.8 The Simplest LLMS Example with Multiple Observations cQtCpJyl77o 2201 L25.8 A Numerical Example - Part II d2M4LNSeIn4 2202 L12.3 The Sum of Independent Continuous Random Variables d5pnfFvggYk 2203 L18.3 The Chebyshev Inequality fBfMIVXc_OM 2204 L19.6 Normal Approximation to the Binomial gH_OmTJ9vQs 2205 L16.2 LMS Estimation in the Absence of Observations h8DKVKfWU_Q 2206 L09.8 From The Joint to the Marginal iUF135CGTeI 2207 L26.7 Expected Time to Absorption jPB9zI8F7rE 2208 L08.3 Uniform & Piecewise Constant PDFs jzhFxJflHXQ 2209 L16.7 LMS Estimation with Multiple Observations or Unknowns lET4uQLpmM0 2210 L20.4 On the Mean Squared Error of an Estimator lmHjUxi2EH4 2211 L21.2 The Bernoulli Process m-enGdJ-j8s 2212 L21.7 The Time of the K-th Arrival n9FTM9f9A6I 2213 L06.1 Lecture Overview nYe4OZVCnIs 2214 S01.5 Infinite Series nuXDb9B3y0M 2215 L20.3 The Sample Mean and Some Terminology eV0kTm1h7mQ 2216 L23.6 Splitting a Poisson Process eXf2Zak-s0o 2217 L08.1 Lecture Overview fZ0bbrbNq58 2218 L21.10 The Poisson Approximation to the Binomial gB5TCCfF6e4 2219 L05.10 The Expected Value Rule gJSPef9zC0c 2220 L14.9 Inferring the Unknown Bias of a Coin - Point Estimates iPWyElxtk-8 2221 L03.10 The King's Sibling jOC4ATKBWlI 2222 L05.6 Binomial Random Variables k9f0N3ADvdM 2223 L17.3 Solution to the LLMS Problem kuhlfBPQPq0 2224 S01.3 Sequences and their Limits kwbDWPrPfQI 2225 L17.1 Lecture Overview l6YYHaV1aGc 2226 L24.6 A Numerical Example - Part I mHj4A1gh_ws 2227 L09.2 Conditioning A Continuous Random Variable on an Event mHonq7Gjjqg 2228 L13.7 Derivation of the Law of Total Variance mxpC3MEiATQ 2229 L19.7 Polling Revisited nQukfQgIIqw 2230 L10.1 Lecture Overview o_qO7RYBF10 2231 L04.4 Combinations ozbtgvLKAqE 2232 L21.9 Splitting a Bernoulli Process pd7dvQBqQqY 2233 L19.5 CLT Examples rRwWYRh8Ypg 2234 L26.3 Review of Steady-State Behavior sSWHT2kbkvc 2235 S07.2 The Variance of the Geometric tzW5jlfEvwU 2236 L22.4 The Poisson PMF for the Number of Arrivals zW1_iugJvF0 2237 L05.3 Probability Mass Functions 2JoRO8Cydtc 2238 L22.5 The Mean and Variance of the Number of Arrivals 6stYmO_N7LI 2239 L22.7 Time of the K-th Arrival 8odFouBR2wE 2240 L02.7 Total Probability Theorem Ajar_6MAOLw 2241 L18.6 Convergence in Probability poeHeiiiLKI 2242 L04.1 Lecture Overview qOQxeYGOIag 2243 L10.7 Independent Normals qgICsL7ybWc 2244 L15.3 Estimating a Normal Random Variable in the Presence of Additive Noise qinepPxDUcY 2245 L15.7 Linear Normal Models rFUb1nvh3CQ 2246 L15.6 Multiple Parameters; Trajectory Estimation r_rzDNLODQw 2247 L22.8 The Fresh Start Property and Its Implications tpaE_C8rqf8 2248 L16.6 Example Continued: LMS Performance Evaluation uQTFiXQR4PQ 2249 L18.5 Polling ugzs7dgQ-JE 2250 L02.6 The Multiplication Rule uviHu6m_YnM 2251 L25.2 Lecture Overview uxVRfj60z98 2252 L12.9 Proof of Key Properties of the Correlation Coefficient v5fOm80VAnc 2253 L14.3 Types of Inference Problems vfqPpai_9jI 2254 L05.2 Definition of Random Variables vjYanZ1nsZg 2255 L18.2 The Markov Inequality w423ypsUHf0 2256 L03.3 Independence of Two Events wBnlmQR5Vhk 2257 L12.1 Lecture Overview wTKRruMNOHw 2258 L15.8 Trajectory Estimation Illustration whbKmwMmB4s 2259 L05.7 Geometric Random Variables wnts35dE1Sg 2260 L10.11 Inference of the Bias of a Coin xDN5Onmu0mk 2261 L23.5 The Time Until the First (or last) Lightbulb Burns Out xdewLsXI_UQ 2262 L13.10 Mean of the Sum of a Random Number of Random Variables zc6PfijY8_s 2263 L13.1 Lecture Overview LVfIS8pBI6Y 2264 L13.4 Stick-Breaking Revisited UZOT_ddWpco 2265 L26.2 Lecture Overview VCyJGp6Enxg 2266 L24.3 Checkout Counter Example fMHJPEcoC08 2267 L20.2 Overview of the Classical Statistical Framework pdR9hV8mRWE 2268 S01.2 De Morgan's Laws uFx7fWujWsU 2269 L11.8 A Nonmonotonic Example vJAG4EzSQZA 2270 L07.3 Conditional Expectation & the Total Expectation Theorem wSQaYn2h-e8 2271 L24.8 Recurrent and Transient States 00krscK7iBA 2272 L20.10 Maximum Likelihood Estimation Examples 46Ym07yKf4A 2273 L14.8 Inferring the Unknown Bias of a Coin and the Beta Distribution 6-gN0dDHU-4 2274 L12.11 Correlations Matter 7nu97OYx4X4 2275 L06.7 Joint PMFs and the Expected Value Rule 85le_VkEK5A 2276 L26.5 Design of a Phone System 8yaRt24qA1M 2277 S14.1 The Beta Formula CN_TJBPv2Qs 2278 L14.7 Continuous Parameter, Continuous Observation D_EGYzqmapc 2279 L22.2 Definition of the Poisson Process MqocbJ-FPo0 2280 S01.8 Countable and Uncountable Sets MzvRQFYUEFU 2281 L20.7 Confidence Intervals for the Mean, When the Variance is Unknown WXIU2tK4qtc 2282 S07.1 The Inclusion-Exclusion Formula X-krLprDrOI 2283 L11.9 The PDF of a Function of Multiple Random Variables __T3eJtjoic 2284 L01.3 Sample Space Examples c-BLp-585aU 2285 L25.9 Visit Frequency Interpretation of Steady-State Probabilities eFDU7t6Jxzc 2286 L11.4 A Linear Function of a Normal Random Variable hJjiCrdsNV8 2287 L04.7 Partitions hsQnmrHbbms 2288 L24.4 Discrete-Time Finite-State Markov Chains jXf5Sz7V87I 2289 L22.9 Summary of Results mgAhDIdbUK8 2290 L23.4 Where is an Arrival of the Merged Process Coming From? sG3_Bveu_cA 2291 L23.7 Random Incidence in the Poisson Process strrrdJivco 2292 L13.2 Conditional Expectation as a Random Variable t_EcSVTWmwk 2293 S23.1 Poisson Versus Normal Approximations to the Binomial 7Knpp3AIteQ 2294 Using Questionnaires to Customize Course Content 9Dwl2FbEc5E 2295 Using Demonstrations in Class GUgIh6ff86Y 2296 Students' Common Misconceptions fTACO13q2oU 2297 Course Iteration: Incorporating Theoretical Content and Demonstrations gDzWxDqb8Xg 2298 Combining Chalk Talks and Slides in a Complementary Way wwQu2_u8jeo 2299 The Role of Recitations 0oUSmdQ-WaA 2300 Taking a Vote to Engage Learners 8P2AvGGtm_A 2301 Tips for Physics Educators cZAM2Co3tzo 2302 Making Time for Individual Questions in a Large Lecture cektQp7QQhk 2303 Behind-the-Scenes Demo Prep lAuAC4hz5rc 2304 Using Humor to Enhance Learning nOb_iQjTy-Q 2305 8.03SC Physics III: Vibrations and Waves Introduction 1JeBWHzrRD4 2306 9. Wave Equation, Standing Waves, Fourier Series 4ysFC9vd3GE 2307 1. Periodic Oscillations, Harmonic Oscillators Ahv7Akj2xs4 2308 6. Driven Oscillators, Resonance BX4QPdP7fT8 2309 4. Coupled Oscillators, Normal Modes Dlhma3z57SA 2310 18. Wave Plates, Radiation FY6iXM9X5Fo 2311 22. Diffraction, Resolution In0E5_JrPpo 2312 15. Uncertainty Principle, 2D Waves J1uHGy1tRmM 2313 8. Translation Symmetry QxemLb8-5AA 2314 13. Dispersive Medium, Phase Velocity, Group Velocity RhIh1zw0-BM 2315 11. Sound Waves SnNmbVH5DAM 2316 10. Traveling Waves TjxR7lAwWhI 2317 17. Polarization, Polarizer VGAlyJ7e0IQ 2318 14. Fourier Transform, AM Radio VkbtIDSHfSc 2319 20. Interference, Soap Bubble _kKIQ1h9UuA 2320 16. 2D and 3D waves, Snell's Law mqhO9GT8hD4 2321 21. Phased Radar, Single Electron Interference sBKHUPDUI1o 2322 19. Waves in Medium 8kcvyoHsXrw 2323 12. Maxwell's Equation, Electromagnetic Waves FCFpaKcpuXQ 2324 3. Driven Oscillators, Transient Phenomena, Resonance I0YACDaY-ww 2325 5. Beat Phenomena Roj7FVjl-gw 2326 23. Quantum Waves and Gravitational Waves T2n6fVybLcU 2327 2. Damped Free Oscillators b1eKhyC9TTo 2328 7. Symmetry, Infinite Number of Coupled Oscillators jwh7LqjT4w0 2329 Exam Review -05tcR4izaw 2330 Seminar 3: Jessica Sommerville - Infants' Sensitivity to Cost and Benefit GXuI9fKDxso 2331 Lecture 3.4: Laura Schulz - Childrens' Sensitivity to Cost and Value of Information eKKXJyabCAQ 2332 Seminar 4.1: Eero Simoncelli: Probing Sensory Representations 3Mvzp5xvEXA 2333 Lecture 1.1: Nancy Kanwisher - Human Cognitive Neuroscience 43kansULeBE 2334 Lecture 4.3. Aude Oliva - Predicting Visual Memory 6iW0beoK2tI 2335 Lecture 3.1: Liz Spelke - Cognition in Infancy (Part 1) 7XvgBI2KV28 2336 Lecture 5.3: Patrick Winston - Story Understanding 8PcPpVQK7N8 2337 Lecture 1.5: Winrich Freiwald - Primates, Faces, & Intelligence A4R2PQOHT2w 2338 Seminar 5: Tom Mitchell - Neural Representations of Language Ch56tU3wb9c 2339 Lecture 1.3: James DiCarlo - Neural Mechanisms of Recognition Part 1 D8zaRaVWy9k 2340 Unit 8 Panel: Robotics GGakcLdPWl4 2341 Unit 3 Debate: Tomer Ullman and Laura Schulz HA4undazeF0 2342 Lecture 6.1: Nancy Kanwisher - Introduction to Social Intelligence HCBaApqRqSg 2343 Lecture 7.1: Josh McDermott - Introduction to Audition, Part 1 IeD8VXfqPyQ 2344 Lecture 9.1: Tomaso Poggio - iTheory: Visual Cortex & Deep Networks NRygklHAoEw 2345 Lecture 5.2: Andrei Barbu - From Language to Vision and Back Again Pwm6DqdC4pU 2346 Lecture 2.1: Josh Tenenbaum - Computational Cognitive Science Part 1 QeHuHti530Q 2347 Lecture 9.2: Haim Sompolinksy - Sensory Representations in Deep Networks RTmoWFZQ-WE 2348 Seminar 1: Larry Abbott - Mind in the Fly Brain S7M9hXsCRFI 2349 Lecture 7.3: Nancy Kanwisher - Human Auditory Cortex TjrRSOHQACw 2350 Seminar 4.2: Anmon Shashua - Applications of Vision Xj4nKgJW5yE 2351 Lecture 4.2: Shimon Ullman - Atoms of Recognition cyQZP23YbCY 2352 Tutorial 3.1: Lorenzo Rosasco - Machine Learning Part 1 fmmRyV9ObkU 2353 Tutorial 3.2: Lorenzo Rosasco - Machine Learning Part 2 ggcbVV3Tquo 2354 Lecture 4.1: Shimon Ullman - Development of Visual Concepts i0-2sd9RQ6E 2355 Lecture 6.3: Rebecca Saxe - MVPA: Window on the Mind via fMRI Part 1 l1t2_5UZhPA 2356 Lecture 3.3: Alia Martin - Developing an Understanding of Communication opMnuRnfaX0 2357 Seminar 9: Surya Ganguli - Statistical Physics of Deep Learning pquNMjlgPwI 2358 Tutorial 3.3: Lorenzo Rosasco - Machine Learning Part 3 vmE4N0m67AA 2359 Lecture 1.6: Matt Wilson - Hippocampus, Memory, & Sleep Part 1 zHa-n2M7Bj8 2360 Lecture 3.5: Josh Tenenbaum - The Child as Scientist 7eUfAb8de8c 2361 Lecture 7.4: Hynek Hermansky - Auditory Perception in Speech Technology, Part 1 AWYzdtetQbE 2362 Lecture 1.4: Neural Mechanisms of Recognition, Part 2 Bn49TBjEAI4 2363 David Rolnick & Ishita Dasgupta: Modeling Dynamic Memory with Hopfield Networks Em9I6XTQA3I 2364 Lecture 7.5: Hynek Hermansky - Auditory Perception in Speech Technology, Part 2 FMb-HSnaNs4 2365 Tutorial 4: Ethan Meyers - Understanding Neural Content via Population Decoding JZcFjR4dMmw 2366 Danny Jeck: Impact of Attention on Cortical Models of Visual Recognition NFFX81o9yRA 2367 Alon Baram & Laurie Bayet: Learning to Recognize Digits and Faces from Few Examples Unvy1L_NH0c 2368 Tutorial 5.2: Tomer Ullman - Church Programming Language Part 2 dfsPKoHv_F4 2369 Lecture 2.3: Josh Tenenbaum - Computational Cognitive Science Part 3 hfryF7_QU2c 2370 Lecture 2.2: Josh Tenenbaum - Computational Cognitive Science Part 2 rUqqquitfMQ 2371 Lecture 8.4: Stefanie Tellex - Human-Robot Collaboration yEbr410E2RE 2372 Lecture 5.1: Vision and Language 1kel8U86EVE 2373 Lecture 8.2: John Leonard - Mapping, Localization and Self Driving Vehicles 3xBTFOxtfNU 2374 Tutorial 1: Leyla Isik - Introduction to Visual Neuroscience 6nfmDpar0fQ 2375 Lecture 3.2: Cognition in Infancy, Part 2 7BAChnLg8Co 2376 Lecture 8.5: Giorgio Metta - Introduction to the iCub Robot EAWpLeor4Zk 2377 Lecture 8.6: iCub Team - Overview of Research on the iCub Robot FRoD9TOJxso 2378 Lecture 8.3: Tony Prescott - Control Architecture in Mammals and Robots FndNHiuFeFU 2379 Lecture 8.1: Russ Tedrake - MIT's Entry in the DARPA Robotics Challenge PlAelAX6gSU 2380 Lecture 7.2: Josh McDermott - Introduction to Audition, Part 2 _qTVDxXBK5A 2381 Nick Cheney: Capturing Neural Plasticity in Deep Networks fmx5Yj95sgQ 2382 Lecture 1.7: Hippocampus, Memory, & Sleep, Part 2 hRAlCx8Xd0Q 2383 Lecture 6.2: Ken Nakayama - The Social Mind hWabPMYZzmo 2384 Lecture 6.4: MVPA: Window on the Mind via fMRI, Part 2 juRiFivEj8s 2385 Unit 7 Panel: Vision and Audition lv3kGg-eRa0 2386 Tutorial 5.1: Tomer Ullman - Church Programming Language Part 1 pCyWp8R4zsA 2387 Tutorial 6: Tomer Ullman - Amazon Mechanical Turk zAx-EEelmLc 2388 Lecture 1.2: Gabriel Kreiman - Computational Roles of Neural Feedback _svW8NV1A6k 2389 Lecture 0: Tomaso Poggio - Introduction to Brains, Minds, and Machines E3JI-qkcTq4 2390 Give 2 Win Be An MIT Student for A Day Sweepstakes -W8jzpw_TgE 2391 Japanese Community Events 6TcIK81Ay3g 2392 学生の語学力を育てる (Developing Students’ Language Skills) M72LGeuJ7q4 2393 文法とドリルセッション (Grammar and Drill Sessions) Qd-zK_1bEPM 2394 Grammar and Drill Sessions _Rug61bsvt8 2395 アセスメントの対策 (Assessment Strategies) a4_x62LdV30 2396 日本のコミュニティイベント (Japanese Community Events) aDAsbWBTlvI 2397 Developing Students' Language Skills dWNrHmcb4Oo 2398 Assessment Strategies nLlx5bE68b0 2399 言語を通しての日本文化の指導 (Teaching Japanese Culture though Language) K12JGiYHcTw 2400 Meet the Educator caSqb6LMF30 2401 Teaching Japanese Culture through Language 15IeTaS5AUI 2402 Blood Sugar Fluctuations and Gluconeogenesis GrrEdi84cV4 2403 When Your Breath Smells Like Nail Polish Remover ePH6sgXk9vw 2404 The Science Behind Type II Diabetes -MVhGXP-6p8 2405 教育者に会う (Meet the Educator) BAoaC8O3X7I 2406 Collaboration: Ideation and Brainstorming kP_1zySn3Rw 2407 Long Project: Awesome Light Show Touch Game S9v_naROYQ8 2408 Short Project: Introduction 0RtBiJ_FTag 2409 Long Project: LED Framed Light Display Part 2 0t659KgehZE 2410 Getting Started: Icebreaker 6xrabmU-gq8 2411 Long Project: Punching Glove 7WAP4DWKarM 2412 Short Project: Plant People WyEwjQt8gfQ 2413 Short Project: Arduino Pinball XKEJRhypx84 2414 Short Project: Back in Black Light Show XmpKWntLzPQ 2415 Short Project: Calculator fppdTndwipg 2416 Long Project: Introduction iNQ0dQ9bPNs 2417 Long Project: Quadcopter kk55qwgSXcA 2418 Short Project: Infrared Lock psoIl5k1FIs 2419 Short Project: Chance Game sNE3_UXhV20 2420 Collaboration: Red Ball During Class ttuvXdZNcDM 2421 Long Project: LED Framed Light Display Part 1 4pPggNBGK88 2422 Long Project: Hand Motion Controlled Car _3lU2LDQdUU 2423 Collaboration: Introduction to Git/Github uPoKChMBeQY 2424 Short Project: Knock Knock Lock VPZD_aij8H0 2425 1. Introduction to Statistics 4DmYVsqRbPg 2426 Short Project: Introduction 5wbD-zChZsU 2427 Short Project: Antisocial 7a4NYOOSVfI 2428 Short Project: Downhill Skiing GUgYT7GxUGA 2429 Long Project: Cats Cradle H6y0szqtRKo 2430 Getting Started: Icebreaker Ksl0Vp4jhmA 2431 Long Project: Cube Constructor R8WOnNX8v9E 2432 Expanding on Tutorials: Humans Matter and Class Details ZLbt_1bI_NA 2433 Getting Started: Q&A _ZVnrpjI_VU 2434 Collaboration: Introduction to Git/Github a4snWHyNTJ4 2435 Guided Tutorial: Purpose and Overview apbCAHH7Ml4 2436 Long Project: Multiple Mini-games gDpkinitSRM 2437 Long Project: Desert Racing h9btrlN9JLk 2438 Collaboration: Red Ball during Class jXtqyQuLlnk 2439 Short Project: Cube Constructor s7i_Dpz-DLU 2440 Getting Started: Introducing Introductions N4GOV3kzbdo 2441 Long Project: Zoo Escape JJRijRD4l-g 2442 Expanding on Tutorials: Kinect Demo rNfMwqjohC8 2443 Long Project: Blackout Tetris xfbzRPUagPY 2444 Short Project: Goshzilla gBD44yITfrw 2445 Long Project: Introduction zNesxH6wiAg 2446 Collaboration: Ideation and Brainstorming 9NChLq-orAk 2447 Short Project: Bodypaint Zqi2n4oZgvk 2448 Expanding on Tutorials lKX4aGOzNvo 2449 Guided Tutorial: Introduction to Unity EIWhCCjSkPU 2450 Short Project: Car Racing F3N5EkMX_ks 2451 8.01SC Classical Mechanics Introduction p0Brd5vwV_Q 2452 Scenario 1: Federal Environmental Policy-Making 922Oig1HWG8 2453 Lexicon of Biochemical Reactions: Vitamin B6 / PLP VVOazB6_D3Q 2454 Lexicon of Biochemical Reactions: Introduction zdage-Lp8m4 2455 5. Enzymes and Catalysis 56vQ0S2eAjw 2456 Lexicon of Biochemical Reactions: Cofactors Formed from Vitamin B12 ojvz7pVVZ-o 2457 Lexicon of Biochemical Reactions: Redox Cofactors 61ZVXmh6ae0 2458 PLP (Pyridoxal Phosphate) Reactions gbOyppJ9OK4 2459 Carbonyl Chemistry 4BwB43Smu7o 2460 Problem Set 7, Problem 1: Tracing Labels through Pathways BY__sHZYi7Q 2461 Problem Set 1, Problem 1: Sizes and Equilibria Kl2KpdlB8SQ 2462 Problem Set 5, Problem 5: How Mannose, an Isomer of Glucose, Enters Glycolysis XmS9DYHQHi0 2463 Problem Set 4, Problem 2: The Mechanism of HMG-CoA Synthase 6MaMdzo416w 2464 Motivating Students to Study Metabolic Biochemistry with Oncology Applications BZGOYTtQUhY 2465 Pentose Phosphate Pathway 345Wz_7CrN4 2466 Carbohydrate Biosynthesis II: Gluconeogenesis cEoteBfcBE0 2467 Respiration: Electron Transport and Oxidative Phosphorylation jHrd43uWD-E 2468 Lipod Catabolism: Fatty Acid Beta-Oxidation 0XAJIHttCNs 2469 Maintenance of Redox Neutrality LCiH8faydGk 2470 Special Cases in Fatty Acid Metabolism eOYHJLqP2Ps 2471 Respiration: TCA Cycle sBYrp3zssWE 2472 Regulation of Metabolism ziJc5pSF5aM 2473 Problem Set 10, Problem 3: Gluconeogenesis bmnKAp3EZ5o 2474 Problem Set 2, Problem 1: Primary Structure h20EdXcopeY 2475 Respiration: Proton Pumps and ATP Synthesis qmqiF0YJ4LM 2476 Ketogenesis, Diabetes, and Starvation wyT7EFJlBak 2477 Introduction to Carbohydrate Catabolism VykaDbJIb8A 2478 Problem Set 8, Problem 2: Bioenergetics of the Electron Transport Chain f-bMQdul6xI 2479 Carbohydrate Biosynthesis I: Glycogen Synthesis qa8IepmE5Mw 2480 Problem Set 3, Problem 2: Proteases: Mechanisms of Inhibition tFEBiKPv1e8 2481 Glycolysis and Early Stages of Respiration ddt1KuSdoOg 2482 Fatty Acids and Lipid Biosynthesis taCtV7gVKdI 2483 Problem Set 9, Problem 1: Catabolism of Triacylglycerols vL_E7Ik_vBs 2484 Problem Set 6, Problem 2: Mechanism of Phosphoglycerate Mutase 6c1jkgSynrI 2485 Research Focus: Ribonucleotide Reductases (RNRs) BYhaXjwgn5I 2486 Teaching Central Pathways to Help Students Understand Metabolism UrgmDSFBYlE 2487 Using a Vitamin Bottle as a Teaching Tool ZS5vxMILXPg 2488 Becoming a Toxicologist _nct_bjbX6E 2489 Advice for Next Teaching Generation: Focus Curricula on the Microbial World bzwf2tgC23E 2490 How Can You Not Think Enzymes are Cool? w1JYnijqT6A 2491 Research Focus: Genetic Change IKXWnA5Xdqo 2492 Why Students Should Memorize Amino Acid Side Chains cOD4yhZVZMY 2493 Focusing on the Morphological Unit of Life WW3ZJHPwvyg 2494 19. Principal Component Analysis V4xOdtqic3o 2495 15. Regression (cont.) TSkDZbGS94k 2496 3. Parametric Inference JTbZP0yt9qc 2497 6. Maximum Likelihood Estimation (cont.) and the Method of Moments QXkOaifVfW4 2498 9. Parametric Hypothesis Testing (cont.) JBIz7UadY5M 2499 14. Regression (cont.) phbw9r1iUDI 2500 7. Parametric Hypothesis Testing lWW54ts9Ubo 2501 24. Generalized Linear Models (cont.) a66tfLdr6oY 2502 11. Parametric Hypothesis Testing (cont.) and Testing Goodness of Fit vMaKx9fmJHE 2503 12. Testing Goodness of Fit (cont.) C_W1adH-NVE 2504 2. Introduction to Statistics (cont.) X-ix97pw0xY 2505 21. Generalized Linear Models 4HRhg4eUiMo 2506 8. Parametric Hypothesis Testing (cont.) a1ZCeFpeW0o 2507 20. Principal Component Analysis (cont.) bFZ-0FH5hfs 2508 17. Bayesian Statistics k2inA31Gups 2509 18. Bayesian Statistics (cont.) mc1y8m9-hOM 2510 22. Generalized Linear Models (cont.) rLlZpnT02ZU 2511 4. Parametric Inference (cont.) and Maximum Likelihood Estimation 0Va2dOLqUfM 2512 5. Maximum Likelihood Estimation (cont.) yP1S37BiEsQ 2513 13. Regression OYcdw5vOgIc 2514 23. Generalized Linear Models (cont.) txKXRtlrFfI 2515 5. Eigenvalues and Eigenvectors LHBQ5Z4CtwA 2516 19. Differntial Algebraic Equations 3 PKbah48l3AU 2517 12. Constrained Optimization; Equality Constraints and Lagrange Multipliers SejxqXAlSec 2518 11. Unconstrained Optimization; Newton-Raphson and Trust Region Methods DsmkIG4-hrQ 2519 18. Differntial Algebraic Equations 2 KFq33hsMxr4 2520 16. ODE-IVP and Numerical Integration 4 KkN_Dk3E2yw 2521 13. ODE-IVP and Numerical Integration 1 4RSQTqPjOLw 2522 30. Models vs. Data 3 8kPUI5HoVxg 2523 8. Quasi-Newton-Raphson Methods 3rIGt0GdGMY 2524 21. Boundary Value Problems 2 42TkHA__6bk 2525 34. Stochastic Chemical Kinetics 1 UZiEFO3J8mE 2526 22. Partial Differential Equations 1 VMyJ_v3K0Tw 2527 28. Models vs. Data 1 Vu_oF9tcjaA 2528 7. Solutions of Nonlinear Equations; Newton-Raphson Method WVAfgCmFonU 2529 27. Probability Theory 2 We570M74cXE 2530 36. Final Lecture geVT3JYHeqI 2531 35. Stochastic Chemical Kinetics 2 muFAQx5dUdU 2532 9. Homotopy and Bifurcation uOPuBNtv6Fk 2533 33. Monte Carlo Methods 2 w9GJyvkHbNM 2534 6. Singular Value Decomposition; Iterative Solutions of Linear Equations M19mzHT8JM4 2535 26. Partial Differential Equations 2 u72VF_VDp2k 2536 25. Review Session xE9IGS-_6zo 2537 20. Boundary Value Problem 1 ZNTBAKAT_WQ 2538 Scenario 7: Local vs. Expert Knowledge - Student Presentation _HpMRwM6tAQ 2539 Scenario 9: Cost-Benefit Analysis - Class Discussion blQBnH1kYZY 2540 Scenario 11: Ecosystem Services Analysis U_sZrNjbj1I 2541 Scenario 4: Comparative Policy Analysis 0ppkDQuiHkw 2542 Scenario 10: Societal Risk Assessment A76FlzncnbU 2543 Scenario 6: Sustainable Development uml1y_50O_g 2544 Scenario 2: The Policy-Making Process St_PAkSBiYs 2545 Scenario 8: Environmental Impact Assessment klPt8DrL5tc 2546 Scenario 14: Relying on Effective Dispute Resolution gj8RoTm9jxM 2547 Scenario 13: Building an Informed Consensus lkq-QWxaxjw 2548 Scenario 9: Cost-Benefit Analysis - Cold Call oJ7-LI_ex0o 2549 Scenario 12: Public Participation Techniques and Strategies r01KsFLKdO4 2550 Scenario 9: Cost-Benefit Analysis - Student Presentation vQhm-w6l1OY 2551 Scenario 3: Policy Evaluation alnDYYwAs74 2552 Scenario 5: Environmental Ethics & the Precautionary Principle QNchkFi-VrE 2553 Scenario 7: Local Knowledge vs. Expert Knowledge - Cold Call v1pwYnDe7dc 2554 Instructor Interview: Using Visual Materials to Teach 21st Century Skills wWsRfu_1wvw 2555 Instructor Interview: Meet the Educator Ay80m-WFyko 2556 Instructor Interview: A Major Course Goal / Learning to Work in Teams xkoq5N0TTlI 2557 Instructor Interview: MIT OpenCourseWare / A Bold Idea zptyZRDiLsQ 2558 Instructor Interview: Flipping the Classroom "Changing Everything" Fg6W-rcCTlc 2559 Instructor Interview: Collaborating with Guest Lecturers cDw2dF6vWlQ 2560 Instructor Interview: Transforming Residential Education with Open Digital Content klubJGAZDOI 2561 Instructor Interview: On Visualizing Cultures CTVFDb44ses 2562 3. Systems Modeling Languages b0VqqwHLqcI 2563 11. Lifecycle Management d44SDevJYR0 2564 6. Design Definition and Multidisciplinary Optimization dv8Dbyfcrd4 2565 7. Miscellaneous Topics — MBSE and Introduction to CAD (Guest Lecture from Solidworks) 9AtMQqCBdhw 2566 8. Systems Integration and Interface Management J_y2I09rj_I 2567 2. Requirements Definition rpGJsC5INd4 2568 10. Commissioning and Operations -63JXElqPaY 2569 9. Verification and Validation ScbSrUSbumo 2570 4. System Architecture and Concept Generation sOkQ4HBmZXo 2571 5. Concept Selection and Tradespace Exploration -Km2237G0P8 2572 Assessing Student Work Completed as Teams 3_vcJ6l7b8Y 2573 Online Written and Oral Exams 4hYgHHC-5z8 2574 Learning from CanSat Examples 7IqUQUic5cI 2575 Team Charters Gv3fPjWiQhs 2576 Reflective Memos RsOCnszziDA 2577 Teaching with Concept Questions Wc0PmAIEUhM 2578 Course Design and Orienting Students with the "V Model" aiSpEUZzP0A 2579 Teaching the Class as a Small Private Online Course (SPOC) MOdNzHR_tck 2580 Meet the Educator rh9ggz7vyM8 2581 Ideal Team Size for the CanSat Competition v6eIvQ9wU1w 2582 Engaging Students in the Design Process through the CanSat Competition YkYeYhXUeEE 2583 1. The Importance of Chemical Principles VXeTfT8JL0Q 2584 Clicker Competitions S5UKjrfJiL8 2585 Building a Team of Teaching Assistants _ZZ6jwuBJxc 2586 Preparing for Lectures htRqniQFm5g 2587 Promoting Active Participation During Lectures -Y8pOF1AgUY 2588 Spotlighting Contemporary Chemists 739SB34oEyo 2589 Using Humor to Engage Students r7MO11iMsOQ 2590 5.111: A Space to Discover Your Passion for Chemistry AVL5AwJrrEU 2591 19. Chemical Equilibrium: Le Châtelier’s Principle YEUyMX7kouw 2592 Meet the Educator xB8xRCSyQlY 2593 Pizza Forums: Connecting with Students Ja9eEQQzTic 2594 12. The Shapes of Molecules: VSEPR Theory lLdPSLNxDqA 2595 28. Transition Metals: Crystal Field Theory Part I BBbuj0XpaiQ 2596 14. Valence Bond Theory and Hybridization JBgbUI3pxV0 2597 27. Introduction to Transition Metals KHkNrbSKFic 2598 33. Kinetics and Temperature ed_XR1BzuQs 2599 10. Lewis Structures 4q0T9c7jotw 2600 32. Kinetics: Reaction Mechanisms FJCVSswFXyE 2601 20. Solubility and Acid-Base Equilibrium Hc5ODj1Ml6c 2602 11. Formal Charge and Resonance OjhZYx1FbhI 2603 16. Thermodynamics: Gibbs Free Energy and Entropy -jJz5OMmuP0 2604 7. Multielectron Atoms O192jrR80oo 2605 13. Molecular Orbital Theory Qg7pQ_CYaIQ 2606 4. Wave-Particle Duality of Matter; Schrödinger Equation XKeAd4xybjM 2607 31. Nuclear Chemistry and Chemical Kinetics caonmXHGB60 2608 22. Acid-Base Equilibrium: Salt Solutions and Buffers f6Z99Gu6XEE 2609 26. Chemical and Biological Oxidations wS1MX-C2V9w 2610 15. Thermodynamics: Bond and Reaction Enthalpies LWmVdG0uj2g 2611 8. The Periodic Table and Periodic Trends Om_5b29d_9g 2612 24. Acid-Base Titrations Part II _U6YamvF7BE 2613 3. Wave-Particle Duality of Light f0udxGcoztE 2614 18. Introduction to Chemical Equilibrium B7iFcW8USjQ 2615 30. Kinetics: Rate Laws pIwp65fPyYU 2616 23. Acid-Base Titrations Part I pn1cxuBmhtI 2617 35. Applying Chemical Principles NIZFPnHtrBA 2618 9. Periodic Table; Ionic and Covalent Bonds V-RPM3e8Ws0 2619 6. Hydrogen Atom Wavefunctions (Orbitals) awdQqF9CFt0 2620 17. Thermodynamics: Now What Happens When You Heat It Up? kO0VmaLkgj8 2621 5. Hydrogen Atom Energy Levels p8AAjZXr5dg 2622 34. Kinetics: Catalysts pJdUR2uak2s 2623 21. Acid-Base Equilibrium: Is MIT Water Safe to Drink? CFPnZ66nge4 2624 29. Transition Metals: Crystal Field Theory Part II ustfXi-mpkI 2625 2. Atomic Structure BZzkyqe6KD8 2626 25. Oxidation-Reduction and Electrochemical Cells Ex_fFlwZoM0 2627 Three dimensional current and conservation J2ltXyByPJA 2628 Probability current and current conservation MJM1AzpB6Y4 2629 Three-dimensional Fourier transforms vcuY46RwoV0 2630 Delta function potential I: Preliminaries 2EV1vJAAo8M 2631 Solving particle on a circle 5L4QfjbK87M 2632 Is probability conserved? Hermiticity of the Hamiltonian 8x94EgM2Mpg 2633 de Broglie wavelength in different frames QMeKIiufg5s 2634 Qualitative insights: Local de Broglie wavelength i-bP2OkQxUI 2635 Parseval identity vWGP5dogNm8 2636 Widths and uncertainties dzI5PddY6eE 2637 Wavepackets and Fourier representation 1D4VPbhDy_A 2638 Uncertainty and eigenstates 1dW_izzvfOk 2639 Delta function potential I: Solving for the bound state 79GY-hI_emE 2640 Correspondence principle: amplitude as a function of position 7euh_iwzSGo 2641 Free Schrödinger equation 8abBLKEZLaI 2642 Fourier transforms and delta functions AtjMKPzNIXQ 2643 Potentials that satisfy V(-x) = V(x) CdAKFagtXpQ 2644 Finite square well. Setting up the problem DvFb-D1zJTA 2645 Reality condition in Fourier transforms K3WI62VJqVo 2646 Eigenfunctions of a Hermitian operator M2i8R6kMXKA 2647 Expectation values on stationary states NwPOhzDPHKc 2648 Node Theorem R-5hjmV-bdY 2649 Interpretation of the wavefunction RxWfrE3o-9k 2650 Recursion relation for the solution T6TQHNXy5Wg 2651 The wave for a free particle m7UT2Hr465o 2652 Commutators, matrices, and 3-dimensional Schrödinger equation -UgQEHHXTRM 2653 Group velocity and stationary phase approximation AnzhigYawy8 2654 Time dependence of expectation values gMnQ21-pjOA 2655 Comments on the spectrum and continuity conditions ipXNYnO7yRk 2656 Time evolution of a free particle wavepacket jd4es6Bo600 2657 Finite square well energy eigenstates 3_qvO8bKGus 2658 The frequency of a matter wave 8KQ-yK2xm60 2659 Stationary states: key equations fWCGM2auQPs 2660 Local picture of the wavefunction gMHkf-107Sw 2661 Infinite square well energy eigenstates i81OpQJIH8U 2662 Motion of a wave-packet sxzFpOsvfgU 2663 Harmonic oscillator: Differential equation vnyxYtj0mfE 2664 Ground state wavefunction Y6Ma-zn4Olk 2665 Quantization of the energy _jPVD45YYlk 2666 Consistency condition. Particle on a circle eNf8nH1yEYc 2667 Behavior of the differential equation rCRH9CTThlo 2668 Defining uncertainty XF6FAEi_54I 2669 Completeness of eigenvectors and measurement postulate EdXaUfRynx8 2670 Nondegeneracy of bound states in 1D. Real solutions d4skxu7MpFI 2671 Normalizable wavefunctions and the question of time evolution qP6y2edM6Ms 2672 Expectation value of Hermitian operators rwzg8iEOc8s 2673 The general Schrödinger equation. x, p commutator 50Tla309i7o 2674 Shape changes in a wave XQKV-hpsurs 2675 Expectation values of operators x_ngaeI00qU 2676 Nodes and symmetries of the infinite square well eigenstates YdtHAIh-kas 2677 Galilean transformation of ordinary waves e0C1Bkcjrdc 2678 Energy eigenstates for particle on a circle 45M-BtYAcwg 2679 Energy eigenstates on a generic symmetric potential. Shooting method 8CCFPgd_P1w 2680 Algebraic solution of the harmonic oscillator ELBh60GU5yE 2681 Momentum operator, energy operator, and a differential equation 62nDLA_A8gs 2682 1. Course Overview and Introduction (MIT 15.S50 How to Win at Texas Hold 'Em, January IAP 2016) _GgdGtQME1I 2683 4. Preflop Re-raising Theory zlmokDj0DaU 2684 6. Independent Chip Model u14ymLSF8y4 2685 7. An In-depth Combinatorial Hand Analysis in Cash Games KTzFk1s2ymE 2686 3. Tournaments vs. Cash Games uFsM8pc36QQ 2687 2. Introduction to Postflop Play jANZxzetPaQ 2688 Quantum mechanics as a framework. Defining linearity EJWG9-etPFw 2689 Incident packet and delay for reflection Lt2Y6fLJ09Q 2690 Associated Legendre functions and spherical harmonics BRFekCz4XQY 2691 Creation and annihilation operators acting on energy eigenstates CR-eOhdxbes 2692 The nature of superposition. Mach-Zehnder interferometer 8Dxo4LPK_9w 2693 Modelling a resonance 8NKsBpjXRt0 2694 Hamiltonian and emerging spin angular momentum WR88_Vzfcx4 2695 Compton Scattering bX-k26w-tsU 2696 Reflection and transmission coefficients byEaU9ILHmw 2697 The photoelectric effect dVWKsiaAZ14 2698 Center of mass and relative motion wavefunctions lWTUcojZ_gQ 2699 Simultaneous eigenstates and quantization of angular momentum 8cRnBhBaSOo 2700 Energy levels and diagram for hydrogen 3VXLIF2DpHI 2701 Series solution and quantization of the energy 7q32Wnm4dEw 2702 Hydrogen atom two-body problem 0ABYYJSvkVk 2703 Scattering states and the step potential 0T83-47Vi-M 2704 Resonances in the complex k plane 3Cij8HYKXOk 2705 Eigenstates of the Hamiltonian sWmY5KME7oo 2706 Phase shift for a potential well -8mPXAsX3DY 2707 The simplest quantum system z79v39lMR3k 2708 Step potential probability current Cb_3sOYLjUI 2709 Excursion of the phase shift EdRkQmmq7vk 2710 Waves on the finite square well EkpbxgEslE4 2711 Energy below the barrier and phase shift G3HSP3qMgKI 2712 Entanglement GyukKStk6Ls 2713 Levinson's theorem, part 1 NXPvXI603RA 2714 Wavepackets KfbvrGt3MlI 2715 Schrödinger equation for hydrogen KkSr0SvXfNY 2716 Resonant transmission Mh8vUEStCQ8 2717 Commuting observables for angular momentum Ot9OjT34gkA 2718 Degeneracy in the spectrum and features of the solution VY-_xLxHQbA 2719 Effects of resonance on phase shifts, wave amplitude and time delay Z4CSAWrzguY 2720 Energy eigenstates of hydrogen OQMczXtDnpU 2721 Half-width and time delay _XDm2cxC-UU 2722 Effective potential and boundary conditions at r=0 avQ2XUzbsgk 2723 Rydberg atoms c5yzy1S3gPg 2724 Orbits in the hydrogen atom dnuZx9fZHsU 2725 de Broglie’s proposal f079K1f2WQk 2726 Necessity of complex numbers fXlzY2l1-4w 2727 More on the hydrogen atom degeneracies and orbits kefsxztSX74 2728 Number operator and commutators 0USje5vTIKs 2729 Mach-Zehnder interferometers and beam splitters 0xNmc2tJ-YM 2730 More on superposition. General state of a photon and spin states 5u-9lFhCl5w 2731 Ramsauer-Townsend phenomenology xoCHe0mtxu0 2732 Angular momentum operators and their algebra yhI3jTX4dY4 2733 Levinson's theorem, part 2 mnvYIEbJXlM 2734 Time delay and resonances w49WAat6ymk 2735 Scattered wave and phase shift xmjvqbYvY9o 2736 Excited states of the harmonic oscillator kiuwtaprFjk 2737 Linearity and nonlinear theories. Schrödinger's equation lA8-N_ARHTw 2738 Particle on the forbidden region sPsDI0dICtc 2739 Translation operator. Central potentials 8OsUQ1yXCcI 2740 Photons and the loss of determinism GWMeYKUvj7Y 2741 Scales of the hydrogen atom S9RjSQro2e0 2742 Units of h and Compton wavelength of particles gKSRrTik1SA 2743 Orthonormality of spherical harmonics twdF0EIbFds 2744 Scattering in 1D. Incoming and outgoing waves vFZeh8bMx58 2745 Elitzur-Vaidman bombs yqrMAZkQOwI 2746 Wavepackets with energy below the barrier 37-GdFJGSXs 2747 Interferometer and interference 0EMIK-6LUE4 2748 23.3 Potential Energy Reference State 1s6_4qX-u2o 2749 27.5 Worked Example: Gravitational Slingshot 4K539RaRDXU 2750 4.2 Newton's Third Law 5zXYEVWSIsg 2751 PS.1.1 Three Questions Before Starting ThZH56PUwNc 2752 23.2 Potential Energy of Gravity near the Surface of the Earth V-fy33vi-64 2753 18.4 Solve for Velocity in the Moving Frame ZjGjNsmsNBU 2754 P.1.4 Sketch the Motion 63U4_OxohOw 2755 PS.2.2 Worked Example - Stacked Blocks - Free Body Diagrams and Applying Newtons 2nd Law 9VJetX_EQqs 2756 19.7 Rocket Problem 7 - Solution with External Forces CcJoqITNvh0 2757 26.3 Totally Inelastic Collisions PQfYJ2TjpEU 2758 PS.1.2 Shooting the apple solution QAdiRwOLl0A 2759 20.3 Work by a Non-Constant Force S9_Oe51XkVY 2760 8.2 Circular Motion: Position and Velocity Vectors SLPRYIb7RdI 2761 19.5 Rocket Problem 5 - Thrust and External Forces 6-7BOpZ2k04 2762 27.1 Worked Example: Elastic 1D Collision B6a9FaYI730 2763 27.2 Relative Velocity in 1D CsHQ35j_1kY 2764 21.2 Scalar Product in Cartesian Coordinates Cslq_ZYdYwE 2765 15.5 Force on a System of Particles FSW9EQNZvxI 2766 20.6 Power _r7pI2_FjSg 2767 Applying Newton's 2nd Law aAybYawUPC4 2768 Internal and External Forces esHLwySu4XU 2769 0.6 Going Between Representations gWLC3r6EHl0 2770 12.2 Constraint Condition i2_731Gi9bg 2771 21.5 Work-Kinetic Energy Theorem in 2D and 3D jAcdLZRhYNU 2772 DD.2.4 Worked Example: 1D Elastic Collision in CM Frame lufK0UlJ7aE 2773 10.3 Worked Example - Angular position from angular acceleration. nfawe03nvAY 2774 22.3 Conservative Forces oQqskrRWGco 2775 21.4 Work in 2D and 3D sgymEX-4FxE 2776 3.3 Instantaneous Acceleration in 2D t2PkbsWjG80 2777 23.5 Potential Energy of Gravitation uhaFP0xEmzM 2778 PS.2.2 Worked Example - Stacked Blocks - Solve for the Maximum Force 7Mv5hT1nugQ 2779 19.2 Rocket Problem 2 - Momentum Diagrams xZn4l1TSvPQ 2780 2.1 Introduction to Acceleration xxGA-7soXiw 2781 17.7 Reduction of a System to a Point Particle flwYlUfw4WU 2782 14.3 Resistive forces - high speed case UE-O9TiKOw0 2783 27.6 2D Collisions XeTsZhYHY_E 2784 PS.2.3 Window Washer Free Body Diagrams cwO5KdgBQh0 2785 25.3 Reading Potential Energy Diagrams IV9NhNIrrDw 2786 6.1 Contact Forces KmGPMec8-iU 2787 DD.2.2 Relative Velocity is Independent of Reference Frame QPV-DmpGXeQ 2788 17.6 Velocity and Acceleration of the Center of Mass ofgusnhQ07Q 2789 11.2 Worked Example - Car on a Banked Turn q785KV5ZIN0 2790 8.3 Angular Velocity qmCbc9dbwXU 2791 2.3 Worked Example: Acceleration from Position 83NmtaE7fEk 2792 3.4 Projectile Motion CFh3gu-z_rc 2793 17.5 Worked Example - Center of Mass of a Uniform Rod GuiIyYbI0HM 2794 12.3 Virtual Displacement l_NW5pPXhg4 2795 9.2 Uniform Circular Motion: Direction of the Acceleration lw9W32ezQhM 2796 12.4 Solve the System of Equations qxNJGKrx3EY 2797 2.2 Acceleration in 1D sN-m5WkbMyI 2798 18.1 Relative Velocity zLGu1dlP0UY 2799 21.3 Kinetic Energy as a Scalar Product -b0dFcebPcs 2800 17.2 Worked Example - Center of Mass of 3 Objects 1GvCIlHihEA 2801 15.1 Momentum and Impulse 30Ww1HsRblM 2802 14.1 Intro to resistive forces 5QKJG0FZTio 2803 13.4 Density 7Kq8BINVDiw 2804 PS.6.1 Rocket Sled - Integrate the Rocket Equation 7WDiK3flILc 2805 PS.2.1 Worked Example - Sliding Block 7x62TdS0Nn0 2806 DD.2.3 1D Elastic Collision Velocities in CM Frame 89SjJv30kGU 2807 4.1 Newton's First and Second Laws CfBeCHrQj_U 2808 7.2 Ideal Rope DYi8KTt8688 2809 25.2 Stable and Unstable Equilibrium Points FNOfxJxceIM 2810 12.1 Pulley Problems Vg8t8_IOHDg 2811 16.1 Cases of Constant Momentum _0PrwAbgoMA 2812 10.1 Circular Motion - Acceleration _7JPHNCT1Qo 2813 23.4 Potential Energy of a Spring d9ugFckUBcg 2814 20.2 Work by a Constant Force efpiHD_2O8E 2815 20.1 Kinetic Energy fLuyZ7ayDog 2816 22.1 Path Independence - Gravity UPnqIKBAMaQ 2817 19.6 Rocket Problem 6 - Solution for No External Forces Uoukes39gb0 2818 DD.2.5 Kinetic Energy in Different Reference Frames bX4liSWB4Gk 2819 PS.3.1 Worked Example - Orbital Circular Motion - Velocity cadbtBS5qf4 2820 13.3 Differential Elements JTePtoM_MeM 2821 14.2 Resistive forces - low speed case SjK2lmRFxc4 2822 P.1.5 Worked Example: Pedestrian and Bike at Intersection _mqFIqnCPak 2823 5.2 Worked Example: Gravity - Superposition ayIgWaBE0aw 2824 27.3 Kinetic Energy and Momentum Equation kJxsMnRZXqE 2825 1.2 Position Vector in 1D mjrQHIJj1iI 2826 DD.2.6 Kinetic Energy in the CM Frame oOQmu6ICxg4 2827 3.2 Instantaneous Velocity in 2D ol1COj0LACs 2828 17.1 Definition of the Center of Mass ozIdCgo5uI4 2829 PS.2.3 Window Washer Solution pb5hUGBjS3A 2830 P.1.3 Worked Example: Braking Car sxv80X2jQYQ 2831 15.4 Momentum of a System of Point Particles tniGFmPQc0E 2832 11.1 Newton's 2nd Law and Circular Motion uo86ir31pn0 2833 8.1 Polar Coordinates vUg50UI1aqs 2834 13.6 Summary for Differential Analysis xtpW7fw8s34 2835 15.2 Impulse is a Vector -M8swpL-Ij8 2836 DD.2.1 Position in the CM Frame yA203Lrd39E 2837 27.4 Worked Example: Elastic 1D Collision Again z5JfWSocZUQ 2838 24.1 Mechanical Energy and Energy Conservation 1UdGbyj8924 2839 24.4 Newton's 2nd Law and Energy Conservation 2TZa151GC-0 2840 21.1 Scalar Product Properties QCA3zOe2xdA 2841 4.3 Reference Frames Q3v_2znHCvg 2842 3.1 Coordinate System and Position Vector in 2D Lpd_TddOSZY 2843 PS.7.1 Worked Example - Collision and Sliding on a Rough Surface NBOL5X13UFY 2844 13.2 Differential Analysis of a Massive Rope NiCMMn12CIs 2845 5.1 Universal Law of Gravitation Bq0fDYtbfBA 2846 0.3 Coordinate Systems and Unit Vectors EHCACV8rdig 2847 25.1 Force is the Derivative of Potential ErlP_SBcA1s 2848 1.1 Coordinate Systems and Unit Vectors in 1D Jf2PgGInUEk 2849 0.2 Vector Operators 7TljYDljC5w 2850 18.3 Solve for Velocity in the Ground Frame TF93gm1_O8M 2851 20.5 Work-Kinetic Energy Theorem VZm6mxu2xlk 2852 0.5 Vector Decomposition into components W1lxlbJ0BZU 2853 1.3 Displacement Vector in 1D Xsg27_uGVZA 2854 19.3 Rocket Problem 3 - Mass Relations YGR5_Hf9dDg 2855 19.1 Rocket Problem 1 - Set up the Problem YdyhDdXaSP4 2856 1.5 Instantaneous Velocity in 1D ZBlHexE8m6A 2857 22.5 Summary of Work and Kinetic Energy dHMGV_WOG7w 2858 7.3 Solving Pulley Systems e548hRYcXlg 2859 17.3 Center of Mass of a Continuous System emrHcqEvXpw 2860 9.1 Uniform Circular Motion gEX7MjWwocE 2861 PS.3.1 Worked Example - Orbital Circular Motion - Radius gl9c9qJRqcM 2862 5.3 Gravity at the surface of the Earth: The value of g. jtOxRPQDuJs 2863 1.7 Worked Example: Derivatives in Kinematics l062G7RC8-o 2864 PS.2.2 Worked Example - Stacked Blocks - Choosing the System of 2 Blocks Together m8_3VwHy7tE 2865 20.4 Integrate adt and adx mLLUgcvQLgY 2866 6.2 Static Friction nCDOa63Jd6M 2867 23.1 Introduction to Potential Energy oRzzwpZ0ei4 2868 DD.2.7 Change in the Kinetic Energy pW6tqp1zRrg 2869 0.4 Vectors - Magnitude and Direction prCwfSiWuq0 2870 10.2 Angular Acceleration 0jWwl0bt6aU 2871 22.2 Path Dependence - Friction 9NS0JcjNdp4 2872 13.1 Rope Hanging Between Trees otGGuHt36XA 2873 1.4 Average Velocity in 1D z0xyQKalezI 2874 4.4 Non-inertial Reference Frames 4ZnijNan49U 2875 26.2 Kinetic Energy in Collisions OwNr82QgkP8 2876 22.4 Non-conservative Forces RBaBEjzMr4E 2877 7.1 Pushing Pulling and Tension YLDRzy8Dcgo 2878 26.1 Momentum in Collisions nWaoEjE8a8M 2879 PS.6.2 Snowplow Problem 3V5y9uq5au0 2880 12.5 Worked Example: 2 Blocks and 2 Pulleys sffRo1-_D8E 2881 DD.1.1 Friction at the Nanoscale vkWY73HnNYA 2882 PS.3.1 Worked Example - Orbital Circular Motion - Period ykwNGB9kuaA 2883 21.6 Worked Example: Block Going Down a Ramp sfH3Jw6LZm8 2884 Newton's 3rd Law Pairs H7xmTMQ265s 2885 2.4 Integration L5jhg4q1Xvo 2886 18.2 Set up a Recoil Problem NCCzjtqZ28M 2887 24.3 Worked Example - Block Sliding Down Circular Slope bEpq3yjismU 2888 15.3 Worked Example - Bouncing Ball bHocXJ4rv5g 2889 PS.6.1 Rocket Sled - Solve for Initial Velocity dvWKCH0ocu8 2890 PS.6.1 Rocket Sled - Differential Equation huPKjd3wLyc 2891 24.2 Energy State Diagrams rCP_-Wuikwo 2892 7.4 Hooke's Law Veyh-DhI8lE 2893 13.5 Demo: Wrapping Friction uua2hbbp7h4 2894 19.4 Rocket Problem 4 - Solution w7z_z-lucyU 2895 16.2 Momentum Diagrams WLHAaaGHfe8 2896 11.3 Demo: Rotating Bucket _zl4b5MnPF0 2897 3.5 Demo: Shooting an Apple rqTAICbKHYM 2898 3.5 Demo: Relative Motion Gun d2POYCmmM8A 2899 32.3 Worked Example - Angular Momentum About Different Points r2Qb0vsxa8Y 2900 29.4 Parallel Axis Theorem c15RtHXBVuQ 2901 34.5 Worked Example - Particle Hits Pivoted Ring cMu0hsvgkGk 2902 29.6 Deep Dive - Derivation of the Parallel Axis Theorem WwvDJqtHNBU 2903 32.2 Calculating Angular Momentum hxa6jAYA980 2904 36.1 Friction on a Rolling Wheel PKOhhK7kPi4 2905 31.2 Internal Torques Cancel in Pairs TvdmaZR6m8Q 2906 36.4 Worked Example - Yoyo Pulled Along the Ground X9K8LT7SCZ0 2907 30.1 Introduction to Torque and Rotational Dynamics ZMa-xKcM2L8 2908 37.1 Kinetic Energy of Translation and Rotation 2oK7Eb0YZ9U 2909 28.3 Review of Angular Velocity and Acceleration BPnbq6BobdA 2910 29.3 Moment of Inertia of a Disc FlHKTvUjD6g 2911 31.4 Worked Example - Atwood Machine 1AJbVRQTZlA 2912 29.2 Moment of Inertia of a Rod 1BU28txGAFI 2913 30.4 Torque 0QF_uCgZW4Y 2914 29.1 Kinetic Energy of Rotation oILq3xz_XtU 2915 35.1 Translation and Rotation of a Wheel 2guwjwIHmGg 2916 31.7 Worked Example - Two Blocks and a Pulley Using Energy 2tSUT6HDeaw 2917 32.4 Angular Momentum of Circular Motion 4r1xgrWbALg 2918 35.5 Contact Point of a Wheel Rolling Without Slipping 5oLLnCGStUc 2919 DD.3.3 Deep Dive - Gyroscopes - Nutation and Total Angular Momentum 9yFkrh7-igc 2920 30.2 Cross Product CfTLS6YYPms 2921 36.2 Worked Example - Wheel Rolling Without Slipping Down Inclined Plane - Torque Method DSk8HTcB7x0 2922 34.1 Torque Causes Angular Momentum to Change - Point Particle IWD-Aue6aIk 2923 PS.10.1 Worked Example - Blocks with Friction and Massive Pulley QmCQUBSsKwQ 2924 29.5 Deep Dive - Moment of Inertia of a Sphere V1I-vrXGl3A 2925 37.3 Angular Momentum of Translation and Rotation W3TqFzVh_rE 2926 34.3 Angular Impulse ZApVXJZF7pE 2927 28.2 Introduction to Translation and Rotation cHKyuSAySyE 2928 36.3 Demo: Spool Demo jOPA3XY-V3U 2929 DD.3.2 Deep Dive - Gyroscopes - Precessional Angular Velocity and Titled Gyroscopes lkeX42KQjac 2930 35.3 Rolling Wheel in the Ground Frame WxkwkGEVu-E 2931 35.2 Rolling Wheel in the Center of Mass Frame NbXDgm7UyVM 2932 33.5 Kinetic Energy of a Symmetric Object O_M8asN10oQ 2933 31.1 Relationship between Torque and Angular Acceleration RX88J2e4W0M 2934 36.5 Analyze Force and Torque in Translation and Rotation Problems 3JzsqGZ6opI 2935 34.4 Demo: Bicycle Wheel Demo ByTlCmDoEnk 2936 30.5 Torque from Gravity Idx3VgOpUDk 2937 32.1 Angular Momentum for a Point Particle 1UD560RQ684 2938 35.4 Rolling Without Slipping Slipping and Skidding reUjl788R9Q 2939 31.3 Worked Example - Find the Moment of Inertia of a Disc from a Falling Mass uRUAnKCyyig 2940 31.5 Massive Pulley Problems x5WavAj2M8A 2941 34.2 Torque Causes Angular Momentum to Change - System of Particles mHVnpuhfpvI 2942 33.1 Worked Example - Angular Momentum of 2 Rotating Point Particles rd9d0WBFzt8 2943 33.2 Angular Momentum of a Symmetric Object tO6Wh_HhifI 2944 33.4 If Momentum is Zero then Angular Momentum is Independent of Origin jM-JYT2j6Yw 2945 30.3 Cross Product in Cartesian Coordinates xh_LCHvzp-Q 2946 37.2 Worked Example - Wheel Rolling Without Slipping Down Inclined Plane 0mGd0JUmgm8 2947 12.0 Week 4 Introduction 0qEIs6ie2q8 2948 20.0 Week 7 Introduction 6h3T3qIkxqw 2949 32.0 Week 11 Introduction ThP6wQkf5ec 2950 DD.3.1 Deep Dive - Gyroscopes - Free Body Diagrams, Torque, and Rotating Vectors EX0uHJbIw68 2951 23.0 Week 8 Introduction dlJtUvRaGdE 2952 8.0 Week 3 Introduction efH7pq9YVQw 2953 28.0 Week 10 Introduction D2lW7o32fzk 2954 18.0 Week 6 Introduction i4u7SZjoAs4 2955 1.0 Week 1 Introduction (8.01 Classical Mechanics) EhgF2OViDDs 2956 35.0 Week 12 Introduction MoRip5VVdkI 2957 26.0 Week 9 Introduction n1cXiw3s72k 2958 15.0 Week 5 Introduction yLb_a1EE888 2959 4.0 Week 2 Introduction u_LAfG5uIpY 2960 28.1 Rigid Bodies 5ucfHd8FWKw 2961 0.1 Vectors vs. Scalars C1lhuz6pZC0 2962 1. Introduction, Optimization Problems (MIT 6.0002 Intro to Computational Thinking and Data Science) 6wUD_gp5WeE 2963 5. Random Walks esmzYhuFnds 2964 12. Clustering fQvg-hh9dUw 2965 10. Understanding Experimental Data (cont.) V_TulH374hw 2966 3. Graph-theoretic Models eg8DJYwdMyg 2967 13. Classification h0e2HAPTGF4 2968 11. Introduction to Machine Learning rUxP7TM8-wo 2969 7. Confidence Intervals -1BnXEwHUok 2970 4. Stochastic Thinking K2SC-WPdT6k 2971 14. Classification and Statistical Sins OgO1gpXSUzU 2972 6. Monte Carlo Simulation uK5yvoXnkSk 2973 2. Optimization Problems iOZVbILaIZc 2974 15. Statistical Sins and Wrap Up soZv_KKax3E 2975 8. Sampling and Standard Error vIFKGFl1Cn8 2976 9. Understanding Experimental Data 5EodYYcTgaE 2977 Please support OPEN through MIT OpenCourseWare PBggBCnfbC8 2978 Week 0: Welcome Video FE4d7BVFxoA 2979 Week 4 Update Video ox0-ancvQ5g 2980 Video 19: Time and Scale tei0bSKTyf0 2981 Video 24: Fuel Cells for Mobile Batteries Case Study MZTmdqC49WA 2982 Video 15: Imaging with a Tablet Camera cnF_eoMHbmQ 2983 Video 18: Designing Graphics d9LjcuZTzz0 2984 Video 2: Placing Objects on the Scanner 37CbZdeh_lU 2985 How-To-Do-It: Convert an Image from Horizontal to Vertical gZ9DWdzGNqQ 2986 Video 23: Liquid Battery Case Study h1GtR8xJraw 2987 Video 14: Using a Smartphone 7wOsPc0XtpY 2988 Video 6: Setting the Exposure DAyXoA2W7bU 2989 Video 12: Fluorescence 7_hOHxaaxGE 2990 Video 13: Use Your Imagination zYcRXHYKYTI 2991 Video 10: Point of View 6tAfLDGm9kA 2992 How-To-Do-It: Fix Mobile Distortion qE0eHhe6muY 2993 How-To-Do-It: Set Your Scanner lTTfrBbXeTk 2994 Video 30: Stretchable Sensors Case Study oOb7kSyOP4s 2995 Video 27: Soft Lithography Case Study ihokgDNXDzY 2996 Video 4: Enhancing the Scanned Image fdJ7hBBivQc 2997 Video 11: An Introduction JF-5nlUNx_g 2998 Week 1 Update Video McyxfIYo4lM 2999 Video 9: Backgrounds W18hxFk9lAQ 3000 Video 1: Using a Flatbed Scanner _rU1VmnyYG0 3001 Video 29: Analytical Microreactor Case Study h0LYxgHiMDE 3002 Video 3: Transmitted and Reflected Light 4_tngSkFXes 3003 Video 7: Aperture AJdBJFlkvpg 3004 Video 21: Image Enhancement OWAEr2egtsI 3005 Video 20: Cover Submissions 17VFTJvgBlY 3006 Video 8: Composition bHbWFHMffzE 3007 How-To-Do-It: Digitally Replace a Background ffOGEN5WZu4 3008 Video 28: Chemical Vapor Deposition Case Study Ki_X8RO3DkU 3009 How-To-Do-It: Sharpen an Image gmq2NACljMc 3010 Video 26: Microneedles Case Study sKYY6o71iNM 3011 Video 16: "Beautiful Chemistry" 3wmmiqjCZyA 3012 Week 2 Update Video IuCpd9kyeSM 3013 Video 5: Camera and Lens t5_ymNZGsCI 3014 Video 31: Solar Cell Case Study YPZ-Cizsh2I 3015 Video 22: Speaking to the Public fQ6mdCCPIIM 3016 Week 3 Update Video plCuZVzK6kk 3017 Video 17: Looking at Videos xB8eS-96q3I 3018 Video 25: A Solar Thermophotovoltaic System (STVP) Case Study MsIvs_6vC38 3019 4. Factorization into A = LU 8PdnOZI7H5E 3020 23. Security Economics 2PO8h1pVW50 3021 22. Guest Lecture by MIT IS&T I0Psvvky-44 3022 7. Sandboxing Native Code OgGTJIgNewE 3023 19. Anonymous Communication TQhmua7Z2cY 3024 6. Capabilities dNl22h1kW1k 3025 4. Privilege Separation r4KjHEgg9Wg 3026 2. Control Hijacking Attacks uT7BXusDgDM 3027 20. Mobile Phone Security 3v5Von-oNUg 3028 16. Side-Channel Attacks WlmKwIe9z1Q 3029 9. Securing Web Applications xSQxaie_h1o 3030 3. Buffer Overflow Exploits and Defenses MT7X17ZRo1U 3031 17. User Authentication bA3xCpYLA34 3032 15. Medical Software eRJ_r8WF1Y0 3033 8. Web Security Model BZTWXl9QNK8 3034 12. Network Security WG5UbMrUiLU 3035 21. Data Tracking XMEFdofERLI 3036 11. Ur/Web q1OF_0ICt9A 3037 14. SSL and HTTPS YTWXAFJf8bw 3038 18. Private Browsing vuS8mlpRn_0 3039 17. Series Expansions Part 3 cLfyjIlu9Uw 3040 Introduction to the Course 6gffCYK1_nk 3041 Interview with Jianming Zhou and Ryder Pearce 8MLEYc3PLUc 3042 What Occupations are Growing? ADWGuj3nDQo 3043 The Changing Role of the Corporation: Interview with John Reed lbqlj1g8gu0 3044 Discussion of Student Reports on Their Plans for Action C-n3hyz-sSY 3045 High Performance Work Systems CBToKajn2u4 3046 Introduction to Week 3 C_akTI3vnHQ 3047 The Post-War Social Contract DE9TnscEmtw 3048 Around the World: Role of the Corporation in Different Societies DidA5vk0h_U 3049 High School and College: Necessary but Not Sufficient Gr_MZYzAWGI 3050 Life Long Learning: Moving from Rhetoric to Reality Hu-ZLesnxfc 3051 Introduction to Week 4 ICBy0tTtgR4 3052 What Changed in the 1980s and Why Should We Care? LxDmWdOwIA8 3053 A Guide to the Negotiations Exercise M4dl1quiPPY 3054 Around the World: Interview with Ms. Nazma Akter MrQwihmwKoc 3055 Early Childhood Education for All d5chZ4A54DI 3056 Alternatives to the Traditional Corporation fbE9xXfb0PA 3057 Interview with Erik Brynjolfsson VieMadwoNNs 3058 Careers and Competencies with Professor Lee Dyer XWFocLnBdhM 3059 The Decline of Unions in the United States _CUXbDB0bUU 3060 The Purpose of the American Corporation RKjvoLeojfk 3061 Social Contracts, Past and Present UmLCGjbeeJ8 3062 MIT Technology Conference with Meryam Bukhari UybHQEFy56c 3063 The Market Basket Case Q67wzxKElp8 3064 The Rise and Fall of Saturn Q69ILtZSteE 3065 Introduction to Week 5 juxuwNK3G-c 3066 A Message from U.S. Secretary of Labor Thomas Perez to the Next Generation Workforce l-bSkqJ6ytE 3067 Current Challenges and Opportunities: Today's Labor Market in Perspective q2mz6LZVnT8 3068 Interviews with Barbara Dyer and Scott Stern sDnM5fTqXv4 3069 Worker Advocacy and Technology OmiGPen5vSo 3070 The New Deal at Work PZQgldCzIjs 3071 Meet Professor Kochan and the 15.662x Team yBvKhgnYLM4 3072 All Innovations Are Local yGvxqV-qpQ8 3073 Introduction to Week 2 Wi4W4PTzdhI 3074 Introduction to Week 1 (RES.15-003 Shaping the Future of Work) r1yb4-JvZhU 3075 A Message from AFL-CIO Secretary Treasurer Liz Shuler uc8kW2iDA3A 3076 The Millennial Generation's Views on their World of Work xApFTcsFPcQ 3077 Uber Case Study WJUHzSQPRVM 3078 Holding Global Corporations Accountable mslvJdTQhHc 3079 Managing Societal and Workplace Conflicts: Interview with Mary Rowe xDoe1HvHfbM 3080 Emerging Forms of Work yBgKkYcoPgM 3081 Animated History of Work 5eKqzY-dyxQ 3082 Introduction to Week 6 Tpaw_dE9LyY 3083 A Message from Guy Ryder, ILO Director-General jfhdvFAplpU 3084 A Message to HR Professionals from Professor Lee Dyer XOfD39Pr4ZU 3085 Traces and Trends LJNAUHOmpAY 3086 Time and the City kd6ww6aPT0A 3087 Nature + the City zoa2pKYp_fk 3088 Active Learning Overview I1IeF7D7kkY 3089 Debate fqrOxeL-fwk 3090 Think-Pair-Share hpM-siY2Bl0 3091 Personal Response Systems I7_PfCBBcFI 3092 Lightning Round n9uDbwgnSp0 3093 Mud Cards L-Sv1oL43ew 3094 Beach Ball Nrylh_-40ng 3095 Jigsaw Zm8uMV5aMdw 3096 Meet the Educator hGBNi4P9OfA 3097 Class Session 5: Teaching Methodologies, Part II: Active Learning: Why and How aGuZTE8-lOQ 3098 Class Session 3: Designing a Course: Developing Learning Outcomes rqI_0FNAeS0 3099 Class Session 8: Teaching with Educational Technology Y6J8I056Ffw 3100 Shell vs. Editor -jjUoTiaSHw 3101 String Manipulations -wz4iU2V-Yo 3102 Errors 4gPwo38MNss 3103 Function Calls 7lQXYl_L28w 3104 11. Understanding Program Efficiency, Part 2 2__KumJsGXc 3105 Class Instance EFCdr_43qmU 3106 Bindings WPSeyjX1-4s 3107 6. Recursion and Dictionaries FlGjISF3l78 3108 9. Python Classes and Inheritance FKp-6sojt9A 3109 List Aliasing/Mutation QaOHeMnpnmU 3110 Functions as Arguments 4WtaFLayz_w 3111 For Loops With Strings zYVWQpCitKQ 3112 Simple Lists 5McjE8e5gIg 3113 Black Box and Glass Box Testing RvRKT-jXvko 3114 5. Tuples, Lists, Aliasing, Mutability, and Cloning SrkqbLOQcEo 3115 List Operations mrvBnZIEsZY 3116 For Loops 0Whyfs88TYE 3117 Exceptions 6LOwPhPDwVc 3118 12. Searching and Sorting goalLDamePE 3119 Methods o9nW0uBqvEo 3120 10. Understanding Program Efficiency, Part 1 -DP1i2ZU9gk 3121 8. Object Oriented Programming F-_PKUUM-qY 3122 Python vs. Math SE4P7IVCunE 3123 3. String Manipulation, Guess and Check, Approximations, Bisection lniF6ys2CIk 3124 Comparisons 0jljZRnHwOI 3125 2. Branching and Iteration MjbuarJ7SE0 3126 4. Decomposition, Abstraction, and Functions jjbWNcIjmzc 3127 Branching vqn_yk5aFcI 3128 Class Definition 8s0d87sjy1A 3129 Subclass P-0w8xWcnDQ 3130 While Loops ncpb4wIsQu8 3131 Tuples qq7I2MQNrtU 3132 Special Methods w4uxYDPsjbw 3133 Strings 9H6muyZjms0 3134 7. Testing, Debugging, Exceptions, and Assertions C_pgH5QhIZ8 3135 Getters and Setters _ax4eNMI9Dw 3136 Method Call 7MWXdi-e-DQ 3137 Video 4: Divisibility Results Based on the Binomial Theorem w_Bl6xbvl3g 3138 Video 1: Introduction to Vectors - Position, Line, Free and Unit Vectors 6vI7xuRSUiM 3139 Video 9: 3D Geometry, Angle Bisector & Line of Intersection _ZG2U_lfc1Q 3140 Video 2: Scalar Triple Product kqTVh_RzPDI 3141 Video 6: How to Solve Linear Equations Using Matrices & Determinants 2o9hOTP8VU4 3142 Video 8: 3D Geometry, Perpendicular Distance, Perpendicular Line Kd5jrNYGQr4 3143 Video 5: Introduction to Trigonometry zv2iDnxWJfM 3144 Video 7: Introduction to Functions qFcra-xNYrw 3145 Video 3: The Binomial Theorem IlkbvrpAbPU 3146 Promoting Low Carbon Development in Johor Bahru JlKqhxwezkg 3147 Challenges of Urban Flooding in Malaysia 2Y0cpVGuDoM 3148 Preservation of Local Identity and Architecture in the Face of Rapid Development in Malaysia DUKQ2SogFf8 3149 The Benefits and Costs of Converting Waste to Energy in Malaysia R65WafN88dw 3150 Reducing Motorcycle Fatality and Promoting Sustainable Transport in Malaysia 2cPGZ4H67Ek 3151 Saving Malaysia Means Saving its Mangroves ehZgJ8Y2UJI 3152 Redefining Urban Rivers: River Restoration in Johor Bahru, Malaysia KFajwRMlo0s 3153 Transforming Shopping Malls into Environmentally and Socially Sustainable Spaces in Malaysia 0oXquNdvAnk 3154 "Reduce, Reuse and Recycle", Encouraging Better Solid Waste Management Practices in Malaysia 4-adJfyB62s 3155 Applying a Bottom Up Approach to Improve Energy Subsidies in Malaysia PfxuFD4ML9s 3156 Converting Biomass to Energy: A Low Carbon Development Strategy for Malaysia 9ICCzJGPaPA 3157 Innovative Strategies to Provide Solid Waste Management in Penang, Malaysia hP9FIMolHEA 3158 Development Induced Displacement in Malaysia AuSAXLGGnXU 3159 A Road Map of Urban Village Transformation in Kuala Lumpur, Malaysia WFbNs3fZJAo 3160 Encouraging Green Architecture in Malaysia xUsGRYtpLDc 3161 Strategies to Reduce Air Pollution from Vehicle Emissions in Penang, Malaysia zqG5N0ixkak 3162 Managing Urban Sprawl in Kuala Lumpur, Malaysia b-PoEwPoRe8 3163 Exploring The Potential For CO2 Emission Reduction Through Green Technology Adoption in Malaysia ZPmBMd6OZeQ 3164 6. Wave Profiles, Heat Equation / point source CSqbjfCCLrU 3165 23. Cache-Oblivious Algorithms: Medians & Matrices 94YsseQIXq0 3166 Video 2: Phase Diagram ZgYuF0SbPDM 3167 Video 3: Lift b04CichdN5g 3168 Video 1: Expectations EGvqg0vUBmU 3169 Video 4: The First Day uPsMwJ116lQ 3170 Video 5: Introductions Btl0HCfSPuU 3171 5. Honeycombs: Out-of-plane Behavior UgKnOuaY1G8 3172 14. Tissue Engineering: Osteochondral Scaffold; How To Write a Paper _tdj84EV7BI 3173 9. Foams: Thermal Properties 5NUS6bcUXmY 3174 7. Natural Honeycombs: Cork; Foams: Linear Elasticity bDnia4HJRqk 3175 2. Processing of Cellular Solids cQpCPzetm3E 3176 10. Exam Review q-9YlXesHtI 3177 3. Structure of Cellular Solids 4zpQwirFsbk 3178 17. Sandwich Panels hOZ6-geaRUo 3179 1. Introduction and Overview (MIT 3.054 Cellular Solids: Structure, Properties, Applications, S15) q-uLJN8upWE 3180 4. Honeycombs: In-plane Behavior v73uMp1fPjM 3181 11. Trabecular Bone and Osteoporosis vVfI1wTp0Jg 3182 15. Cell-scaffold Interactions; Energy Absorption Txidu-5VYfU 3183 13. Tissue Engineering Scaffolds: Processing and Properties WiFahA1iAv4 3184 8. Foams: Non-linear Elasticity jJvVmdkiD3Y 3185 6. Natural Honeycombs: Wood LzA1OqHY68M 3186 18. Natural Sandwich Structures; Density Gradients kpbG3L5awgk 3187 19. Biomimicking yDr8Df35C64 3188 12. Trabecular Bone, Osteoporosis, and Evolution yK5SA6HngCY 3189 16. Applications: Energy Absorption in Foams jq0jsHapHH0 3190 Thank You to our YouTube Subscribers! XUM4lLbG5UY 3191 About MIT OpenCourseWare eSRLIYaPPA0 3192 MIT Undergraduate Curriculum Map and OCW RE5PmdGNgj0 3193 2.11.1 Stable Matching: Video Sdw8_0RDZuw 3194 2.6.1 DAGs: Video e-yQFC6dACA 3195 4.2.5 Bayes' Theorem: Video CAKSh3M0y8k 3196 2.2.3 Inverses mod n: Video HswnmlLPGZ4 3197 3.4.3 Two Pair Poker Hands: Video K8ZfzNN1miQ 3198 1.8.6 WOP vs Induction: Video [optional] KFcodn4qfrQ 3199 4.5.9 Linearity of Expectation: Video L2yOSFsMvnc 3200 4.4.4 Random Variables: Uniform & Binomial: Video Mhip1rljvRo 3201 1.6.2 Sets Operations: Video gFD1Lp6zK3w 3202 1.7.3 Relational Mappings: Video iZX8WEGZTVw 3203 4.8.2 Stationary Distributions: Video mqoDXWrSais 3204 4.5.5 Total Expectation: Video -yo3YxfY47g 3205 4.7.1 Law Of Large Numbers: Video 5hETv64GIuE 3206 1.11.9 Russell's Paradox: Video 5wCZqdCDafc 3207 2.9.4 k-Connectivity: Video Amd_bNYzgUw 3208 4.1.5 Sample Spaces: Video CpW0ZJ7i0oc 3209 1.2.1 Proof by Contradiction D3E5CKebKuQ 3210 1.8.2 Bogus Induction: Video D9l-pIg1Ayo 3211 4.5.3 Expected Number Of Heads: Video YVQdVzSkcmQ 3212 4.5.1 Expectation: Video ZEsk64C0fJg 3213 2.10.1 Trees: Video _3WDzxt5p8c 3214 1.4.4 Truth Tables: Video _RqqzyWDVMA 3215 2.10.5 Spanning Trees: Video fV3v6qQ3w4A 3216 1.3.1 Well Ordering Principle 1: Video fpy5Hsz5t6E 3217 1.7.5 Finite Cardinality: Video juGgfHsO-xM 3218 3.4.5 Multinomial Theorem: Video n0lce1dMAh8 3219 3.3.3 Counting with Bijections: Video v6axtBS6IF8 3220 3.1.1 Arithmetic Sums: Video EegG5TPL29c 3221 3.1.7 Integral Method: Video HeyEK0TWiBw 3222 3.2.3 Asymptotic Properties: Video MX-mBxt6huU 3223 2.5.1 Digraphs: Walks & Paths: Video Q-6Cw8tYVeY 3224 4.7.7 Sampling & Confidence: Video VJzv6WJTtNc 3225 4.4.2 Random Variables: Independence: Video jwjDj4GoSV0 3226 3.4.4 Binomial Theorem: Video tOsdeaYDCMk 3227 1.10.7 Recursive Functions: Video yzKPotFLfsc 3228 2.1.4 Pulverizer: Video 0w9luYcxHrw 3229 2.7.1 Partial Orders: Video AipSRi3CyLg 3230 1.11.3 Countable Sets: Video CWkh5kb4TGc 3231 3.2.1 Asymptotic Notation: Video CdhuVhWTSMI 3232 3.1.5 Book Stacking: Video FkfsmwAtDdY 3233 1.7.1 Relations: Video HZLKDC9OSaQ 3234 2.11.7 Bipartite Matching a7JUH-EtHtI 3235 1.9.3 Derived Variables: Video eMWG-jTh-GE 3236 1.4.3 Digital Logic: Video hNrtGiCFPGs 3237 1.3.5 Well Ordering Principle 3: Video hVerxuP4cFg 3238 2.8.3 Isomorphism: Video lU_QT5GSuxI 3239 3.1.9 Stirling's Formula: Video m07lrb7m0D0 3240 4.6.3 Markov Bounds: Video 1TpzSCMLg08 3241 2.6.3 Scheduling: Video 1vQ2x5O_xqk 3242 4.3.1 Independence: Video 6vgHIImFwHo 3243 2.11.2 Matching Ritual: Video BEAv82FinM0 3244 4.2.7 Monty Hall Problem: Video Dqx56lZ_icg 3245 4.5.7 Mean Time to Failure: Video F3y8qupFfUs 3246 4.2.3 Law of Total Probability: Video QKO_2WQkZ0k 3247 4.8.3 Page Rank: Video QsKtEuUyIdw 3248 2.1.7 Prime Factorization: Video TIpnudrzvgg 3249 2.8.1 Degree: Video UroprmQHTLc 3250 1.5.1 Predicate Logic 1: Video cUYTlKA8jaw 3251 2.6.5 Time versus Processors: Video nwpzBE9IwJQ 3252 3.5.4 Inclusion-Exclusion 2 Sets: Video BH4qlkYCLW0 3253 4.4.1 Bigger Number Game: Video Cu9_LaaWgHo 3254 4.2.1 Conditional Probability Definitions: Video TXNXT3oBROw 3255 1.10.1 Recursive Data: Video WQHOImO0pX0 3256 1.11.7 The Halting Problem: Video [Optional] bHvMYZvZp7Y 3257 2.7.3 Representing Partial Orders As Subset Relations: Video c3qNBNl1h8g 3258 2.1.6 Revisiting Die Hard: Video et3FOZdI6pk 3259 2.1.1 GCDs & Linear Combinations: Video iDfyX8WRIyM 3260 3.4.1 Generalized Counting Rules: Video s-E5T3igntw 3261 2.7.4 Equivalence Relations: Video uaa4P-kkLrA 3262 4.6.5 Chebyshev Bounds: Video zcvsyL7GtH4 3263 1.11.11 Set Theory Axioms: Video [Optional] ALn1McUXg-c 3264 4.6.1 Deviation From The Mean: Video I1HpgnWQI7I 3265 1.3.3 Well Ordering Principle 2: Video KZ7jjLTQ9r4 3266 1.6.1 Sets Definitions: Video KvtLWgCTwn4 3267 2.2.1 Congruence mod n: Video L30HPgryd6I 3268 4.1.3 Simplified Monty Hall Tree: Video Penh4mv5gAg 3269 2.9.1 Coloring: Video TeRYL7kkhqs 3270 2.3.1 Modular Exponentiation Euler's Function: Video i5AWE-OoOsY 3271 2.11.9 Hall's Theorem wJzBU7Do1ls 3272 4.3.3 Mutual Independence: Video 4dj1ogUwTEM 3273 1.11.4 Cantor's Theorem: Video n4KKgKpp--0 3274 2.11.5 Optimal Stable Matching: Video yTrtVwKZkwU 3275 3.3.1 Sum And Product Rules: Video QzSCf62kzjE 3276 1.11.1 Cardinality: Video TIQ3xN38jgM 3277 2.9.3 Connectivity: Video dW0f62lcCLE 3278 2.1.2 Euclidean Algorithm: Video dZgI16nMuqE 3279 2.3.3 The Ring Z: Video o57CTwt1-ck 3280 4.6.7 Variance: Video L5uBeAGJV1k 3281 1.5.4 Predicate Logic 3: Video TUueMeRooBk 3282 1.8.4 Strong Induction: Video ZDQk45NQbEo 3283 3.1.3 Geometric Sums: Video 0exBzsexUoI 3284 1.4.1 Propositional Operators: Video vzpFQ3uNyPo 3285 1.2.3 Proof by Cases yWIQCewgfwY 3286 2.4.3 Reducing Factoring To SAT: Video GyFVgJZ0hIs 3287 1.1.2 Intro to Proofs: Part 1 -j7MoM3P_J8 3288 4.8.1 Random Walks: Video 4Dz4vNUxnZM 3289 3.5.1 The Pigeonhole Principle: Video VWIDwHCGJDQ 3290 1.10.4 Structural Induction: Video 51-b2mgZVNY 3291 3.5.3 Inclusion-Exclusion Example: Video MMn7q1M7pGI 3292 4.7.3 Independent Sampling Theorem: Video QORX1OUabio 3293 2.5.3 Digraphs: Connected Vertices: Video T1AtlGrCoU8 3294 1.5.2 Predicate Logic 2: Video TWVntUfXsKs 3295 4.7.5 Birthday Matching: Video VuG2JNcRXYg 3296 1.9.1 State Machines Invariants: Video dEsFEK4vnV4 3297 4.1.1 Tree Model: Video g2mOvmC1TKc 3298 2.10.3 Tree Coloring: Video hxp4fbQpico 3299 2.9.2 State Machines Invariants: Video wIq4CssPoO0 3300 1.1.1 Welcome to 6.042 XnV8GAuAqJM 3301 1.8.1 Induction: Video Y9Blo_G-Mvg 3302 3.2.6 Asymptotic Blunders ZUZ8VbX1YNQ 3303 2.4.1 RSA Public Key Encryption: Video wfr4XbR5VP8 3304 1.1.3 Intro to Proofs: Part 2 VUgN-YEklTU 3305 Random Incidence Under Erlang Arrivals DkOgvZywshI 3306 ODE45 Mva9UIz_wwA 3307 Classical Runge-Kutta, ODE4 ScZMBOB_qYQ 3308 Estimating Error, ODE23 cQKR5m5pTTg 3309 The MATLAB ODE Suite gwmIksA7aXM 3310 Stiffness, ODE23s, ODE15s 6O9D6am_RK4 3311 Order, Naming Conventions NNhVVk244ZA 3312 Systems of Equations Q_f1vRLAENA 3313 Lorenz Attractor and Chaos 3vKlYA7vXOk 3314 Session 3, Part 2: Financial Projections 9upRT5T7drI 3315 Session 3, Part 1: Financing Sources Panel Azq6S6Hx0gU 3316 Session 2, Part 1: Marketing and Sales ZcPNcoTbkIU 3317 Session 1, Part 1: Introduction and Overview of Business Plans Lau7bwQAWr4 3318 Session 1, Part 2: Refining and Presenting Your Venture Idea b9Yyj3htBLE 3319 Session 2, Part 2: Business Models sfYD3LX-Rgw 3320 Session 4, Part 2: Legal Issues 5GEKCOhiqro 3321 Inspiration for the Developing the Course Lm8WHM0glHE 3322 The Role of Fun in Research, Teaching, and Learning c5Myaxq44mI 3323 Students Scribing Lecture Notes iDNpHHO_O6w 3324 Using a Survey to Get to Know Students tkU8_LJGCvE 3325 Course Iteration EMyRV3H4Vf4 3326 Collaboration as a Problem-Solving Approach KdN2mQ594t0 3327 Final Projects rLOVwqMKlBc 3328 Inviting Students to Solve Open Problems fRWCYq5qxL4 3329 Listening for Success: The Importance of Audio Files g7frRgUhmeU 3330 Motivating Students jBNVKat3GoQ 3331 When Students Struggle, Ask Them to Show You How They Prepare 8UbNWSx41Y4 3332 「聽說領先，讀寫跟上」 / 「听说领先，读写跟上」 (Speaking and Listening be... hNUoYTJl3j4 3333 Daily Grading System oUIGRmcnUtA 3334 Speaking and Listening before Reading and Writing pVJ6E-jUeb0 3335 Meet the Educator uskl5IFNM64 3336 Creating an Immersive Classroom Environment zGx0aFh8oxk 3337 Cultivating Cultural Competence 1ZSJvvCcwzw 3338 自發學習 / 自发学习 (Motivating Students ) 8_9C0_xw0KI 3339 全中文的學習環境 / 全中文的学习环境 (Creating an Immersive Classroom Environment) akxeQg1WaRQ 3340 每日評分 (Daily Grading System) dp7gVBLm0OI 3341 個別指導 / 个别指导 (When Students Struggle, Ask Them to Show You How They Prepare) pYrkksIQAnE 3342 使用聽力強化中文學習 / 使用听力强化中文学习 (Listening for Success: The Impo... FkZtE9qCk-A 3343 語言與文化的關聯 / 语言与文化的关联 (Cultivating Cultural Competence ) 6lsGKRj7Yzg 3344 Thank you to the 2016 OCW Spring Challenge Donors k9wV8OIv5Qg 3345 Q & A with MIT Professor John Guttag eHZifpgyH_4 3346 16. Complexity: P, NP, NP-completeness, Reductions 4q-jmGrmxKs 3347 18. Complexity: Fixed-Parameter Algorithms zNGKX-4PRsk 3348 0. Introduction 2DDjHvH8d2k 3349 3. Examples Demonstration 0cmj5TfFCLY 3350 Demonstration 7 4StlYd7xKFA 3351 7. Examples Demonstration KXJVqsbh_4Y 3352 1. Using Associative Arrays P5SjikeOHr0 3353 0. Examples Demonstration mbr667kATEg 3354 5. Perfect Power Law Graphs -- Generation, Sampling, Construction, and Fitting pHOPafutFSo 3355 3. Entity Analysis in Unstructured Data 5RqTJWf1l_A 3356 1. Examples Demonstration ADQck0zeBLQ 3357 6. Examples Demonstration hMUpevQzNzY 3358 6. Bio Sequence Cross Correlation moJ7TQb5Fuk 3359 4. Examples Demonstration tUk8o-ZbF4c 3360 2. Group Theory zkcj6JrhGy8 3361 4. Analysis of Structured Data MTakzGAhYvo 3362 7. Kronecker Graphs, Data Generation, and Performance R6-LQbqUCI0 3363 5. Examples Demonstration WkYdi40yNwY 3364 2. Examples Demonstration lWe1rYtlsJY 3365 Feedback from Dr. K, an OCW fan cN1mjMQyPBw 3366 Donate to OCW today and celebrate 15 years of open sharing U6fI3brP8V4 3367 Lecture 2: Experimental Facts of Life aW-e04zwTnc 3368 Euler, ODE1 zrFJKy5l_PY 3369 Predator-Prey Equations 6b9AW6QxXt0 3370 Electrical Networks: Voltages and Currents ECslmuGlu-U 3371 Step Function and Delta Function SMQPt7t0bHk 3372 Second Order Equations with Damping qJOQOkJ7rI8 3373 Integrating Factor for a Varying Rate ttCKLZ2fWWE 3374 Tumbling Box x0Ap2kDsGRQ 3375 Midpoint Method, ODE2 RwBCrVB98s8 3376 Graphs VqXKa11IA6A 3377 Phase Plane Pictures: Source, Sink, Saddle kcLc4FsshO4 3378 Laplace Transform: Second Order Equation lL0oUZGMhXc 3379 Examples of Fourier Series o93axeQJqJ8 3380 Exponential Response – Possible Resonance CB9I4mwpQ5E 3381 Response to Exponential Input E97SZm2ZrBo 3382 Boundary Conditions Replace Initial Conditions GAOjfd5QJZE 3383 Eigenvalues and Stability: 2 by 2 Matrix, A LKMGo8G7-vk 3384 Similar Matrices MJUjSKew4nQ 3385 Integrating Factor for Constant Rate N6pc8Axv3Gs 3386 Linearization of two nonlinear equations NmntYoB1uJg 3387 The Stability and Instability of Steady States U8R54zOTVLw 3388 Diagonalizing a Matrix _FATUw506mE 3389 Separable Equations ggWYkes-n6E 3390 The Big Picture of Linear Algebra n98ilenWoak 3391 The Column Space of a Matrix n9H-6TQIEJc 3392 Phase Plane Pictures: Spirals and Centers nGKeHq_kRQA 3393 Incidence Matrices of Graphs ojUQk_GNQbQ 3394 Positive Definite Matrices xw3ccgYhFis 3395 Response to Oscillating Input zkFZY6esNOU 3396 Forced Harmonic Motion zqks_JcU0cM 3397 Unforced Damped Motion 0hx59wYpFyY 3398 Linearization at Critical Points 9RJml41PFnc 3399 Laplace Transform: First Order Equation Ku2zZ5Vfpzo 3400 Second Order Systems PoHO4PZtW78 3401 Impulse Response and Step Response f0BxAtprWts 3402 The Calculus You Need -D4GDdxJrpg 3403 Laplace Equation Jy5XpZqy56U 3404 The Tumbling Box in 3-D TCkLSYxx21c 3405 The Logistic Equation ghjOS7Q82s0 3406 Overview of Differential Equations i8rnEl8O-r0 3407 Heat Equation vA9dfINW4Rg 3408 Fourier Series ZTNniGvY5IQ 3409 Symmetric Matrices, Real Eigenvalues, Orthogonal Eigenvectors cDfWtSqGiBY 3410 Pictures of Solutions eeMJg4uI7o0 3411 Independence, Basis, and Dimension fd7ioT_wwPE 3412 Two First Order Equations: Stability iVlHPDER0FA 3413 Solving Linear Systems 9TQCKWWAVjM 3414 Wave Equation DzqE7tj7eIM 3415 Eigenvalues and Eigenvectors WWphCZkdByA 3416 Fourier Series Solution of Laplace's Equation mBcLRGuAFUk 3417 Singular Value Decomposition (the SVD) u_XsCvhzzbg 3418 An Example of Undetermined Coefficients 0f15AVSQ770 3419 Variation of Parameters 0r2L3wTqkBc 3420 Solution for Any Input LwSk9M5lJx4 3421 The Matrix Exponential WZMQdLW4COQ 3422 Laplace Transforms and Convolution kIT2uMxYh6M 3423 Response to Complex Exponential mKYlNJhK_2o 3424 Method of Undetermined Coefficients xCCeV-glFdM 3425 Second Order Equations xtMzTXHO_zA 3426 Powers of Matrices and Markov Matrices ZvL88xqYSak 3427 Gilbert and Cleve Introduction uXt8qF2Zzfo 3428 12a: Neural Nets VrMHA3yX_QI 3429 12b: Deep Neural Nets nBDFbsq10To 3430 Thank You for 15 Years of Open Sharing WsEPhUu8kKU 3431 17. Jean Renoir and Poetic Realism kvbLY2mQW1k 3432 The Film Experience: A Course in Transition nIMlZ8ErLfs 3433 Thematic Spines of the Course BgozyEIGsuc 3434 6. German Film, Murnau NOT1VZrNkMo 3435 7. The Studio Era gjnJf9jobb4 3436 Approach to Lecturing vtViG3o2mgg 3437 9. Alfred Hitchcock flAwb1TmOkQ 3438 21. Truffaut, the Nouvelle Vague, The 400 Blows e0pgB4jWUjA 3439 Why Study Film? ilM34q8F6rY 3440 8. The Work of Movies; Capra & Hawks r8quwPWwurA 3441 Meet the Educator tg_1R6CDIa0 3442 Beyond Film: Television & Literature xt_0iNlUQ2U 3443 10. Shadow of a Doubt, Rear Window eO3RNUAFtDE 3444 18. Renoir's Grand Illusion (1937) lbtrbE_kK_Q 3445 23. Summary Perspectives - Film as Art and Artifact oocw6x_kCQs 3446 14. The Western (continued) r67dVaGtBGA 3447 5. Film as Global & Cultural Form; Montage, Mise en Scène wAojFJTmsxE 3448 13. The Western 6B8FySbsUsM 3449 22. Kurosawa and Rashomon lhKse0vIbqo 3450 The Video Lecture Conundrum mPCTR32vxWo 3451 11. The Musical tHttGDNmgKI 3452 12. The Musical (continued) BWLwSqLZd2o 3453 15. American Film in the 1970s, Part I (2007) HypQZfQPtYk 3454 20. Italian Neorealism, Part II (2007) LFOsw1Vccac 3455 1. Introduction to MIT 21L.011 The Film Experience (2007) j-F3Sy1nxPA 3456 16. American Film in the 1970s, Part II (2007) m4ZuXay_qOo 3457 3. Chaplin, Part I (2007) 0jWfHFBLnv0 3458 4. Chaplin, Part II (2007) Fq0mvAbzUrY 3459 19. Italian Neorealism, Part I (2007) vpJba2qIXjs 3460 2. Keaton (2007) -yfdG4BRFBY 3461 Becoming the Next Bill Nye 3MpzavN3Mco 3462 5. Amortization: Amortized Analysis G7mqtB6npfE 3463 R8. NP-Complete Problems MEz1J9wY2iM 3464 17. Complexity: Approximation Algorithms NzgFUwOaoIw 3465 11. Dynamic Programming: All-Pairs Shortest Paths krZI60lKPek 3466 R5. Dynamic Programming mUBmcbbJNf4 3467 19. Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees 09vU-wVwW3U 3468 R1. Matrix Multiplication and the Master Theorem xVka6z1hu-I 3469 9. Augmentation: Range Trees z0lJ2k0sl1g 3470 8. Randomization: Universal & Perfect Hashing 0CdxkgAjsDA 3471 R7. Network Flow and Matching QPk8MUtq5yA 3472 R4. Randomized Select and Randomized Quicksort cNB2lADK3_s 3473 6. Randomization: Matrix Multiply, Quicksort 9TNI2wHmaeI 3474 22. Cryptography: Encryption ZLOhV4XQ_tI 3475 R11. Cryptography: More Primitives KqqOXndnvic 3476 21. Cryptography: Hash Functions iTMn0Kt18tg 3477 3. Divide & Conquer: FFT tKwnms5iRBU 3478 12. Greedy Algorithms: Minimum Spanning Tree zM5MW5NKZJg 3479 R9. Approximation Algorithms: Traveling Salesman Problem 2P-yW7LQr08 3480 1. Course Overview, Interval Scheduling Tw1k46ywN6E 3481 10. Dynamic Programming: Advanced DP VYZGlgzr_As 3482 13. Incremental Improvement: Max Flow, Min Cut hmReJCupbNU 3483 4. Divide & Conquer: van Emde Boas Trees -QcPo_DWJk4 3484 R6. Greedy Algorithms WwMz2fJwUCg 3485 15. Linear Programming: LP, reductions, Simplex w_-SX4vR53M 3486 R10. Distributed Algorithms 8C_T4iTzPCU 3487 14. Incremental Improvement: Matching TOb1tuEZ2X4 3488 R2. 2-3 Trees and B-Trees U4x-hzhohB8 3489 Meet the Educator ojdXVFQfZPw 3490 Engaging Students 2g9OSRKJuzM 3491 7. Randomization: Skip Lists 2q7gqUuG_EA 3492 Co-Teaching the Course C6EWVBNCxsc 3493 24. Cache-Oblivious Algorithms: Searching & Sorting EzeYI7p9MjU 3494 2. Divide & Conquer: Convex Hull, Median Finding xnEZqVz7iy4 3495 On the Challenge of Assessing Students' Abiliites to Apply Algorithms in New and Creative Ways z_QOKNpEVro 3496 On Teaching Complex Content EUnGZoBa3nc 3497 1. Emergence of Gravity eGPpz9kYUCg 3498 19. Mass-dimension Relation jhyWwA_bJ5A 3499 11. String Theory in the Light-cone Gauge 1LEYgS8Wzsk 3500 16. Geometry of D-branes and AdS / CFT Conjecture _75zfIar62c 3501 24. Holographic Entanglement Entropy iPWIqjYkVns 3502 13. Physics of D-branes, Part I oXsC9bjMJA4 3503 21. Euclidean Correlation Functions: Higher-point Functions 14_8tzAd1rA 3504 7. Structure of Large N Expansion 1OGZCt58GLc 3505 20. Euclidean Correlation Functions: Two-point Functions 1pkoBetgo7s 3506 6. Holographic Principle WPuDh61Lkpg 3507 22. Computation of the Wilson Loop gLYwLyeE8oU 3508 4. Physical Interpretation of Black Hole Temperature -mrxN8XcQOQ 3509 15. Physics of D-branes, Part III LTEtH1gzwoE 3510 3. Causal Structure of a Black Hole and Black Hole Temperature LoIXB2GJHkg 3511 8. Large N Expansion as a String Theory, Part I hIvrYfwUyZQ 3512 5. Black Hole Thermodynamics k6HCdJ9lKho 3513 14. Physics of D-branes, Part II 0fChZwU1zEc 3514 17. More on AdS / CFT Duality M_8UajiNlDg 3515 9. Large N Expansion as a String Theory, Part II Wcy-zCt8llk 3516 12. String Spectrum and Graviton owhNn20aZo8 3517 10. Basics of String Theory and Light-cone Gauge raP-0nqnF_A 3518 23. Duality at a Finite Temperature and Finite Chemical Potential WVOIk8en6YE 3519 2. Classical Black Hole Geometry nW4vp_upvmE 3520 18. General Aspects of the Duality VBgVRviSKek 3521 Day 1: Identity and Genre; Part 1 a9Zo4rqL5Mc 3522 Teaching Reflection: Day 6 6v_Aj0EkdZM 3523 Teaching Reflection: Day 11 ILiokEbMqr4 3524 Teaching Reflection: Day 2 awiBfhYl5mY 3525 Teaching Reflection: Day 4 shyN9JFhkpg 3526 Teaching Reflection: Day 1 02NyrrxEGqM 3527 Day 5: Storyteller’s Toolkit Pt. III: Visual Storytelling & Realizing Vision; Part 4 553n_ovfN-o 3528 Teaching Reflection: Day 7 & 8 d9TA4nITTp8 3529 Teaching Reflection: Day 5 rCG6r6gotZQ 3530 Day 2: STEM Nuggets; Part 1 x_DGTWH4tEA 3531 Teaching Reflection: Day 3 2z33hyYG6Js 3532 Instructor Interview: Workshops 3HnHQXWIFd4 3533 Day 4: Storyteller’s Toolkit Pt. II: Visual Storytelling; Part 1: Animation CbDsSQEvEkA 3534 Instructor Interview: Inspiration for the Course and Intended Learning Outcomes iR6FUYCNi5A 3535 Day 10: Project Time; Part 1: Animation 17uL1VoaWTQ 3536 Day 1: Identity and Genre; Part 2 KKj4FAMF1Bk 3537 Student Interview: Joshua Cheong MTxjpJSp43A 3538 Instructor Interview: A Class on Pre-Production 3ha4ROyWr9Q 3539 Instructor Interview: Digital Media Literacy Ui2q2uoA-_g 3540 Day 2: STEM Nuggets; Part 2 YzUx6j3Qv4I 3541 Instructor Interview: Teaching as a Team kQnA60blp6o 3542 Day 10: Project Time; Part 2: Rough Cuts rt3EMeJ0lDQ 3543 Instructor Interview: Assessment and Feedback in Creative Contexts 6lUGb3VIPmY 3544 Day 3: Storyteller’s Toolkit Pt. I: Verbal Storytelling/Writing for the Spoken Word; Part 2 XDBr39cwmbg 3545 Day 6: Table-Read / Office Hours aHygKFodPKg 3546 Day 1: Identity and Genre; Part 3 AjK2zF9yN0k 3547 Day 3: Storyteller’s Toolkit Pt. I: Verbal Storytelling/Writing for the Spoken Word; Part 1 BZfqcnlpofI 3548 Day 5: Storyteller’s Toolkit Pt. III: Visual Storytelling & Realizing Vision; Part 2 VQi6t2NfWig 3549 Day 11: Screening (Rough Cuts) bhGIdWQqUYw 3550 Student Interview: Nathan Hernandez and Andrea Desrosiers ftrKlCmELm4 3551 Day 5: Storyteller’s Toolkit Pt. III: Visual Storytelling & Realizing Vision; Part 3 3coxJFCY3T4 3552 Student Interview: Kenneth Cheah Docl3KOqnHI 3553 Day 7: Table Read / Post-Production; Part 2: Post-Production VHyCh1mDneE 3554 Day 4: Storyteller’s Toolkit Pt. II: Visual Storytelling; Part 2: Storyboarding gUNY29Zpu7g 3555 Day 5: Storyteller’s Toolkit Pt. III: Visual Storytelling & Realizing Vision; Part 1 ViSVJJoo7nE 3556 Day 2: STEM Nuggets; Part 3 ZMe7jSsPmW4 3557 Day 7: Table-read / Post-production; Part 1: Table-read gb80yhA2o4A 3558 Student Interview: Yuliya Klochan qkkI9Z9tKvo 3559 Day 13: Screening (Final Cuts) oCk2LZwRU0s 3560 Interview with Lara Baladi V5lJj6VAKmg 3561 Gamification & Us: Promises and Challenges of a Gameful World qnGoJKxNTtE 3562 OCW Educator: Sharing teaching approaches and materials from MIT with educators everywhere, for free -56G36H8BvY 3563 Instructor Interview: Teaching Heritage Learners in a Streamlined Language Course 4afZKY-INNA 3564 Instructor Interview: Incorporating Authentic Text Going Forward 9RZa3zBruVA 3565 Instructor Interview: Philosophical Approach to Language Teaching FtIdQUcZlWU 3566 Instructor Interview: Assessing Students’ Language Learning M_gQolc3clM 3567 Instructor Interview: Meet the Instructor QLVFxgVpg1w 3568 評量學生的語言學習 / 评量学生的语言学习 bH4L4Nv_PeA 3569 Instructor Interview: Teaching with Lingt Technology -laccUOh92k 3570 中文快班的教學哲學 / 中文快班的教学哲学 6W-ZKWuK4oM 3571 未來教材的更新與展望 / 未来教材的更新与展望 NDclHOywqB4 3572 教導具華語基礎的學生 / 教导具华语基础的学生 Vd2xO_nF1gg 3573 使用Lingt於課堂教學 / 使用Lingt于课堂教学 itLh_yWsOX0 3574 Harpsichord Demonstration _DbUa8w0W74 3575 Instructor Interview: Course History 0IF8oBg_Zd8 3576 Instructor Interview: Making Learning Public EmwHY7Ibu9k 3577 Instructor Interview: Learning about being an Educator UswuSLKQVK4 3578 Instructor Interview: Teaching Students to Learn from Failure Wup3xqOvvpA 3579 Instructor Interview: Collaborating with Clients EWjWv1YBB7A 3580 28-30. Mid-Semester Presentations K67ojX4-PL8 3581 Instructor Interview: The Role of Mentors ZGCJabWew3A 3582 Instructor Interview: Advice for Educators ZjLZ_P8svSY 3583 Instructor Interview: Assessing Students' Learning yqrQ9dKPV78 3584 Instructor Interview: Meet the Educators 6Vea2rZOA3k 3585 Student Interview: Team Chris 9r3067S3Dm0 3586 Student Interview: Team Beverly Ann kJEwyrLHZoQ 3587 Student Interview: Team Aaron x18bMLW4eO4 3588 53. Final Presentations 4HP37G4v3S8 3589 Instructor Interview: Postmortem Analysis RY0X1oEQbb0 3590 Instructor Introduction: Philip Tan 8TPJUR378f0 3591 Instructor Introduction: Andrew Haydn Grant B3_z1qTD2ZE 3592 Instructor Interview: Teaching the Iterative Process HpeJ1h0V1RE 3593 Instructor Interview: Assessing Students' Projects Od21y3eAwUo 3594 Student Interview: Lauren Merriman T0GdXZusbKI 3595 Instructor Interview: Advice for Educators CrS0ndCbsro 3596 Instructor Interview: Refining the Course HpACiptk990 3597 Instructor Introduction: Richard Eberhardt Y7cMih9O8es 3598 Instructor Interview: Teaching Students How to Solve Creative Problems as Teams bgMZSJ2rfNc 3599 Student Interview: Tej Chajed bhk8Wtgpb1w 3600 Instructor Introduction: Sara Verrilli uX-D5Q_5v4A 3601 Student Interview: Matthew Susskind cBoUvyAaEUY 3602 Instructor Interview: Fostering Diversity of Voices lyR4HQ01nos 3603 Instructor Interview: Sequencing Learning Experiences Ey_eWZhG8vI 3604 19. Working with Sound Designers (Guest Lecture by Richard Ludlow and Andy Forsberg) lxpXowuUdKw 3605 From Pitch to Product: The Development of Hello Waves -3ixsZ7fBUI 3606 Student Interview: Miriam Prosnitz J4pnlCBTJYc 3607 11. Guest Lecture (EA) on Development and Best Practices j8ZGpRo8jd4 3608 2. Project 1, Low Fidelity Prototyping nrfl6GAQy2s 3609 6. Agile Project Management s8At7cnDelQ 3610 15. Guest Lecture (Scot Osterweil of MIT Game Lab) 9is-GrNpNvA 3611 12. Project 3 Presentations, Project 4 Introduction (Small Game Project) B1zWyyNoRq8 3612 9. Guest Lecture with SWERY of Access Games SSnV-2uWG9w 3613 18. Fiction and Narrative in Video Games Ya8wC2rNQK0 3614 22. Cutting Features; Scope zaabQDKK8WY 3615 25. Getting Players to Your Game (Guest Lecture by Sean Baptiste) -SHXUwpVgXU 3616 10. UI and Usability 0teK9aXB0GI 3617 14. Aesthetics 2pfdTSZ-GUM 3618 3. Game Engines 5wHMEQkFzvE 3619 20. Writing in Games (Guest Lecture by Heather Albano and Laura Baldwin) ok4qM1OzlPA 3620 26. Final Presentation Rehearsals pfDfriSjFbY 3621 1. Introduction (CMS.611J Creating Video Games) SODYb6YPPLk 3622 23. Team Discussions UxMpn92vGXs 3623 5. Agile Software Development __knqdOcWTM 3624 24. Running a Game Studio (Guest Lecture by Michael Carriere and Jenna Hoffstein) dE-QgdrtzHw 3625 4. Project 2, Digital Prototype with Project Management gQHbZlo4Exo 3626 17. Working with Artists (Guest Lecture by Luigi Guatieri) MZSnYgdlV0A 3627 8. Project 2 Presentations, Project 3 (Digital Prototype II: User Interface) WLjo-mDBiDg 3628 Client Interview: Pablo Suarez jbhbJBtS48w 3629 Student Interview: Lenny Martinez xQANWfUYeNg 3630 7. Testing and Guest Lecture with Genevieve Conley of Riot Games zzKSn1Y80F4 3631 13. Serious Games, Simulation and Abstraction Av9sFr_NsBU 3632 16. Team Dynamics sKolTx6sxUo 3633 27. Final Presentations 8woIHrY6eM0 3634 8. Kinetic Theory of Gases Part 2 A0owfH3UERI 3635 Lecture 10: Green Supply Chain Strategy HMM2PKQ-VDQ 3636 Lecture 9: International Regulations and Supply Chains: The Case of Mercury OgpNXj2cEzA 3637 Lecture 4: Carbon Footprinting UBfckR8Ne5c 3638 Lecture 7: Multi-stakeholder Engagements e_Hpp8cgeRs 3639 Lecture 3: Reverse Logistics and Closing the Loop gpuvUU0Nl4k 3640 Lecture 5: Life Cycle Analysis TZSBHuy8yhQ 3641 3. 3-Partition II FXxpkucTR2E 3642 2. Reducing the Danger of Nuclear Weapons and Proliferation clG-JuzTxrI 3643 1. South Asia Under the Shadow of Nuclear Weapons 6PxncdxIXNE 3644 Clonal Interference and the Distribution of Beneficial Mutations BJXCf6pFrhA 3645 Survival in Fluctuating Environments EFXjKHdbi6A 3646 Fitness Landscapes and Sequence Spaces TuXFwKrWQg8 3647 Life at Low Reynolds Number hfq1T9windg 3648 Synthetic Biology and Stability Analysis in the Toggle Switch lC3XSwQ62iw 3649 Ecosystem Stability, Critical Transitions, and Biodiversity 03bVGr-vYHQ 3650 Causes and Consequences of Stochastic Gene Expression KLrPm-BEEOI 3651 Evolution in Finite Populations NnDqJhtUqjw 3652 Graph Properties of Transcription Networks gc3O2sKIsX4 3653 Introduction to the Class and Overview of Topics xNNxlsY-F-s 3654 Oscillatory Genetic Networks zJTVMkGe8-8 3655 Feed-forward Loop Network Motif 3eIzIJ6QncY 3656 Dynamics of Populations in Space 9yGxpWVWYDY 3657 Microbial Evolution Experiments and Optimal Gene Circuit Design cT855rpX8bc 3658 Robustness and Bacterial Chemotaxis sJ7p2AuOYlA 3659 Autoregulation, Feedback and Bistability Cn5K8R8cEiI 3660 Parasites, the Evolution of Virulence and Sex WTesORG5H-A 3661 Interspecies Interactions a8Fbmj4nIxY 3662 Evolutionary Games dP4NQIpUH6w 3663 Introduction to Stochastic Gene Expression m41DWardioc 3664 The Neutral Theory of Ecology onL_UF4FLVM 3665 Robustness in Development and Pattern Formation EXBO08-78IU 3666 Stochastic Modeling lLY1u2aghIQ 3667 Input Function, Michaelis-Menten kinetics, and Cooperativity 7d73E1DiH0w 3668 1. Overview 28WhZvnvsAg 3669 11. Inapproximability Examples 42TnAE67iaE 3670 19. Unbounded Games PFfv1JnQB8Q 3671 8. Hamiltonicity R-0_0OQ2f4Y 3672 12. Gaps and PCP TUbfCY_8Dzs 3673 22. PPAD ccD0yAk1wL0 3674 17. Nondeterministic Constraint Logic snugEmWtEm4 3675 10. Inapproximabililty Overview x-Ik9YAFAPo 3676 4. SAT I ziViLYrf1Ak 3677 6. Circuit SAT KvBk_u8NNp4 3678 9. Graph Problems LHBc2mE71yc 3679 20. Undecidable and P-Complete P3YoIxiz6to 3680 13. W Hierarchy ZaSMm2xvatw 3681 2. 3-Partition I aDmFyu0Yt7s 3682 18. 0- and 2-Player Games Ih0cPR745fM 3683 23. PPAD Reductions X05j49pc6DE 3684 21. 3SUM and APSP Hardness XROTP1RiNaA 3685 15. #P and ASP ctxnYDAIDO4 3686 14. ETH and Planar FPT e10dswn-grA 3687 5. SAT Reductions ogbjia9gp34 3688 16. NP and PSPACE Video Games KU8I8LjnQgE 3689 7. Planar SAT GqmQg-cszw4 3690 1. Introduction, Threat Models QOtA76ga_fY 3691 13. Network Protocols yRVZPvHYHzw 3692 10. Symbolic Execution cOArT0rpiVg 3693 OCW Scholar Wisdom by Obi-Six OCW kGkF6flOwb8 3694 OCW Scholar Wisdom by Obi-Five OCW 3me_PJvOOxs 3695 OCW Scholar Wisdom by Obi-Four OCW r2sFNLx3ohQ 3696 OCW Scholar Wisdom by Obi-Three OCW e_POJZfQZPg 3697 OCW Scholar Wisdom by Obi-Two OCW guW98--0D74 3698 OCW Scholar Wisdom by Obi-One OCW 7v-YVpGxTtc 3699 MIT OpenCourseWare Gift Challenge - Thank You! LCoPLFaeq0U 3700 Basic Strategy IZZ4y5GfdOU 3701 Poker Economics JQSTRkGEiWw 3702 Tournament Play MnbQjpejZt4 3703 Game Theory OTkq4OsG_Yc 3704 Introduction to Poker Theory tXVDY1HvrVU 3705 Analytical Techniques tssNDp5I6zA 3706 Preflop Analysis kn92WXcKr0M 3707 Decision Making 2MaQKFHqYBw 3708 1. Collective Behavior, from Particles to Fields Part 1 WtGS6lV5MDI 3709 8. The Scaling Hypothesis Part 3 bQ-miBkhy9M 3710 14. Position Space Renormalization Group, Part 2 h_YZxQJpPv0 3711 4. The Landau-Ginzburg Approach Part 3 iecno1uInk8 3712 23. Continuous Spins at Low Temperatures Part 4 opL7d8vY0KA 3713 20. Continuous Spins at Low Temperatures Part 1 00PK6cUCbnU 3714 9. Perturbative Renormalization Group Part 1 1_dMnMLbIok 3715 13. Position Space Renormalization Group, Part 1 9WhnbTT_nS8 3716 5. The Landau-Ginzburg Approach Part 4 NLKJdcb1E5I 3717 6. The Scaling Hypothesis Part 1 bMnpf0s-mAk 3718 15. Series Expansions Part 1 xtgygDYTKM0 3719 10. Perturbative Renormalization Group Part 2 y7sIuqgADgc 3720 16. Series Expansions Part 2 yBdXS5dXQN4 3721 18. Series Expansions Part 4 2Ep48LwBhAQ 3722 3. The Landau-Ginzburg Approach Part 2 6HrTfI8R_9A 3723 19. Series Expansions Part 5 DVRjcfMwAkk 3724 11. Perturbative Renormalization Group Part 3 fGUaxrIejr4 3725 7. The Scaling Hypothesis Part 2 vhLqp3eIkU4 3726 12. Perturbative Renormalization Group Part 4 MphmZC2o0aM 3727 21. Continuous Spins at Low Temperatures Part 2 XDpCdELStJs 3728 22. Continuous Spins at Low Temperatures Part 3 eKVr-oKxMPg 3729 2. Lec 1 (continued); The Landau-Ginzburg Approach Part 1 Lj8w7uWZWWA 3730 MIT OpenCourseWare Gift Challenge f9XFM8YLccg 3731 3. Probability Theory MxWZwTA_PHc 3732 Lecture Preparation 4d3RQs2JnKg 3733 Project Logistics and Support 6eEbSM3TafQ 3734 Faculty Introduction and Background U2DvFy2qM74 3735 Role of Images ZWdDKll8qZc 3736 Unique Aspects of the Course rjYk_5_oe6U 3737 Student Project Examples LhPZwdhutgU 3738 Octave/MATLAB® for Beginners, Part 1: Starting from Scratch NtMOab_nhs0 3739 Octave/MATLAB® for Beginners, Part 2: Fitting Data and Plotting WUxImdA7k8E 3740 Octave/MATLAB® for Beginners, Part 3: Cleaning Up & Saving Plots MVOJloovd18 3741 16. Atom-light Interactions V NOE2GDmSbDQ 3742 25. Coherence V TcvY8Nt0ZGA 3743 2. Resonance II zlaRnrjcjmw 3744 21. Two-photon Excitation II and Coherence I 4fZPNSMiRvk 3745 12. Atoms in External Fields IV and Atom-light Interactions I Fnsu19QD1D8 3746 20. Line Broadening IV and Two-photon Excitation I JFSRqIozgh0 3747 15. Atom-light Interactions IV OIis_b2bSVo 3748 18. Line Broadening II iwQ49oG-DO8 3749 1. Resonance I nSxRp52JkKY 3750 14. Atom-light Interactions III pQ10vZKnttA 3751 23. Coherence III zMlEb29UlKw 3752 10. Atoms in External Fields II EfuSYmCQSY8 3753 22. Coherence II Y7UsD2SNIIw 3754 24. Coherence IV hUVfj1XktGI 3755 9. Atoms V and Atoms in External Fields I jgSn1mB8uSI 3756 11. Atoms in External Fields III o3Oog9I25dA 3757 17. Atom-light Interactions VI and Line Broadening I ol2GRkRam4k 3758 8. Atoms IV vkka1O2H5h4 3759 6. Atoms II Lgqpoct9kk8 3760 5. Resonance V and Atoms I OMdGWyruixk 3761 4. Resonance IV gA1ZO0xBiYg 3762 7. Atoms III godnGvjmGZc 3763 19. Line Broadening III kWNv0-0tlAw 3764 13. Atom-light Interactions II r70MEz4cZFc 3765 3. Resonance III 5YmokPZWkaA 3766 CMS.611: Creating Video Games promo trailer dt4sSAb-7cE 3767 Proteins, levels of Structure, Non-covalent Forces, excerpt 2 | MIT 7.01SC Fundamentals of Biology H44LyNdIi5E 3768 25. Continuous Spins at Low Temperatures Part 5 Rv1UBrGVGFk 3769 24. Dissipative Dynamics PGnLAx8e4Gk 3770 26. Continuous Spins at Low Temperatures Part 6 5NB2Z6pZBNA 3771 Readings in Old and Middle English PdyARRNwi7I 3772 3. Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM) So6MK_FcP4E 3773 15. Gene Regulatory Networks iKLvCuFD1MA 3774 18. Analysis of Chromatin Structure 1EMonM7qAU8 3775 9. Modeling and Discovery of Sequence Motifs d5NMrA2HkG4 3776 10. Markov and Hidden Markov Models of Genomic and Protein Features kx_Hks_-SZM 3777 19. Discovering Quantitative Trait Loci (QTLs) lJzybEXmIj0 3778 1. Introduction to Computational and Systems Biology 14m9MW-qMhg 3779 4. Comparative Genomic Analysis of Gene Regulation 6ROBp57G2ZI 3780 12. Introduction to Protein Structure; Structure Comparison and Classification KYQ2dPW5nEU 3781 20. Human Genetics, SNPs, and Genome Wide Associate Studies MniYgsZSp30 3782 8. RNA-sequence Analysis: Expression, Isoforms Ob9xGBPvr_s 3783 7. ChIP-seq Analysis; DNA-protein Interactions P3ORBMon8aw 3784 5. Library Complexity and Short Read Alignment (Mapping) i59JDQ9hk10 3785 17. Logic Modeling of Cell Signaling Networks j1s9JfZKFqU 3786 13. Predicting Protein Structure kKyrR0cFrEg 3787 21. Synthetic Biology: From Parts to Modules to Therapeutic Systems kUN6rJ21Hno 3788 11. RNA Secondary Structure; Biological Functions and Predictions uD4-fOWeXAY 3789 22. Causality, Natural Computing, and Engineering Genomes 6Udqou3vmng 3790 2. Local Alignment (BLAST) and Statistics C95294_vvQY 3791 14. Predicting Protein Interactions RBPcKbEvK3U 3792 16. Protein Interaction Networks ZYW2AeDE6wU 3793 6. Genome Assembly aFx8dVLkrWs 3794 5. Second-Order Equations (continued) xvTYUnqn2wY 3795 4. Second-Order Equations Gp94Hph_-BU 3796 3. First-Order Equations (continued) 4X0SGGrXDiI 3797 2. First-Order Equations pPqI5LbC96Y 3798 Method of Simulated Moments (MSM) 7xJJU5HDCVE 3799 Maximum Likelihood Estimation and Confidence Intervals TuTmC8aOQJE 3800 5. Stochastic Processes I bKmcRfE3I6E 3801 26. Introduction to Counterparty Credit Risk cDlbEQz1PQk 3802 9. Volatility Modeling nmehlS-8b3Y 3803 13. Commodity Models uBeM1FUk4Ps 3804 8. Time Series Analysis I vc5dotshPZc 3805 25. Ross Recovery Theorem 8TJQhQ2GZ0Y 3806 16. Portfolio Management 92WaNz9mPeY 3807 7. Value At Risk (VAR) Models TnS8kI_KuJc 3808 19. Black-Scholes Formula, Risk-neutral Valuation Z5yRMMVUC5w 3809 18. Itō Calculus aga-Tak3c3M 3810 10. Regularized Pricing and Risk Models l1kLCrxL9Hk 3811 6. Regression Analysis qdbkvD4N-us 3812 21. Stochastic Differential Equations ywl3pq6yc54 3813 14. Portfolio Theory 55OXxe_ix2o 3814 23. Quanto Credit Hedging 9G1IDAqrWkg 3815 12. Time Series Analysis III 9YtmGy-wfE4 3816 2. Linear Algebra D2Jn1VrqjWI 3817 24. HJM Model for Interest Rates and Credit PPl-7_RL0Ko 3818 17. Stochastic Processes II _IFUfFuyQlU 3819 11. Time Series Analysis II eG_aRPy1KVE 3820 20. Option Price and Probability Duality ro07evEWbCE 3821 15. Factor Modeling wvXDB9dMdEo 3822 1. Introduction, Financial Terms and Concepts DyuQsaqXhwU 3823 Sample Class: Class 12--Bayesian Updating: Discrete Priors 7KOwsepQcXI 3824 HHMI Education Group Seminar: Flipping the Dice 4RX_lpoGRBg 3825 1. Thermodynamics Part 1 8kNP_VWmfFs 3826 23. Ideal Quantum Gases Part 2 EQB2Pw0lWRU 3827 2. Thermodynamics Part 2 JaEqS1ozlHY 3828 3. Thermodynamics Part 3 __tGxUu5BTc 3829 4. Thermodynamics Part 4 b1P0hurY6UE 3830 20. Quantum Statistical Mechanics Part 1 t7pTpwMjQ5I 3831 9. Kinetic Theory of Gases Part 3 ybCsMYk5xMg 3832 10. Kinetic Theory of Gases Part 4 34lmLIYpkYQ 3833 21. Quantum Statistical Mechanics Part 2 I_LcUur7quE 3834 6. Probability Part 2 QmV7FOXijMo 3835 11. Kinetic Theory of Gases Part 5 TDnfhpAZBqs 3836 16. Interacting Particles Part 2 TSjJlJJ2aoI 3837 17. Interacting Particles Part 3 Y59FgktB4uQ 3838 15. Interacting Particles Part 1 hRHzPaDpgu0 3839 22. Ideal Quantum Gases Part 1 l2Q31eoy_rY 3840 18. Interacting Particles Part 4 w_I0AkvbWFc 3841 5. Probability Part 1 6gMgNriK1Nk 3842 26. Ideal Quantum Gases Part 5 6rn4q9mv4jQ 3843 25. Ideal Quantum Gases Part 4 BhVyiU_dWps 3844 7. Kinetic Theory of Gases Part 1 Lt8FtWsq0q0 3845 13. Classical Statistical Mechanics Part 2 ckUyxmwaC5E 3846 12. Classical Statistical Mechanics Part 1 tCxonq5r-O8 3847 14. Classical Statistical Mechanics Part 3 FmylhZqFXNk 3848 24. Ideal Quantum Gases Part 3 hl4c1P9D8IY 3849 19. Interacting Particles Part 5 69H3kTwques 3850 Tutorial: Texturing qIJx2PRGKqw 3851 Tutorial: Solar Cell Operation k12GMjtN8aA 3852 Tutorial: Doping 20GlFVyxqHY 3853 Tutorial: Photoconductivity CAEyIum3cWI 3854 MIT Milestone Celebration | Highlights for High School Announcement -I-WA_kSkfA 3855 13. Review: The visual and oculomotor systems A0KpTR_Ujks 3856 22. Auditory cortex 1: Physiology and sound localization LJZi6CZafms 3857 11. The neural control of visually guided eye movements 2 M2KHrh_fCHE 3858 6. Adaptation and color TdOdc_n-ZCA 3859 2. Basic layout of the visual system and the retina g1ka1MXpo3s 3860 1. Introduction, the visual system jdiy_lV2xno 3861 14. Sound: External, middle and inner ears qubzQvNNaLI 3862 19. Descending systems and reflexes vPXTDpXwBs0 3863 9. Illusions and visual prosthesis -2d9XooPwHo 3864 18. Hearing loss; demo by Sheila Xu, cochlear implant user PXJvQGDyESc 3865 16. Auditory nerve; psychophysics of frequency resolution T9HYPlE8xzc 3866 3. The lateral geniculate nucleus and the visual cortex _ly5LmLte50 3867 8. Form perception n-NpJQgSLrk 3868 4. The ON and OFF channels oPb9AWMN2fY 3869 12. Motion perception and pursuit eye movements rGYhDvz066I 3870 7. Depth perception t4IA4GsLMEk 3871 15. Hair cells 9fL2zRnkDdQ 3872 17. Cochlear nucleus: Tonotopy, unit types and cell types A11axifKMtQ 3873 21. Sound localization 2: Superior olivary complex and IC OAOec-To-84 3874 23. Auditory cortex 2: Language; bats and echolocation Z937cqa--P8 3875 20. Sound localization 1: Psychophysics and neural circuits _XTuXlXav78 3876 5. The Midget and Parasol systems ezBuTFbF5Gs 3877 10. The neural control of visually guided eye movements 1 k7CqAVzhkoo 3878 Preview video: Making Science and Engineering Pictures: A Practical Guide to Presenting Your Work CzBufqJ5kME 3879 Instructor Interview: Teaching Design Thinking J1T7FwXryDE 3880 Instructor Interview: What Happens in Class? ET15GHDbbeA 3881 Instructor Interview: Online Student Forum KPWMFrMA52Y 3882 2. 10-Step Design Process and Dieter Ram (Sample Lecture) O5Vh5nCMMmA 3883 Instructor Interview: Grading a Design Course prmIRgNoexo 3884 Instructor Interview: Origins of This Course zY6Xf87GAyg 3885 3. Research and Stakeholder Analysis (Sample Lecture) 7nFDlFLDqWE 3886 Part 3: Reflected and Transmitted Light CzBtKHvaDr0 3887 How-To-Do-It: Sharpening OZzGlrEfM_0 3888 Part 2: Placing Devices on a Flatbed Scanner YrJKI6u5Eoo 3889 Part 1: Using a Flatbed Scanner fSv0tMKLqPw 3890 How-To-Do-It: Digitally Replacing a Background and More fW7-namlCT0 3891 Part 4: Enhancing the Scanned Image -Xwla4ZbWe8 3892 Lecture 17: Alexandrov's Theorem 2X9Tv1bF2UM 3893 Class 14: Hinged Dissections AxCavqjfy6w 3894 Lecture 4: Efficient Origami Design PuUPnAkcNog 3895 Lecture 12: Tensegrities & Carpenter's Rules SEyDJ2qMVl4 3896 Class 13: Locked Linkages _wctRwpa6j4 3897 Class 5: Tessellations & Modulars k2jKCJ8fhj0 3898 Lecture 11: Rigidity Theory usWjdV0-Jg0 3899 Lecture 15: General & Edge Unfolding yIjTCMlIgpU 3900 Class 3: Single-Vertex Crease Patterns ylQ5-9f5KIs 3901 Class 4: Efficient Origami Design 82t7g2itzm4 3902 Lecture 20: Protein Chains FEmDxtkee_0 3903 Class 1: Overview J2uMjEDsE6s 3904 Class 20: 3D Linkage Folding dLjCy6RmBN4 3905 Lecture 19: Refolding & Smooth Folding 3jZqCHtWV6o 3906 Class 10: Kempe's Universality Theorem 64Kp4kgRdzs 3907 Lecture 18: Gluing Algorithms 6GAq2w_HBUQ 3908 Lecture 2: Simple Folds Ao9qzPPfTJM 3909 Class 16: Vertex & Orthogonal Unfolding M8Jn9JdzoHU 3910 Lecture 5: Artistic Origami Design MDcAOTaCXHs 3911 Lecture 1: Overview PHy7iaX7rJU 3912 Class 6: Architectural Origami VQcvVx-niG4 3913 Lecture 7: Origami is Hard rfWCDzG4PWk 3914 Lecture 10: Kempe's Universality Theorem 6-Zh8U1RRK4 3915 Class 9: Pleat Folding 8RI9OSOftUE 3916 Lecture 21: HP Model & Interlocked Chains OznepAivkkg 3917 Class 17: D-Forms _OcgtpQvrVs 3918 Lecture 9: Pleat Folding nPyH0xPFjbE 3919 Class 19: Refolding & Kinetic Sculpture tnbzV-_pxbE 3920 Class 2: Univeresality & Simple Folds tzXIDPNb93Y 3921 Class 15: General & Edge Unfolding voMyQUarX-k 3922 Class 7: Origami is Hard wBR4Q6nFyqk 3923 Class 8: Fold & One Cut wPPf9S7IiAs 3924 Lecture 13: Locked Linkages yvatNaV6Bog 3925 Class 11: Generic Rigidity 2ylK_QUpJcQ 3926 Lecture 16: Vertex & Orthogonal Unfolding 5lO7gBJEzH4 3927 Lecture 3: Single-Vertex Crease Patterns 7RrVVji3pH8 3928 Class 12: Tensegrities K0GuKDSX1FA 3929 Lecture 8: Fold & One Cut ShvQYLXCjos 3930 Lecture 6: Architectural Origami kRD_u8AUlwk 3931 Lecture 14: Hinged Dissections -IWKPe6X6Vs 3932 Genetics and Statistics jwfeVqhqEB8 3933 Latent Heat -fhWuEt5yKc 3934 Gravity fv5QB3eK7jA 3935 Moments of Distributions gqBK3LVdyRw 3936 New Balance® visita de la planta, parte 1 -XKsFKIGjZ0 3937 New Balance® visita de la planta, parte 2 Qh3ZoZAzFT8 3938 New Balance® visita de la planta, parte 3 AnTwZVviXyY 3939 Introduction to System Dynamics: Overview e-OhjL2fNjQ 3940 Designing the Architect Agu68RGaoWM 3941 1. Introduction to Atomic Physics s83SihcFfYo 3942 2. QED Hamiltonian k7DskqekDZk 3943 3. Quantum description of light, Part 1 r6OUO3an7-0 3944 3. Quantum description of light, Part 2 QE-9hHvOles 3945 4. Non-classical light, squeezing, Part 1 zfBXJQ-i6p8 3946 4. Non-classical light, squeezing, Part 2 TJUXTASd0g0 3947 5. Single photons, Part 1 sYS3OCiLDzA 3948 5. Single photons, Part 2 8NiJSP-iE74 3949 6. Entangled states hmAp4ASxmKs 3950 7. Metrology, shot noise and Heisenberg limit, Part 1 A75xAGO3ZEY 3951 7. Metrology, shot noise and Heisenberg limit, Part 2 Ef1eG33K_V0 3952 8. g(2) for atoms and light D7APJXFJsbc 3953 9. Diagrams for light-atom interactions RjcU0OydPcE 3954 10. van der Waals and Casimir interactions q5iBqycJuqU 3955 11. Casimir force ZEmvTidO7k4 3956 12. Resonant interactions RITcQMokTJs 3957 13. Derivation of optical Bloch equations T1KLrKvCGbA 3958 14. Solutions of optical Bloch equations, Part 1 O92M9n8uIGY 3959 14. Solutions of optical Bloch equations, Part 2 vFmdogFFcko 3960 15. Unraveling Open System Quantum Dynamics vyDnTx4gTis 3961 16. Light forces, Part 1 r_fWDSikuNQ 3962 16. Light forces, Part 2 k0X7iSaPM38 3963 17. Dressed atom, Part 1 j8Wg9c9aWV8 3964 17. Dressed atom, Part 2 FU3P-vnGSZ0 3965 18. Techniques for ultralow temperatures Ih01TfuEfqU 3966 19. Bose gases O_zjGYvP4Ps 3967 20. Fermi gases, BEC-BCS crossover lJOuPmI--5c 3968 21. Ion trapping and quantum gates w20MA5SLBfk 3969 Lab 1: Introduction (21M.355 Musical Improvisation) ozWf4TDXvdk 3970 Concert Series 1: FiLmprov _SxMjq1_RrI 3971 7. "In a Silent Way" and student demonstrations s31hXhmhUws 3972 Concert Series 2: Natraj with guest Chitravina Ravikiran u9givSC2M8Y 3973 Guest Artist Workshop 2.1: Indian Classical Music qo-XkWeLWLs 3974 Guest Artist Workshop 2.2: Indian Classical Music student demonstrations PPDWaZPu7MU 3975 Guest Artist Workshop 3.1: Electronics ho1kCjRCjg8 3976 Concert Series 3: Neil Leonard and Robin Eubanks DD0VDr65wmo 3977 Guest Artist Workshop 3.2: Electronics student demonstrations _P1vVyKziWk 3978 12. Flexology student demonstrations qsEYV-yD0H0 3979 Guest Artist Workshop 4.1: Tim Ray and Eugene Friesen l5J-t5NcHuQ 3980 Concert Series 4: Tre Corda Posv6O0845c 3981 Guest Artist Workshop 4.2: Tim Ray and Greg Hopkins ANCN7vr9FVk 3982 1. Inflationary Cosmology: Is Our Universe Part of a Multiverse? Part I 4OinSH6sAUo 3983 2. Inflationary Cosmology: Is Our Universe Part of a Multiverse, Part II tJ2AJJMcQXs 3984 3. The Doppler Effect and Special Relativity wuPEmfon9lg 3985 4. The Kinematics of the Homogeneous Expanding Universe 45RQrWHzovU 3986 5. Cosmological Redshift and the Dynamics of Homogeneous Expansion, Part I vKLqWj0FRyc 3987 6. The Dynamics of Homogeneous Expansion, Part II m00PjHTq6jU 3988 7. The Dynamics of Homogeneous Expansion, Part III OtJFD9HNnoc 3989 8. The Dynamics of Homogeneous Expansion, Part IV U9n-Y_ZC-2M 3990 9. The Dynamics of Homogeneous Expansion, Part V YfbXB_MSkSY 3991 10. Introduction to Non-Euclidean Spaces ARuzDX55Xnk 3992 11. Non-Euclidean Spaces: Closed Universes dBhMcn7UDs0 3993 12. Non-Euclidean Spaces: Open Universes and the Spacetime Metric eUYIcR1VGns 3994 13. Non-Euclidean Spaces: Spacetime Metric and Geodesic Equation -yIKKST-_Mw 3995 14. The Geodesic Equation moyD_yeviMY 3996 15. Black-Body Radiation and the Early History of the Universe, Part I 6b83DypBeYg 3997 16. Black-Body Radiation and the Early History of the Universe, Part II KY91PsqCy_8 3998 17. Black-Body Radiation and the Early History of the Universe, Part III MKPswx4hjec 3999 18. Cosmic Microwave Background Spectrum and the Cosmological Constant, Part I U_Ot1PTuUv4 4000 19. The Cosmological Constant, Part II RgScJ20EnW8 4001 20. Supernovae Ia and Vacuum Energy Density PK1KNojfvMQ 4002 21. Problems of the Conventional (Non-inflationary) Hot Big Bang Model seBwiL9InII 4003 22. The Higgs Field and the Cosmological Magnetic Monopole Problem PsfyE1-s9Rs 4004 23. Inflation cFPnLqEms5k 4005 Lecture 14: Resonance and the S-Matrix BLExWo9Empk 4006 1. Introduction to Battlecode Fl6fKzon8LI 4007 2. Writing Your First Player PA3bcu83j38 4008 3. Navigation g2NoQCEgsCM 4009 4. Git Repository dEXo0QyA-Rs 4010 5. Swarms, Artillery, and Mines tbsYFzmk_24 4011 6. Numerical Strategy pISCwkvKMZ0 4012 7. The Lost Lecture 3j3Odfpvhrs 4013 8. Lessons from the Sprint Tournament lZ3bPUKo5zc 4014 Lecture 1: Introduction to Superposition TkJ_WgruM2g 4015 2. Experimental Facts of Life Ei8CFin00PY 4016 Lecture 3: The Wave Function NN2txluv1PY 4017 Lecture 4: Expectations, Momentum, and Uncertainty lMFgfqRZYoc 4018 Lecture 5: Operators and the Schrödinger Equation TWpyhsPAK14 4019 Lecture 6: Time Evolution and the Schrödinger Equation Uk5DUtHY7LM 4020 Lecture 7: More on Energy Eigenstates qu-jyrwW6hw 4021 Lecture 8: Quantum Harmonic Oscillator jJX_1zT73U0 4022 Lecture 9: Operator Methods for the Harmonic Oscillator VSqpYPgxcps 4023 Lecture 10: Clicker Bonanza and Dirac Notation iZKAtzK5WXM 4024 Lecture 11: Dispersion of the Gaussian and the Finite Well lHhw_SExF1M 4025 Lecture 12: The Dirac Well and Scattering off the Finite Step SsCeVABM4Mo 4026 Lecture 13: More on Scattering H5m39G-FAwE 4027 Lecture 15: Eigenstates of the Angular Momentum Part 1 R4LyPVfGWtI 4028 Lecture 16: Eigenstates of the Angular Momentum Part 2 mLe8YCnUed4 4029 Lecture 17: More on Central Potentials G5_u6k9LR3E 4030 Lecture 18: "Hydrogen" and its Discontents 9lX2FENOe4o 4031 Lecture 19: Identical Particles gK_D6RkbMy8 4032 Lecture 20: Periodic Lattices Part 1 SZlnoxak4xM 4033 Lecture 21: Periodic Lattices Part 2 Oq4OHT4hhJc 4034 Lecture 22: Metals, Insulators, and Semiconductors Rc1vFAUnRUM 4035 Lecture 23: More on Spin awpnsGl08bc 4036 Lecture 24: Entanglement: QComputing, EPR, and Bell's Theorem ytewCHh00mk 4037 Experiment 2: Effective Mass QI13S04w8dM 4038 1. Wave Mechanics 4WsMeqCKpgI 4039 14. Quantum Dynamics (continued) 65XkZ_SRxBk 4040 25. Addition of Angular Momentum (continued) 8yvmHBGcNbg 4041 6. Linear Algebra: Vector Spaces and Operators (continued) AX9769eQV24 4042 3. Wave Mechanics (continued) and Stern-Gerlach Experiment RTKvGmiT-9Q 4043 19. Multiparticle States and Tensor Products (continued) a9FHHS6n-r4 4044 8. Linear Algebra: Vector Spaces and Operators (continued) eZzBK3oy-08 4045 5. Linear Algebra: Vector Spaces and Operators jjZM88ku-7k 4046 7. Linear Algebra: Vector Spaces and Operators (continued) lnZR0TVNh2k 4047 2. Wave Mechanics (continued) xieyFMfX-Ao 4048 18. Two State Systems (continued), Multiparticle States and Tensor Products 7Nrymx1ULis 4049 12. Quantum Dynamics 8rAQBnhbjms 4050 10. Uncertainty Principle and Compatible Observables BWM0RXg-uvI 4051 4. Spin One-half, Bras, Kets, and Operators JjoqYkq4J6k 4052 21. Angular Momentum (continued) LYXIUtVzPAM 4053 20. Multiparticle States and Tensor Products (continued) and Angular Momentum NXgobnaBN7U 4054 15. Quantum Dynamics (continued) Oi-JCJePLlc 4055 11. Uncertainty Principle and Compatible Observables (continued) TUenwZezzdk 4056 16. Quantum Dynamics (continued) and Two State Systems WFQ-UcH4jMM 4057 26. Addition of Angular Momentum (continued) YDRMLCuNteY 4058 23. Angular Momentum (continued) ZTNip78TUvA 4059 24. Addition of Angular Momentum r2NMWEsNcTs 4060 9. Dirac's Bra and Ket Notation t3r9j7YUFrs 4061 17. Two State Systems (continued) v3dkStu-tMc 4062 22. Angular Momentum (continued) zOZw3zCLzyE 4063 13. Quantum Dynamics (continued) | Heisenberg Picture Zg6wQdMFO2c 4064 Problem Solving Process 3gxNrc_EEN8 4065 Dimensional Analysis 6HtVKlFNb2A 4066 Radio Receivers AfQEEymfzaI 4067 Free Body Diagrams DRte6vRCIgI 4068 Vector Fields JrlZSfRM-IY 4069 Stability Analysis aT-gcunlFJg 4070 Kinetics and Equilibrium lGaMKrtiTc8 4071 Rigid Body Kinematics mBJCP3AH2Mk 4072 Contaminant Fate Modeling nwZ9FbZtOv0 4073 Linear Approximations o84SekTsgPo 4074 Conservation of Mass w4y12u5S0HE 4075 Diffusion and Fick's Law zRslv221V9c 4076 Motion Xcsp0486olY 4077 What is Entrepreneurship oD7X3KvJAVk 4078 What is Innovation 1mw_Uo5ba58 4079 Varieties of Innovation NExvTgq5IM4 4080 Three Ways to Start a Company _zWgGX71Iws 4081 Six Myths of Entrepreneurship JyYoXu0cJwA 4082 How to Do Market Segmentation 2KpOZ9N2QOQ 4083 What is a Beachhead Market Ma3ANiGPVNU 4084 Our Passion for Entrepreneurship at MIT IPDZFNh73Kw 4085 Market Segmentation with SensAble Technologies: Part I cHgbCAHQgbU 4086 Market Segmentation with SensAble Technologies: Part II NS0pxSF0Kmo 4087 From Passion to Idea or Technology cKJ0Bx3N2tQ 4088 What Makes a Business 0nFNEpIYmk8 4089 7. Impulse, skier separation problem 5iTUUeKjiEM 4090 10. Three cases, rolling disc problem K1pZ90xp2Gw 4091 4. Magic and super-magic formulae K_6tRupDxF4 4092 1. Course information; Begin kinematics PJ905OQGsBA 4093 3. Pulley problem, angular velocity, magic formula ejvzjQ1wQ-U 4094 8. Single particle; Two particles uhjq0UQqkVg 4095 9. Dumbbell problem, multiple particle systems, rigid bodies, derivation of torque = I*alpha vIjmMUI2w4c 4096 2. The "spider on a Frisbee" problem yYDEpATHF7o 4097 5. Super-magic formula, degrees of freedom, non-standard coordinates, kinematic constraints BcVzc6IGwS0 4098 2. The Solar Resource yHzpj_MDOdk 4099 16. Solar Cell Characterization PLVjevMsQpQ 4100 13. Thin Films: Material Choices & Manufacturing, Part II 9LGLbcjXxqI 4101 10. Wafer Silicon-Based Solar Cells, Part I dFF2DuEv-2c 4102 7. Toward a 1D Device Model, Part I: Device Fundamentals n25tsUQb3vo 4103 18. Cost, Price, Markets, & Support Mechanisms, Part I a6NFLJ082vI 4104 Student Project Presentations - Part 2 lLcDbHI5KGU 4105 14. PV Efficiency: Measurement and Theoretical Limits rhV4Wnz8g-U 4106 12. Thin Films: Material Choices & Manufacturing, Part I 3NQlT1SYpuQ 4107 11. Wafer Silicon-Based Solar Cells, Part II hewgCK5oZAo 4108 Student Project Presentations - Part 1 iJ_lDszxGDw 4109 4. Charge Excitation W1Wh00CQ-Vc 4110 9. Charge Extraction C42jXQLc_Jo 4111 17. Modules, Systems, and Reliability FLbfYpkSZ84 4112 15. Advanced Concepts c4jP3XCZ4Sw 4113 20. R&D Investment & Innovation in PV KUjWMEBSS8Q 4114 19. Cost, Price, Markets, & Support Mechanisms, Part II uLbqhIp3ahc 4115 5. Charge Separation, Part I: Diode w6Gfm4D_pmw 4116 3. Light Absorption and Optical Losses vN5Yn-niTXE 4117 8. Toward a 1D Device Model, Part II: Material Fundamentals AWU3lTs9KJA 4118 6. Charge Separation, Part II: Diode Under Illumination LOVZE9WalRE 4119 1. Introduction (2.627 Fundamentals of Photovoltaics) gF9Q0wNGENc 4120 10. Linear time-invariant (LTI) systems RG3CkwIDYfI 4121 9. Transmitting on a physical channel JJdzY3OTzEg 4122 8. Noise POetF9rX7Zw 4123 7. Viterbi decoding ytGmd25_10k 4124 6. Convolutional codes jNzdhBVU620 4125 5. Error correction, syndrome decoding 5YyUArlg8Sg 4126 4. Linear block codes, parity relations HkmAT9eVYSo 4127 3. Errors, channel codes WafWLM41pQ0 4128 2. Compression: Huffman and LZW BtaVq2g17G0 4129 1. Overview: information and entropy fQcJNoe-q-s 4130 11. LTI channel and intersymbol interference jQM_gpIXBFs 4131 12. Filters and composition Te1qKOJd8aw 4132 13. Frequency response of LTI systems U1sAeMwdm6A 4133 14. Spectral representation of signals 7kpuZgm-3GY 4134 15. Modulation/demodulation QfaGCnfWpus 4135 16. More on modulation/demodulation 9HCUnJB9ovk 4136 17. Packet switching y02p8znNAKk 4137 18. MAC protocols 2QxgN2ugcMY 4138 19. Network routing (without failures) EG6PPYma050 4139 20. Network routing (with failures) qpYjftJbGYI 4140 21. Reliable transport xa38Q2_pnlQ 4141 22. Sliding window analysis, Little's law oIezCGjxV3A 4142 23. A brief history of the Internet RN4gSBTANUY 4143 24. History of the Internet cont'd, course summary Ug6DYV6za-k 4144 An Introduction to Active Learning Recitation in 16.06 OCMbmPx6fYM 4145 Transitioning From a Lecturer to a Coach ubhxIM51UPU 4146 The Advantages of Active Learning sldnB9DVjUk 4147 Adjusting to Active Learning M7zTtKAbRn4 4148 12. From Reduced Form to Structural Evaluation ONO1anWuNOk 4149 11. Evaluation of a Large Scale Microfinance Experiment BrvMZf2jaso 4150 10. Dynamic Financial Constraints w7aOU0ZAJp0 4151 9. Labor and Development -CASb3VeZRg 4152 8. Macro Approaches to Consumption Smoothing and Risk Sharing h6Ok8CNVOaE 4153 7. Capital Asset Pricing IVm21JGcwFo 4154 6. Insurance AW3a2ECNFlE 4155 5. Measurement in Development ekWxanQrsz4 4156 4. Growth, TFP, Domestic and International Capital Flows Q0Ponv0DBXU 4157 3. Growth, TFP, and Inequality MR_Dwrf9yII 4158 2. Micro-Founded Macro Models 0hA7nbRzOy0 4159 1. Finance, Growth, and Volatility xIOQ0O90DjI 4160 9. Some review and introduction to solar photovoltaics bf5IWKhSWRo 4161 8. Advance properties of materials: What else can we do? FvwDJ3Op2Js 4162 7. Quantum modeling of solids: Basic properties VsQi0jHQ3to 4163 6. Hydrogen storage, and atoms to molecules Iq8yyEHm_jI 4164 5. Application of QM modeling: Solar thermal fuels (II) U5zt5u-C_uY 4165 4. Application of QM modeling: Solar thermal fuels (I) HkoxlFUerR0 4166 3. From many-body to single-particle: Quantum modeling of molecules CJkfedF3Y7k 4167 2. Practice makes perfect HGB8VlcFVzU 4168 1. It's a quantum world: The theory of quantum mechanics d3ChB1tDMyI 4169 0. Introduction to Part II: Quantum mechanical methods 8GIRyIkHJZI 4170 10. Solar photovoltaics RVWsRDF0-p0 4171 Teaching 4.241J/11.330J: Embracing Complexities of Urbanism k2_wuThLG6o 4172 1. Introduction to Theory of City Form rbTLRBdEcqA 4173 2. Normative Theory I: The City as Supernatural oBKDFgLoR9o 4174 3. Normative Theory II: The City as Machine gMmamytjyXI 4175 4. Normative Theory III: The City as Organism 0su7rM_7_DM 4176 5. Descriptive and Functional Theory ayw-96xs-ag 4177 6. Dimensions, Patterns, Agreements, Structure, and Syntax SEu8X7AfllU 4178 7. The Early Cities of Capitalism qBrYZb6tdo4 4179 8. Transformations I: London fyQFGf2z4gQ 4180 9. Transformations II: Paris wOR8XgKnWZA 4181 10. Transformations III: Vienna and Barcelona urE_22UEO_8 4182 11. Transformations IV: Chicago Lac4liQeHEQ 4183 12. Transformations V: Panopticism, St. Petersburg and Berlin lKy6EMP3Yhw 4184 13. Utopianism as Social Reform and Built Form HHpf1He752s 4185 14. 20th Century Realizations: Russia and Great Britain yv3PIJF1Uqc 4186 15. City Form and Process MOcWRURkmS0 4187 16. Spatial & Social Structure I: Theory 1Aj6M4peeGw 4188 17. Spatial & Social Structure II: Bipolarity H2GNZX0h84I 4189 18. Spatial & Social Structure III: Colony & Post-colony LYudSLnQEkY 4190 19. Form Models I: Modern and Post-modern Urbanism 4DX9GM_kZmc 4191 20. Form Models II: Open-endedness and Prophecy Wf4_tmPw1As 4192 21. Form Models III and IV: Rationality and Memory q485E0u9Kjk 4193 22. Cases I: Public and Private Domains 1KRy9nUmzfM 4194 23. Cases II: Suburbs and Periphery 3V5ORt7shjI 4195 24. Cases III: Post-urbanism and Resource Conservation M4VQypB3o90 4196 26. Conclusion: Towards a Theory of City Form X1F6a1FWirM 4197 25. Cases IV: Hyper and Mega-urbanism c6-ybCfU6Zc 4198 Ses. 3-6: Six Sigma Basics hQRfikgHzdg 4199 Ses. 3-5: Quality Tools and Topics z1KloN7Ub0M 4200 Ses. 3-4: A3 Thinking I-DIXcoeaNQ 4201 Ses. 3-3 Lean for Healthcare: An Overview uDBGHmhAmT8 4202 Ses. 3-2: Variability Simulation uGkH08B05Q4 4203 Ses. 2-4: Improving the Enterprise, Healthcare Option dNvt3SSm9Jc 4204 Ses. 2-2: Continuous Process Improvement, Healthcare Option F3tPapv5w48 4205 Ses. 2-1: Lean healthcare simulation (covers 2-1, 2-3, and 2-5) Ba8ZyAmffAM 4206 Ses. 1-6: Value Stream Mapping Basics uVlkeGHup6E 4207 Ses. 1-5: People: The Heart of Lean u3Umk_2PVuw 4208 Ses. 1-3: Lean Thinking: Part II POBjtg7oDFg 4209 Ses. 1-3: Lean Thinking: Part I T1K4pkhtad8 4210 Ses. 1-2: The Start of Your Lean Journey TOLwmtn8Miw 4211 13. Closing Thoughts LmE_mdugLWE 4212 12. Question and Answer Session 4 EXXZQjo3twk 4213 10. Question and Answer Session 3 6Px0livk6m8 4214 11. Mind vs. Brain: Confessions of a Defector o6suzoRLZD4 4215 9. Common Sense ATkGXyfuJqs 4216 8. Question and Answer Session 2 oG6FyY2r9G0 4217 7. Layered Knowledge Representations qJZ_1a-t_sA 4218 6. Layers of Mental Activities AO7F0n2Dclc 4219 5. From Panic to Suffering LuJFPVY1Nzo 4220 4. Question and Answer Session 1 2KbvJ3iapbc 4221 3. Cognitive Architectures 6AS48fTXBBs 4222 2. Falling In Love -pb3z2w9gDg 4223 1. Introduction to 'The Society of Mind' 0MrkYxOg_Vo 4224 Sampling People on Buses 3mu47FWEuqA 4225 The Coupon Collector Problem 81ZWzdj-I9w 4226 Joint Probability Mass Function (PMF) Drill 1 DwBK4duYhTU 4227 Inferring a Parameter of Uniform Part 2 TbC-kPbRt3c 4228 Inferring a Continuous Random Variable from a Discrete Measurement aGyJO6G3mxQ 4229 A Coin with Random Bias eUPpqZFSqdw 4230 Competing Exponentials x4q6H6lxFFE 4231 Convergence in Probability and in the Mean Part 1 3gCQ6-yitFc 4232 Hypergeometric Probabilities 6UdLp2gpmcE 4233 A Mixed Distribution Example 7zjuscCceR8 4234 Flipping a Coin a Random Number of Times 96UEwIcSTG0 4235 Inferring a Discrete Random Variable from a Continuous Measurement 9hzVb4hfPPo 4236 Inferring a Parameter of Uniform Part 1 D_vUxa3tEGs 4237 Convergence in Probability and in the Mean Part 2 GJ2klfD0Q3g 4238 Mean & Variance of the Exponential M3615Gbd6-8 4239 Using the Central Limit Theorem Na4R11fWVJg 4240 Rooks on a Chessboard PqZj8pySQiU 4241 Network Reliability eb-eRduYwZY 4242 Convergence in Probability Example eilGapl5cz8 4243 A Chess Tournament Problem euqZK85cQwo 4244 The Probability Distribution Function (PDF) of [X] ibFeUX5F_fw 4245 Setting Up a Markov Chain jxxrwZtpHH0 4246 Uniform Probabilities on a Square s8geHBRvSos 4247 Probabilty Bounds 8ueUXUTRlSQ 4248 The Sum of Discrete and Continuous Random Variables JIOJRuzwJQw 4249 Joint Probability Mass Function (PMF) Drill 2 Qx2NKaUCUw0 4250 PMF of a Function of a Random Variable UgKrQ2ywVfs 4251 The Monty Hall Problem Y8zx1tWEbeI 4252 Widgets and Crates f8Nli1AfygM 4253 The Difference of Two Independent Exponential Random Variables fa5Bdv_94ZE 4254 Mean First Passage and Recurrence Times gpMLYEMIw24 4255 Ambulance Travel Time i0Jom_gR0t4 4256 Bernoulli Process Practice wQ6Q9W3Y1ZE 4257 Calculating a Cumulative Distribution Function (CDF) xFS4xpYQ82w 4258 Probability that Three Pieces Form a Triangle ya1braz5n88 4259 A Random Walker S_Egep9GOpQ 4260 A Coin Tossing Puzzle nxHOWeT0ID0 4261 Markov Chain Practice 1 rzg_CavQI_M 4262 Communication over a Noisy Channel 62KrMWdX-RU 4263 Normal Probability Calculation NYOcZx6Kxsw 4264 A Random Number of Coin Flips 1s2H3QssiMw 4265 An Inference Example 6MffbP5O2v0 4266 Conditional Probability Example HwkKtHLCmzo 4267 A Derived Distribution Example NlRgBtSLViI 4268 The Variance in the Stick Breaking Problem y7lV5jwK27E 4269 Geniuses and Chocolates CSkcBXUIJh4 4270 Using the Conditional Expectation and Variance X5ch4xZf3LE 4271 The Absent Minded Professor v8N6l9RXbOM 4272 Uniform Probabilities on a Triangle o4Ccc1qJyAo 4273 The Probability of the Difference of Two Events imIVOrUkNJE 4274 Debrief Session for First Draft of Sample Paper #1 gCIxvunjqf0 4275 Course Introduction G7p3lFMmDiQ 4276 Writing Workshop fJQz-t3Zzro 4277 Practice Presentation for Sample Paper #1 -UdkFmZwUqA 4278 Final Presentation for Sample Paper #1 5ZhLLCQWjWQ 4279 Debrief Session for First Draft of Sample Paper #2 U_LjhPf92-A 4280 Presentation Workshop rNoeRFC17fQ 4281 Project Laboratory in Mathematics: A Taste of Research IEPuLyxRmJc 4282 Chirality DjMaDN3EtWc 4283 Gear Trains XR_0k8JIawY 4284 Buffers 0BDi0d1j7u0 4285 Basic Programming Techniques NlSKAbefDTA 4286 Equilibrium vs. Steady State eRZDD6Ypdc0 4287 What is Temperature? IOcrHOc23N4 4288 Rotating Frames of Reference Of68ZXH35o0 4289 Polyelectrolyte Multilayers X8DlaW83HJc 4290 The Art of Approximation pR12XGWcn0U 4291 Feedback Loops JGeTcRfKgBo 4292 Conditional Probability cKcAcm5NDOI 4293 1. The Paradigm Shift from Producer to User Innovation 31iUEuwi740 4294 2. Basing New Commercial Products on "Lead User" Innovations odj5VnTI490 4295 3. Users Working Together in Communities Are Powerful Innovators RPSt0o3yRhI 4296 4. Toolkits to Support Product Development by Customers 62FdhX-zS2Y 4297 23. Stem Cells BK1afo-GMag 4298 21. Development 1 b_lgH_ZnCmg 4299 29. Cancer I kpUg96uZk2M 4300 26. Neurobiology 3 080BGpawP3I 4301 22. Development 2 Nx76XS_4FRE 4302 25. Neurobiology 2 svahhl-J4AY 4303 30. Cancer 2 THR1YOKVdtk 4304 31. Cancer 3 dKLkXQEN9XU 4305 24. Neurobiology 1 WB8r7CU7clk 4306 1. Introduction to Effective Field Theory (EFT) f4BQ_VHXgd8 4307 2. Dimensional Power Counting 6PrAW28eUpE 4308 3. Field Redefinitions KwtuwXp16cY 4309 4. Matching and Decoupling zqOoSBbcack 4310 6. Chiral Lagrangians HKkSPqCOmD0 4311 7. Chiral Loops kEd-WsV7ESA 4312 8. Heavy Quark Effective Theory (HQET) ogrcXqbvbL4 4313 9. HQET Matching & Power Corrections kZcGNN5cYCg 4314 10. HQET Examples wwSNCM7e9VA 4315 11. Renormalons DdnXB0Fa3gQ 4316 12. More Renormalons DdY98Zaff5I 4317 14. EFT with Fine Tuning Part 2 v2JKK_yPwc0 4318 15. Soft-Collinear Effective Theory (SCET) Introduction AFQnH_upWBY 4319 16. SCET Collinear Wilson Lines TcNXre5Ea6Y 4320 17. SCET Multipole Expansion Jtda1czqdxc 4321 19. SCET Beyond Tree Level 2 pusPy4EDPC0 4322 20. SCET Wilson Coefficients kJFbJDYuU_k 4323 21. SCET Sudakov Logarithms tKo9-jn7A3g 4324 22. SCET for DIS hAFnqX7diSU 4325 23. SCET for Dijets k0vA0aTcUZA 4326 24. SCETII zd9aU90WzV8 4327 25. SCET_2 Rapidity RGE WtOJN2TCD6o 4328 18. SCET Beyond Tree Level Xpqcsa3RVTU 4329 26. SCET for LHC VrXUdbg3NiM 4330 13. EFT with Fine Tuning zr3wuh3fWRw 4331 5. Classic Operator Renormalization Group Equations (RGE) XPEJg_6Cg6o 4332 23. Model Merging, Cross-Modal Coupling, Course Summary j1H3jAAGlEA 4333 4. Search: Depth-First, Hill Climbing, Beam 09mb78oiPkA 4334 10. Introduction to Learning, Nearest Neighbors PimSbFGrwXM 4335 19. Architectures: GPS, SOAR, Subsumption, Society of Mind 6nDqY8MPLDM 4336 Mega-R5. Support Vector Machines Tl_p5pgBsyM 4337 Mega-R2. Basic Search, Optimal Search bQI0OmJPby4 4338 18. Representations: Classes, Trajectories, Transitions kHyNqSnzP8Y 4339 13. Learning: Genetic Algorithms L73hY1pBcQI 4340 14. Learning: Sparse Spaces, Phonology TjZBTDzGeGg 4341 1. Introduction and Scope J-ocRQCjcwE 4342 Mega-R7. Near Misses, Arch Learning PNKj529yY5c 4343 2. Reasoning: Goal Trees and Problem Solving SXBG3RGr_Rc 4344 11. Learning: Identification Trees, Disorder l-tzjenXrvI 4345 7. Constraints: Interpreting Line Drawings leXa7EKUPFk 4346 3. Reasoning: Goal Trees and Rule-Based Expert Systems EC6bf8JCpDQ 4347 22. Probabilistic Inference II gvmfbePC2pc 4348 9. Constraints: Visual Object Recognition A6Ud6oUCRak 4349 21. Probabilistic Inference I sh3EPjhhd40 4350 15. Learning: Near Misses, Felicity Conditions hM2EAvMkhtk 4351 Mega-R3. Games, Minimax, Alpha-Beta UHBmv7qCey4 4352 17. Learning: Boosting gGQ-vAmdAOI 4353 5. Search: Optimal, Branch and Bound, A* iusTmgQyZ44 4354 Mega-R1. Rule-Based Systems ZZmzMJB-tow 4355 Mega-R6. Boosting JMrFgnqSS0w 4356 Mega-R4. Neural Nets _PwhiWxHK8o 4357 16. Learning: Support Vector Machines STjW3eH0Cik 4358 6. Search: Games, Minimax, and Alpha-Beta NkV27ApZ0h4 4359 Unit Analysis mDvty90jENM 4360 Gradient pazn1IIeDEU 4361 Kinetic Theory FXWZr3mscUo 4362 Enzyme Kinetics l8HAiSLPSn8 4363 VSEPR ND89SWpkWgw 4364 Electric Potential tGqogBLtK4M 4365 Flux and Gauss' Law 8r_cJIHv3A0 4366 Strategic Communication mVQOmLTXLbQ 4367 Vectors 870y6GUKbwc 4368 Entropy 2HpF8R_cjR8 4369 Torque x5Zr2-od-fU 4370 Models of Light 3e1ZF1L1VhY 4371 22. History of Memory Models Yarwp7TNTL4 4372 21. Dynamic Connectivity Lower Bound L7ywsci9ujo 4373 20. Dynamic Graphs II XZLN6NxEQWo 4374 19. Dynamic Graphs I ABX-Hvn8ymE 4375 18. Succinct Structures II 3Y2weLDiUWw 4376 17. Succinct Structures I NinWEPPrkDQ 4377 16. Strings 0rCFkuQS968 4378 15. Static Trees pOKy3RZbSws 4379 14. Sorting in Linear Time RecEYrnvGPM 4380 13. Integer Lower Bounds xSGorVW8j6Q 4381 12. Fusion Trees u-HHY1ylhHY 4382 11. Integer Models Mf9Nn9PbGsE 4383 10. Dictionaries Fs4-E4Nj1Ks 4384 9. Cache-Oblivious Structures II bY8f4DSkQ6M 4385 8. Cache-Oblivious Structures I V3omVLzI0WE 4386 7. Memory Hierarchy Models NoOYvZvH_FU 4387 6. Dynamic Optimality II DZ7jt1F8KKw 4388 5. Dynamic Optimality I FzS0n_Z8lrk 4389 4. Geometric Structures II NMxLL3D5qd8 4390 3. Geometric Structures I WqCWghETNDc 4391 2. Retroactive Data Structures T0yzrZL1py0 4392 1. Persistent Data Structures SFXxjejtsCI 4393 Lab 10 Part 1: Introduction to Lighting (Lecture) xMohaACn0yY 4394 2. Documentary and Ways of Seeing 7FzD5EH7_q8 4395 3. Science and Seeing nHhQeCdbxoE 4396 Lab 1 Part 1: Introduction to the Camera Hy0YzQa-tW8 4397 Lab 10 Part 2: Introduction to Lighting (Demonstration) gv5DP2JMIlo 4398 Lab 6: Documenting MIT; Interviewing Techniques QKUOHFHkttg 4399 Lab 2 Part 2: Introduction to Sound ENpCNrl_NjI 4400 Lab 1 Part 2: Camera Tutorial and Shooting Exercises U975uDZ1oTY 4401 Lab 2 Part I: Review Lab 1 Footage; Film Grammar hRlOTPnJmqM 4402 1. Introduction: Doing Science & Making Documentary Film A5j7NosunEQ 4403 Lab 11: Silicon Photovoltaics DINHUO-JxZ8 4404 Lab 8: Doping H4ApbdIFmkA 4405 Lab 9: Piezoelectricity J5LwNGm0tbw 4406 Lab 5: Paper Microfluidics _FXukyeNEFQ 4407 Lab 3: ZnS:Cu LED fMUemBZ0k5Q 4408 Lab 6A: PDMS Microfluidics: O2 Plasma Treatment fl42pnUbCCA 4409 Lab 1: CD Spectrometer oO5yP0cqEIw 4410 Lab 2: Holography raq5iUY_ykM 4411 Lab 6C: PDMS Microfluidics: Testing the Devices zKm3A6dIXpg 4412 Lab 6B: PDMS Microfluidics: Preparing a Test Pattern 9QwiP6glJfw 4413 Tour the Experimental Study Group Area 4hTOGc93ZTc 4414 10. Interference of Electromagnetic Waves IokpYk5mTas 4415 2. Harmonic Oscillators with Damping U_C7xW_gCfI 4416 7. Standing Waves Part II Usm7cWtAbRY 4417 4. Coupled Oscillators without Damping X60J__-GMx8 4418 6. Standing Waves Part I YbFgNsM6r44 4419 1. Simple Harmonic Motion & Problem Solving Introduction h4S4eHdwUL0 4420 8. Electromagnetic Waves in a Vacuum j1ADxLi1wYg 4421 3. Driven Harmonic Oscillators uyofLz9Dtuw 4422 5. Traveling Waves without Damping wF8vLZ9ceb0 4423 9. Accelerated Charges Radiating Electromagnetic Waves Fo-Y6kEMURk 4424 10. Equations of Motion, Torque, Angular Momentum of Rigid Bodies zNCBDrnT05E 4425 8. Fictitious Forces & Rotating Mass -QVENB3aEvY 4426 R8. Cart and Pendulum, Lagrange Method 1xJJu5p3dD0 4427 27. Vibration of Continuous Structures: Strings, Beams, Rods, etc. 3F4wlYR_3h8 4428 R12. Modal Analysis of a Double Pendulum System 6wPHoFjnYXI 4429 R6. Angular Momentum and Torque 7kcWV6zlcRU 4430 R2. Velocity and Acceleration in Translating and Rotating Frames 9CPA6WG6mRo 4431 22. Finding Natural Frequencies & Mode Shapes of a 2 DOF System 9_d8CQrCYUw 4432 19. Introduction to Mechanical Vibration OxcCPTc_bXw 4433 24. Modal Analysis: Orthogonality, Mass Stiffness, Damping Matrix PZ1zxBO1kO8 4434 R5. Equations of Motion QYP-oC1kP_s 4435 R3. Motion in Moving Reference Frames QadsG49DY3M 4436 R9. Generalized Forces Ze5nqLIYUMc 4437 R7. Cart and Pendulum, Direct Method cd8lDtAtJbE 4438 17. Practice Finding EOM Using Lagrange Equations cecD1w3-SD0 4439 R4. Free Body Diagrams f1pxiNDTyHc 4440 21. Vibration Isolation fK9AGvLf3yw 4441 26. Response of 2-DOF Systems by the Use of Transfer Functions fZKrUgm9R1o 4442 R11. Double Pendulum System jROTMB142T0 4443 6. Torque & the Time Rate of Change of Angular Momentum lFedznDnPZc 4444 16. Kinematic Approach to Finding Generalized Forces osyKjTQuwlk 4445 18. Quiz Review From Optional Problem Set 8 p9DHjoLS3GA 4446 25. Modal Analysis: Response to IC's and to Harmonic Forces pYZMNOuRwk0 4447 R10. Steady State Dynamics qrbCpv3Sv34 4448 14. More Complex Rotational Problems & Their Equations of Motion tm51lwadMOc 4449 23. Vibration by Mode Superposition wzEqF_UQkks 4450 20. Linear System Modeling a Single Degree of Freedom Oscillator zhk9xLjrmi4 4451 15. Introduction to Lagrange With Examples zlbbbA5Uuu8 4452 Notation Systems wERH7LtoUuE 4453 13. Four Classes of Problems With Rotational Motion 63sIgMvBuEQ 4454 7. Degrees of Freedom, Free Body Diagrams, & Fictitious Forces NHedXxUO-Bg 4455 5. Impulse, Torque, & Angular Momentum for a System of Particles QHTJK0v404U 4456 9. Rotating Imbalance YZ9y4zcfCPs 4457 11. Mass Moment of Inertia of Rigid Bodies d00XI_UTKQo 4458 3. Motion of Center of Mass; Acceleration in Rotating Ref. Frames iMz0LiqjFmE 4459 4. Movement of a Particle in Circular Motion w/ Polar Coordinates mB_rrEN_Ltc 4460 12. Problem Solving Methods for Rotating Rigid Bodies ZNVvYg1FOPk 4461 2. Newton's Laws & Describing the Kinematics of Particles GUvoVvXwoOQ 4462 1. History of Dynamics; Motion in Moving Reference Frames 1S_QU0PmYrU 4463 Lesson 13: Part 3 - Food Preparation 7c2bwfiDCgs 4464 Selecting the Correct Language Level AmOVEZRyryk 4465 Idea for the Course FfE0U3Jlkqw 4466 Lesson 13: Part 2 - Ingredients and Cooking Instruction KoXTTlI7mIg 4467 Teaching Italian Grammar NsrNLQ5g978 4468 Lesson 11: Part 3 - Closing Lecture Ov_L1mBpsW4 4469 Preparing for the Course Xm8Dv7qH7UI 4470 Language Immersion ZpQOL9Ec9Lk 4471 Using Cooking to Teach Italian ctP2eqCROLc 4472 Lesson 3: Part 2 - Ingredients and Vocab gmrh_WvmctY 4473 Lesson 4: Part 1 - Language Instruction hufDjvW5DRM 4474 Structure of a Typical Class ibrMMF4Oo-4 4475 Time Management/Students' Energy Levels j9twDytNikc 4476 Creating the Assignments nSin1QDLUDs 4477 Lesson 3: Part 3 - Cooking Instruction pqFskmxJZCo 4478 Lesson 2: Part 1 - Language Instruction qIfu7MwTBrA 4479 Lesson 13: Part 1 - Opening Lecture rxDJlK7RgZA 4480 Future Versions of the Course uYFs17Sh2As 4481 Goals for the Course bHOpK1yQ9tI 4482 Lesson 10: Part 4 - A Game! dTGVt1enLlc 4483 Lesson 8: Part 1 - Opening Lecture dwXBk5z5fcs 4484 Lesson 6: Part 2 - Cooking Instruction gUEOXa57tts 4485 Lesson 7: Part 1 - Opening Lecture m3ye7Ycg9zA 4486 Lesson 5: Part 2 - Ingredients and Vocabulary nQKY3muPumw 4487 Lesson 6: Part 1 - Vocabulary and Sentences odn_rO3ao0Y 4488 Lesson 9 Part 3 - Food Preparation u8slUoRbeN0 4489 Lesson 11: Part 1 - Opening Lecture wEyKvA_O-n4 4490 Lesson 5: Part 3 - Cooking Instruction xqmEuE97KzI 4491 Lesson 6: Part 3 - Closing Lecture zFFnuPvbw9Y 4492 Lesson 10: Part 1 - Opening Lecture 03CJMrAP4vc 4493 Lesson 2: Part 3 - Cooking Instruction 18Gs4SWp0_I 4494 Lesson 12: Part 1 - Opening and Ingredients 1tBrJ7I-1Vc 4495 Lesson 3: Part 1 - Opening Lecture 4VacwRELszQ 4496 Lesson 4: Part 2 - Ingredients and Vocabulary 5AjzlkahiL0 4497 Lesson 1: Part 1 - Language Instruction 5PU-b1HFyDU 4498 Lesson 4: Part 3 - Cooking Instruction 7WrrPchS4Ec 4499 Lesson 9: Part 1 - Opening Lecture 8bITVuu7-O8 4500 Lesson 7: Part 2 - Ingredients CIW1T5YdBuI 4501 Lesson 9: Part 2 - Ingredients and Cooking Instruction CKeXFjIOmZE 4502 Lesson 12: Part 2 - Cooking Instruction F07k0PSQ8xk 4503 Lesson 5: Part 1 - Language Instruction GPYUDm2MDX8 4504 Lesson 8: Part 2 - Cooking Instruction IzztWOkcg4I 4505 Lesson 10: Part 3 - Closing Lecture K4LPH0VDpaY 4506 Lesson 1: Part 2 - Cooking Instruction KfmQr8gcBL0 4507 Lesson 12: Part 3 - Closing Lecture Khw54aZz3gg 4508 Lesson 3: Part 4 - Closing Lecture Ot6KACafyJU 4509 Lesson 11: Part 2 - Ingredients and Cooking Instruction Ph-kwY_OU30 4510 Lesson 7: Part 3 - Cooking Instruction U_Dobe_zofU 4511 Lesson 2: Part 2 - Ingredients Wxk2Q3F6oDE 4512 Lesson 10: Part 2 - Ingredients and Cooking Instruction 1b4-R6NjZOA 4513 12. Feedback Compensation of an Operational Amplifier 6HWeg0Q8VP4 4514 2. Effects of Feedback on Noise and Nonlinearities BGug_49cGYw 4515 5. Root Locus CWlJLpAE4BI 4516 9. More Compensation Cx7eVOkFvKA 4517 3. Introduction to Systems with Dynamics Hgi3PSZI6Jw 4518 11. Feedback Compensation KyO8jcUR254 4519 7. Stability via Frequency Response MtogKYrQ3sA 4520 10. Compensation Example NRlBCoVIJBM 4521 6. More Root Locus PsUPRyatjxw 4522 19. Phase-locked Loops Qyij_naUg-A 4523 17. Conditional Stability SIgbYpXE4Xs 4524 14. Linearized Analysis of Nonlinear Systems ToEFkUxFURg 4525 1. Introduction and Basic Concepts akWLXjbYHK4 4526 8. Compensation eyb_RzOnfGY 4527 18. Oscillators (Intentional) fn2UGyk5DP4 4528 13. Operational Amplifier Compensation (continued) uHtKGf4AymM 4529 20. Model Train Speed Control w6vrSsNPE00 4530 15. Describing Functions wKMUrhlkExw 4531 4. Stability wbEFsypvVQI 4532 16. Describing Functions (continued) HBu23Qqizmc 4533 Exercise 7 Video: Inflation of Discretized Units MJo58_8uSYM 4534 Exercise 7 Video: Construction Process 4VjL3SWAxjY 4535 Video Demonstration of Project 1: Spider Web Deformation WU5elpt0XdE 4536 Video Demonstration of Project 1: Belousov-Zhabotinsky Reaction dVer9B2z4VE 4537 Video Demonstration of Project 1: EMT Variations in Cancer jqpJ52XfOqM 4538 Video Demonstration of Project 1: Chitin and Butterflies 4F1J5Q3DiaI 4539 Ses 3: Present Value Relations II AtT59jxU9es 4540 Ses 6: Fixed-Income Securities III HdHlfiOAJyE 4541 Ses 1: Introduction and Course Overview IwA7nVEwqto 4542 Ses 10: Forward and Futures Contracts II & Options I J7d3vcaS9-o 4543 Ses 14: Portfolio Theory II JE80wLNIhjE 4544 Ses 17: The CAPM and APT III & Capital Budgeting I N8gtnbJuMoo 4545 Ses 16: The CAPM and APT II P03PfYgNjmw 4546 Ses 20: Efficient Markets III & Course Summary Q2qjnLO3I_M 4547 Ses 12: Options III & Risk and Return I U03Md5enU-0 4548 Ses 2: Present Value Relations I ZWKnK9LIETA 4549 Ses 7: Fixed-Income Securities IV a5PF2PcElV0 4550 Ses 19: Efficient Markets II cny-1yDbQno 4551 Ses 8: Equities hyc8h5T76BE 4552 Ses 4: Present Value Relations III & Fixed-Income Securities I i_pLF9J3QPE 4553 Ses 9: Forward and Futures Contracts I rMsu4v-UlkA 4554 Ses 11: Options II sMKQywwkIjQ 4555 Ses 18: Capital Budgeting II & Efficient Markets I tL7Lcl90Sc0 4556 Ses 13: Risk and Return II & Portfolio Theory I yrmqYNvvIzs 4557 Ses 5: Fixed-Income Securities II z2oQe6B1Qa4 4558 Ses 15: Portfolio Theory III & The CAPM and APT I -H-KFf-PNnE 4559 Assignment 3: ("Hello World" Fabric PCB) - PCButterfly in operation 0zitghvkD5w 4560 Assignment 6: (Networked Wearable) - Wrist-based Way-finding compass demonstration ErA4yU29dVA 4561 Assignment 8: (Knit, Woven, Embroidery, or Print) - Blossom algorithm animation LRKA7foBCug 4562 Assignment 8: (Knit, Woven, Embroidery, or Print) - Blossom on the Bernina embroidery machine YmTnFAlgMaM 4563 Assignment 9: (Final Project) - Tunable Stiffness Structures: silicone in wax ck4wFgMnh5U 4564 Assignment 9: (Final Project) - Sneaky Slippers ggoWaPc_2xo 4565 Assignment 3: ("Hello World" Fabric PCB) - PCButterfly laser cutter fabrication lbqiVx7_eDo 4566 Assignment 9: (Final Project) - Responsive Fabric n6mUnjLR3PA 4567 Assignment 9: (Final Project) - Tunable Stiffness Structures: muslin in wax yYTp28YQuYs 4568 Assignment 9: (Final Project) - Tunable Stiffness Structures: steel yarn in wax 00btLB6u6DY 4569 Solute Transport: Advection with Dispersion A_hcPtESedQ 4570 Cape Cod Trip: Groundwater Discharge - Iron and Manganese Presence BVHwDed_X_w 4571 Cape Cod Trip: Ashumit Pond Introduction G8B_Wzmeo_8 4572 Cape Cod Trip: Seepage Meter 2 GjoL2LwdAVU 4573 Cape Cod Trip: Cranberry Bog HxfSOdFOqkk 4574 Cape Cod Trip: Large-scale Aquifer Sampling MzU6DPa_6J4 4575 Solute Transport: Diffusive Mass Transfer NvTZT0U01jc 4576 Cape Cod Trip: Sampling and Monitoring Devices TWfH6UFeNSg 4577 Cape Cod Trip: Water Sampling and Pumping UzulSaiF4Fs 4578 Solute Transport: Active Mass Transfer XIm-f183Ijg 4579 Cape Cod Trip: Sampling and Monitoring Devices hG34fyeC-Gk 4580 Bangladesh Study: Manual Well Drilling mJMS4mvNAag 4581 Cape Cod Trip: Diffusion Sampling mf5YOU_jr8U 4582 Cape Cod Trip: Seepage Meter 1 wfNfnT8RYVg 4583 Solute Transport: Adsorption, Graphing Over Time 0pB2Wn6fvj4 4584 20. Social Movements 6Rq2VFCGQfE 4585 21. U.S. Environment Policy -7dYXCHtTFY 4586 1. This Course and The U.S. Energy System -WapZQ_LwFM 4587 9. Energy Use by Individuals and Households 2oooMpS_3vg 4588 6. Climate Science and Policy 2wGduvHRck4 4589 2. Comparative Energy Systems 6nhKL-AuvY4 4590 19. Making Public Policy 8aNkTgarBis 4591 17. (Yesterday's &) Today's Electric Power System FaLqAip6A0Q 4592 13. Developing Profitable Strategies LoXGM05lqKc 4593 4. The Market and The State NmVdm5kqDvM 4594 15. Non-Renewable Energy Resources WpcbBk5ckas 4595 5. Path Dependence in Energy Systems XJdqfhuqLJA 4596 3. U.S. Energy Problems XMVoIzP6Kpo 4597 11. Business Decisions in Reality: CHP at Hexion _d-sBKShO90 4598 8. Economics of Energy Demand _dZtcXCwIFw 4599 14. Innovation and Energy Business Models f12cqwfH-N0 4600 16. Shale: Opportunities & Challenges hVYBgsi0JcM 4601 22. Economic Development & Green Growth m0eRTYvmRDg 4602 10. Normative Frameworks for Business Decisions mKmMDYGO3-Y 4603 12. Organizational Decision-Making: Biodiesel at MIT ruRaCsL9tpQ 4604 18. Tomorrow's Electric Power System 1p81Mb69f8E 4605 Lab 6: Charcoal Making and Stove Testing 5jk6t_aVrx4 4606 Lab 3: Biogas and Biodigesters, Part II: Activities 7MzwxhtVfFc 4607 Lab 1: Human Power LnSvSfXUmVs 4608 Lab 5: Savonius Wind Turbine Construction and Testing NHGOc_nC_eU 4609 Lab 2: Solar Power Measurement, Part I: Lecture _RIqn1c_BY8 4610 Lab 3: Biogas and Biodigesters, Part I: Lecture g2ISFplW5zQ 4611 Lab 4: Wiring Solar Panels, Part I: Lecture wZ0LCQV9jvY 4612 Lab 4: Wiring Solar Panels, Part II: Activities zVzixXOtq7Y 4613 Lab 2: Solar Power Measurement, Part II: Activities 1El4znkRH0g 4614 21. Sampling 2X7o37pfdp8 4615 11. Continuous-Time (CT) Frequency Response and Bode Plot 3D51nqZ-97Q 4616 18. Discrete-Time (DT) Fourier Representations 4PlHFcfB8DA 4617 4. Continuous-Time (CT) Systems 5w2BvCPuYY0 4618 12. Continuous-Time (CT) Feedback and Control, Part 1 HDYAbIA-DNY 4619 19. Relations Among Fourier Representations K3OFb7RlbVE 4620 3. Feedback, Poles, and Fundamental Modes MRy8xxvsZA4 4621 6. Laplace Transform N0CVIoVQkmc 4622 15. Fourier Series OT04cEdpK-M 4623 23. Modulation, Part 1 OfMhtibbVXU 4624 24. Modulation, Part 2 TeVSxZgIHAA 4625 10. Feedback and Control bJvv5SckGeA 4626 22. Sampling and Quantization iWZNTM139xQ 4627 16. Fourier Transform t2hNMFoIv8w 4628 25. Audio CD -FHm2pQmiSM 4629 1. Signals and Systems Ih4s5IFphCw 4630 2. Discrete-Time (DT) Systems fKaZeD70p8I 4631 9. Frequency Response gwa-Rh0u6bs 4632 17. Discrete-Time (DT) Frequency Representations gxgV_oOG7Zc 4633 13. Continuous-Time (CT) Feedback and Control, Part 2 iI-ejO9hczw 4634 5. Z Transform pqkYqU11ETA 4635 7. Discrete Approximation of Continuous-Time Systems tp_MdKz3fC8 4636 20. Applications of Fourier Transforms ufU6b7OHb8M 4637 14. Fourier Representations w1Z2FX8rQc0 4638 8. Convolution 5hUX2Z5ffF0 4639 Current Events YhZKUKVMa7Q 4640 Constructivist rJC4o7bhlms 4641 Strong Backgrounds sY3ut7JjRCw 4642 Students Thoughts -ZMUweeYBco 4643 Experiment X: Ekman Layers 7BcDOuJRUoo 4644 Experiment VIII: Hadley Circulation 83fDGbK5ANA 4645 Experiment III: Radial Inflow (Fast) Ah6lPqpgVhc 4646 Experiment XIII: Ocean Gyres DARyaierioc 4647 Experiment IX: Cylinder Collapse RrWKSOvqV-0 4648 Experiment V: Visualizing the Coriolis Force Tuj7ynY8Ffc 4649 Experiment XII: Ekman Pumping and Suction UKA8RoZrCdg 4650 Experiment VII: Taylor-Proudman Theorem ZMcgF9WQKyM 4651 Experiment II: Stratified Convection bkBG_QokUCY 4652 Experiment XI: Baroclinic Instability of the Thermal Wind (Eddies) e6AwoSqmAkM 4653 Experiment 0: Non-Rotating Fluids emWThWDNjsE 4654 Experiment 0: Rotating Fluids 2 gLLt3Y3_E9U 4655 Experiment III: Radial Inflow (Slow) ms2jjd6lQOM 4656 Experiment XIV: Thermohaline Circulation n_rs6nkJrvU 4657 Experiment 0: Rotating Fluids P-QxpiSYPOY 4658 Chemistry in Action: Jacquin Niles UEthcrwFZks 4659 Chemistry in Action: Liz Nolan uYuPranLS1k 4660 Chemistry in Action: Katharina Ribbeck pVY9pw7S-B4 4661 Macrowikinomics: Rethinking Education Lecture by Don Tapscott 97G6FGS2JC0 4662 Lab 1: DC Motors Lq6Os-qABK4 4663 Lab 4: Spectrometer YBKJ9Qi2PxM 4664 Lab 2: Shooting Magnets rWqHLR5aSXM 4665 Lab 3: Liquid Crystal Displays w-8_fMtNZiQ 4666 Lab 5: Quantum Mechanical Tunneling ACqW2Z64-GE 4667 9. Patient Safety in Resource-Poor Settings JxDTBbXKvyo 4668 5. Process Improvement Theory and Application KxG5v5mRMwc 4669 4. Health Systems Research LidkQq8cYnc 4670 11. The Millenium Global Village-Network MNatWiy5GjA 4671 6. Innovation and Adoption of New Practices QGOLnKZTFEQ 4672 1. Translational Research and Advocacy Vf9if09KUvw 4673 10. Organizational Change: Positive Deviance fMYY8pLMFcU 4674 8. What is Quality and Why Should We Measure It? mNlOG7CFPEY 4675 7. WHO Safe Surgery and Safe Childbirth Checklists oRENvSw8pO4 4676 3. Overview of Quality Improvement u5BYTR-oKUg 4677 12. A Perspective on Monitoring and Evaluation vQY3NziSZ2w 4678 2. Design and Impact of Health Information Systems Cy5-17esUsE 4679 2. Energy Storage & Microgrids FbP7q5m05pI 4680 Project 4: Final Presentations MVd5BMAgRdI 4681 Project 1: Trip Planning Presentations (from Lecture 7) QAg3GPMUO84 4682 8. Project Design Process SbpeBF8D_m4 4683 1. Introduction to Energy UE3_JL4wS2o 4684 Project 2: Trip Report Presentations (from Lecture 8) WMDXIL3IvBg 4685 7. Solar Cookers; Creative Capacity Building; Trip Preparation YZpYxeeb6hA 4686 Project 3: Initial Design Review bElGczheDOc 4687 3. Lighting; Trip Introduction i35rFCupvNA 4688 4. Solar Energy y4uc4t5vcdI 4689 5. Wind and Micro-Hydro Power; Trip Planning zzePDMT2-oc 4690 6. Cooking, Stoves and Fuel 8wiIV-NfYwc 4691 6. Debugging OisFNNzz3xQ 4692 5. Scripted Functions UKU1477cXVY 4693 3. Using Files WpAXzSJJqW4 4694 4. Plotting jTS5ZmrrzMs 4695 1. Using MATLAB for the First Time lWSsUH_MQM4 4696 2. The Command Prompt 6RbIUZ-ZvZs 4697 26. Five Thoughts in Place of a Sweeing Conclusion FLwiEHSEQt8 4698 25. Policies, Politics: Can Evidence Play a Role in the Fight Against Poverty?, cont. LERsET25_l0 4699 15. Risk and Insurance LLdc7VyZHt4 4700 24. Policies, Politics: Can Evidence Play a Role in the Fight Against Poverty? Yh6r3I821ng 4701 17. The (Not So Simple) Economics of Lending to the Poor ZaN3W5as42s 4702 19. The Promise and Perils of Microfinance kvmrpgEReX8 4703 16. Insurance nc7dDE4_3zs 4704 20. Savings p5ro4x1r16Q 4705 21. Savings 2 xuAD_a1OuNo 4706 22. Entrepreneurs and Workers 7y67IP6XTPc 4707 2. What is a Poverty Trap? FQZN92nEC0Q 4708 5. Is There a Nutrition-Based Poverty Trap? GdHqomimt8c 4709 13. How Do Families Decide? K2LvCx8H0OU 4710 1. Introduction (14.73 The Challenge of World Poverty) U1g_-FzqUXc 4711 3. Social Experiments: Why and How? b0VOqHiq5zU 4712 8. Health: Low Hanging Fruit? jXU0OeAaHn8 4713 14. Gender Discrimination klz2SdQorbA 4714 10. Is It Possible to Deliver Quality Education to the Poor-The Pratham-JPAL Partnership qAS8Kh2pz9o 4715 6. Nutrition: The Hidden Traps qgA-JxgtjZg 4716 9. Education: Setting the Stage quATCFNpM50 4717 11. Education: The Man Made Trap vE3v2HtAQto 4718 12. (Somewhat) Un-Orthodox Findings on the Family 3oV1saJEZy8 4719 20. Classical Size Effects, Perpendicular Direction 4uHWWVa4z2s 4720 21. Slip Condition, Coupled Energy Transport & Conversion 7Ken5EC4OrU 4721 10. Fundamental of Statistical Thermodynamics D8icilnxcy4 4722 9. Specific Heat and Planck's Law Hqm4Xc4212E 4723 3. Schrödinger Equation and Material Waves Ii6UtH6h2jY 4724 8. Density of States and Statistical Distributions LKNuAQWzWDE 4725 11. Energy Transfer by Waves: Plane Waves XrdcGZppwI4 4726 25. Statistical Foundation for Molecular Dynamics Simulation YHW7TwF00Rs 4727 15. Particle Description, Liouville & Boltzmann Equations ZYMWsmertQk 4728 22. PN Junction, Diode and Photovoltaic Cells _ayCen0j-0w 4729 19. Classical Size Effects, Parallel Direction fYNz3SsWf90 4730 17. Solutions to Boltzmann Equation: Diffusion Laws rEVqrE_7CqE 4731 18. Electron Transport and Thermoelectric Effects zC78xmSbhAY 4732 16. Fermi Golden Rule and Relaxation Time Approximation NLDNfnRGWxI 4733 5. Electronic Levels in One-Dimensional Lattice Chain XfWkgDLc4xA 4734 2. Characteristic Time and Length, Simple Kinetic Theory Z5tZlfSwHrk 4735 24. Electrical Double Layer, Size Effects in Phase Change _DHlhTrlDxc 4736 12. EM Waves: Reflection at a Single Interface _i0yWRrEesM 4737 13. EM Wave Propagation Through Thin Films & Multilayers bESVLOTvijk 4738 4. Solutions to Schrödinger Equation, Energy Quantization fat0ZKEDzSY 4739 14. Wave Phenomena and Landauer Formalism jisTDmIk3Nw 4740 1. Intro to Nanotechnology, Nanoscale Transport Phenomena lcVaTjSpn7Y 4741 7. Phonon Energy Levels in Crystal and Crystal Structures qsFzIv3PHz8 4742 23. Liquids: Brownian Motion and Forces in Liquids rfgaLeHq5f0 4743 6. Crystal Bonding & Electronic Energy Levels in Crystals 2E7MmKv0Y24 4744 Lecture 16: Dijkstra 2YeJ-5UAke8 4745 Lecture 12: Square Roots, Newton's Method 9Jry5-82I68 4746 Lecture 5: Binary Search Trees, BST Sort Aa2sqUhIn-E 4747 Lecture 15: Single-Source Shortest Paths Problem AfSk24UTFS8 4748 Lecture 14: Depth-First Search (DFS), Topological Sort B7hVxCmfPtM 4749 Lecture 4: Heaps and Heap Sort BRO7mVIFt08 4750 Lecture 9: Table Doubling, Karp-Rabin CHvQ3q_gJ7E 4751 Lecture 18: Speeding up Dijkstra FNeL18KsWPc 4752 Lecture 6: AVL Trees, AVL Sort HtSuA80QTyo 4753 Lecture 1: Algorithmic Thinking, Peak Finding Kg4bqzAqRBM 4754 Lecture 3: Insertion Sort, Merge Sort Nz1KZXbghj8 4755 Lecture 7: Counting Sort, Radix Sort, Lower Bounds for Sorting OQ5jsbhAv_M 4756 Lecture 19: Dynamic Programming I: Fibonacci, Shortest Paths Zc54gFhdpLA 4757 Lecture 2: Models of Computation, Document Distance dU40AvBURDQ 4758 Lecture 24: Topics in Algorithms Research eCaXlAaN2uE 4759 Lecture 11: Integer Arithmetic, Karatsuba Multiplication moPtwq_cVH8 4760 Lecture 23: Computational Complexity -DwGrJ8JxDc 4761 Recitation 9b: DNA Sequence Matching 0M_kIqhwbFo 4762 Lecture 8: Hashing with Chaining ENyox7kNKeY 4763 Lecture 20: Dynamic Programming II: Text Justification, Blackjack IFrvgSvZA0I 4764 Recitation 19: Dynamic Programming: Crazy Eights, Shortest Path hkAONP0aC9w 4765 Recitation 24: Final Exam Review mQSp6VmfakA 4766 R15. Shortest Paths oRpERQA4Vik 4767 Recitation 16: Rubik's Cube, StarCraft Zero ocZMDMZwhCY 4768 Lecture 21: Dynamic Programming III: Parenthesization, Edit Distance, Knapsack ozsuci5pIso 4769 Lecture 17: Bellman-Ford rvdJDijO2Ro 4770 Lecture 10: Open Addressing, Cryptographic Hashing s-CYnVz-uh4 4771 Lecture 13: Breadth-First Search (BFS) t5Wxk96QjUk 4772 Recitation 23: Computational Complexity tp4_UXaVyx8 4773 Lecture 22: Dynamic Programming IV: Guitar Fingering, Tetris, Super Mario Bros. wFP5VHGHFdk 4774 Recitation 21: Dynamic Programming: Knapsack Problem -FElVPKykgw 4775 Recitation 10: Quiz 1 Review 4iXLnF3hExw 4776 Recitation 3: Document Distance, Insertion and Merge Sort 5JxShDZ_ylo 4777 Recitation 13: Breadth-First Search (BFS) 9bkvws_vqLU 4778 Recitation 7: Comparison Sort, Counting and Radix Sort C5SPsY72_CM 4779 Recitation 14: Depth-First Search (DFS) IWzYoXKaRIc 4780 Recitation 6: AVL Trees JRgIXyEPnbA 4781 Recitation 12: Karatsuba Multiplication, Newton's Method P7frcB_-g4w 4782 Recitation 1: Asymptotic Complexity, Peak Finding PptQgy89cN8 4783 Recitation 22: Dynamic Programming: Dance Dance Revolution QFcyt8fgQMU 4784 Recitation 2: Python Cost Model, Document Distance a_otxyu0mSQ 4785 Recitation 11: Principles of Algorithm Design eGSXsaJ-BlY 4786 Recitation 8: Simulation Algorithms jZbkToeNK2g 4787 Recitation 20: Dynamic Programming: Blackjack r5pXu1PAUkI 4788 Recitation 5: Recursion Trees, Binary Search Trees sPuazUPiV1k 4789 Recitation 18: Quiz 2 Review w6nuXg0BISo 4790 Recitation 9: Rolling Hashes, Amortized Analysis 09yIb3VHhMI 4791 Lec 17 | MIT 6.042J Mathematics for Computer Science, Fall 2010 1nScXLQAQ9A 4792 Lec 11 | MIT 6.042J Mathematics for Computer Science, Fall 2010 56iFMY8QW2k 4793 Lec 25 | MIT 6.042J Mathematics for Computer Science, Fall 2010 5RSMLgy06Ew 4794 Lec 7 | MIT 6.042J Mathematics for Computer Science, Fall 2010 E6FbvM-FGZ8 4795 Lec 19 | MIT 6.042J Mathematics for Computer Science, Fall 2010 Kqf0uO0oV6s 4796 Lec 14 | MIT 6.042J Mathematics for Computer Science, Fall 2010 L3LMbpZIKhQ 4797 Lec 1 | MIT 6.042J Mathematics for Computer Science, Fall 2010 MOfhhFaQdjw 4798 Lec 21 | MIT 6.042J Mathematics for Computer Science, Fall 2010 TWBB-JlmYUc 4799 Lec 15 | MIT 6.042J Mathematics for Computer Science, Fall 2010 X9eErxRjQEI 4800 Lec 13 | MIT 6.042J Mathematics for Computer Science, Fall 2010 pNt5Ll6hGqo 4801 Lec 16 | MIT 6.042J Mathematics for Computer Science, Fall 2010 DOIp5D7VMS4 4802 Lec 10 | MIT 6.042J Mathematics for Computer Science, Fall 2010 GJpt_3ie4WU 4803 Lec 8 | MIT 6.042J Mathematics for Computer Science, Fall 2010 NuGDkmwEObM 4804 Lec 3 | MIT 6.042J Mathematics for Computer Science, Fall 2010 NuY7szYSXSw 4805 Lec 4 | MIT 6.042J Mathematics for Computer Science, Fall 2010 SmFwFdESMHI 4806 Lec 18 | MIT 6.042J Mathematics for Computer Science, Fall 2010 XX7ePR21Ook 4807 Lec 5 | MIT 6.042J Mathematics for Computer Science, Fall 2010 bTyxpoi2dmM 4808 Lec 9 | MIT 6.042J Mathematics for Computer Science, Fall 2010 fAeShezAGLE 4809 Lec 12 | MIT 6.042J Mathematics for Computer Science, Fall 2010 gGlMSe7uEkA 4810 Lec 22 | MIT 6.042J Mathematics for Computer Science, Fall 2010 h9wxtqoa1jY 4811 Lec 6 | MIT 6.042J Mathematics for Computer Science, Fall 2010 l1BCv3qqW4A 4812 Lec 20 | MIT 6.042J Mathematics for Computer Science, Fall 2010 oI9fMUqgfxY 4813 Lec 23 | MIT 6.042J Mathematics for Computer Science, Fall 2010 q4mwO2qS2z4 4814 Lec 24 | MIT 6.042J Mathematics for Computer Science, Fall 2010 z8HKWUWS-lA 4815 Lec 2 | MIT 6.042J Mathematics for Computer Science, Fall 2010 DJgBybFMkYM 4816 15. Film in the 1970s, Part I YL0TNHW-4P4 4817 19. Italian Neorealism, Part I p12HLN9jw6s 4818 16. Film in the 1970s, Part II 4VvpqIVwsuc 4819 11. Pass/Fail | MIT ChemLab Boot Camp nhGA_iLfKA8 4820 Bonus Video 4: Phil-osophy | MIT ChemLab Boot Camp YrgrcBxcBiw 4821 Science is Fun and the Joy of Learning | MIT Chemistry Behind the Magic 3NlEuo_baRY 4822 Bringin' Home the Bacon | MIT Chemistry Behind the Magic 5Y3hS_ckeJE 4823 Money to Burn | MIT Chemistry Behind the Magic UjHXiTpQGpg 4824 Let It Snow | MIT Chemistry Behind the Magic _erP4SBOXRI 4825 Elements on Fire | MIT Chemistry Behind the Magic iSVu2XHH_NY 4826 Death of a Gummy Bear | MIT Chemistry Behind the Magic l73yJ16-HPk 4827 Let's Drink To That | MIT Chemistry Behind the Magic nAhIrh9vM4A 4828 Colorful Indicators | MIT Chemistry Behind the Magic slSy_ZDeWEg 4829 Steaming Gun | MIT Chemistry Behind the Magic IggngxY3riU 4830 Briggs-Rauscher Reaction | MIT Chemistry Behind the Magic PY-R-7tkjSc 4831 Mirror Mirror | MIT Chemistry Behind the Magic Y9y3Xb5ocp8 4832 Midas' Magic | MIT Chemistry Behind the Magic qSKhcFEpHcE 4833 Anatomy of a Glowstick | MIT Chemistry Behind the Magic _fJZbeVeBxg 4834 10. The Killing Curve | MIT ChemLab Boot Camp zIEDzaF9gKw 4835 9. Roses and Death | MIT ChemLab Boot Camp 1jDBM9UM9xk 4836 21. Bayesian Statistical Inference I 4UJc0S8APm4 4837 23. Classical Statistical Inference I HIMxdWDLEK8 4838 18. Markov Chains III XtNXQJkgkhI 4839 22. Bayesian Statistical Inference II jsqSScywvMc 4840 14. Poisson Process I -qCEoqpwjf4 4841 6. Discrete Random Variables II 19Ql_Q3l0GA 4842 3. Independence 3MOahpLxj6A 4843 5. Discrete Random Variables I 6oV3pKLgW2I 4844 4. Counting EObHWIEKGjA 4845 7. Discrete Random Variables III P7a4bjE6Crk 4846 12. Iterated Expectations TluTv5V0RmE 4847 2. Conditioning and Bayes' Rule gMTiAeE0NCw 4848 13. Bernoulli Process j9WZyLZCBzs 4849 1. Probability Models and Axioms tBUHRpFZy0s 4850 24. Classical Inference II 3eiio3Tw7UQ 4851 19. Weak Law of Large Numbers CadZXGNauY0 4852 9. Multiple Continuous Random Variables H_k1w3cfny8 4853 10. Continuous Bayes' Rule; Derived Distributions IkbkEtOOC1Y 4854 16. Markov Chains I Tx7zzD4aeiA 4855 20. Central Limit Theorem XsYXACeIklU 4856 15. Poisson Process II ZulMqrvP-Pk 4857 17. Markov Chains II l4NoMKEHQwM 4858 11. Derived Distributions (ctd.); Covariance mHfn_7ym6to 4859 8. Continuous Random Variables rYefUsYuEp0 4860 25. Classical Inference III JV12FObiQ38 4861 Bonus Video 3: It's Complicated | MIT ChemLab Boot Camp t9zBeCrLYE4 4862 8. Serious Business | MIT ChemLab Boot Camp VHnwjl4rYX8 4863 7. Chinese Wedding | MIT ChemLab Boot Camp nAtEwpgQI_E 4864 Bonus Video 2: The Spill | MIT ChemLab Boot Camp tYkr4jMSOFg 4865 6. Crystal Cloudy | MIT ChemLab Boot Camp T8Ydn1eglm8 4866 Bonus Video 1: War Stories | MIT ChemLab Boot Camp IbIqu6wAuQE 4867 5. The Alliances | MIT ChemLab Boot Camp JgMXrmpq1vg 4868 4. Crystal Clear | ChemLab Boot Camp -bbZA_s0hR0 4869 3. Chaplin CMmB8KtbT1U 4870 1. Introduction (21L.011 The Film Experience) JZ19Eot3lPc 4871 2. Keaton Qt8DNIRCYsw 4872 20. Italian neorealism HPh3LjDP_I4 4873 3. Rotovap Mishap | ChemLab Boot Camp Fw92I_zpmRU 4874 2. America in 1850: The Age of Transformation RwDQWPhNZ8U 4875 6. World War I, the 1920s, and the 1930s 3qhlao9T2dA 4876 5. MIT and the corporate world in the age of big business, 1890-1930 QaY9AxkqifQ 4877 3. William Barton Rogers & The Foundational Years, 1861-1896 YKT-vSm4Nxw 4878 10. Aerospace and Computing in the 1960s, Lab Life in the 1970s, The Past Three Decades YfmVSPS7EFI 4879 1. Introduction, Course Overview, What is Technology? ZL0yOsnLDsQ 4880 8. World War II and the Aftermath drFOEAuLspU 4881 4. Harvard, MIT, and Building a New Campus hwQ8RThpXZ4 4882 9. World War II and the Aftermath J0bAFdMzBbs 4883 ChemLab Boot Camp Trailer (HD) 843TkmUy0Yw 4884 2. Overwhelmed | ChemLab Boot Camp 0h8ZTSdgnuA 4885 1. Great Expectations | ChemLab Boot Camp 1towIPbNi8g 4886 Lec 16 | MIT 21M.220 Early Music, Fall 2010 n1fMW_bUWjU 4887 ChemLab Boot Camp Trailer QP57eR40-co 4888 第二次考试例题求解 | MIT 18.06SC 线性代数, 秋 2011 nTM6ktBeiH4 4889 微分方程指数矩阵 (At) | MIT 18.06SC 线性代数, 秋 2011 BDEo4ey9SNQ 4890 行列式和体积 | MIT 18.06SC 线性代数, 秋 2011 clT4rtP9_DQ 4891 行列式 | MIT 18.06SC 线性代数, 秋 2011 tuKjnpYJYew 4892 三维空间的子空间 | MIT 18.06SC 线性代数, 秋 2011 F0HYWmnSSRs 4893 线性代数的几何表示 | MIT 18.06SC 线性代数, 秋 2011 hNDFwVVKVk0 4894 Course Introduction | MIT 18.06SC Linear Algebra EDRa-ESxmJY 4895 8. Addressing Molyneux's Query F0Eq5Lt_fSQ 4896 19. Theories of Consciousness that Neuroscientists Take Seriously FkhU7i8hRK4 4897 12. The Imagery Debate: The Role of the Brain M3F_hAHJzNQ 4898 17. Theories of Consciousness that Neuroscientists Take Seriously mcrGC0KTfnY 4899 5. Are Infants Little Scientists? -AHhHlk8AbI 4900 Biofuels Sub-task Presentation II 1v4uOjgrru4 4901 Lecture 3: Hydrogen and Biofuel Production; Design Process GZ2gWYzCYeI 4902 Lecture 1: Core - Nonconventional (Non-PWR/BWR) Reactors JQtOFKmLOl4 4903 Final Project Presentation _ieUdiazvmA 4904 Core Sub-task Presentation II jXbEfIzdzH4 4905 Lecture 7: Qualitative Optimization of CaC2/Acetylene Block Diagram js34ZxECiCA 4906 Lecture 8: Metals and Cheeses - Uncoventional Pairings nGo9rYqd3Hg 4907 Hydrogen Sub-task Presentation II u9bvzE5Qhjk 4908 Lecture 4: Quality Function Deployment (QFD) and House of Quality uIMVYNzqZL0 4909 Lecture 2: Process Heat - Major Challenges 6rjmzV-Wrvg 4910 Lec 21 | MIT 21L.448J Darwin and Design, Fall 2010 7_N-8cIKjew 4911 Lec 18 | MIT 21L.448J Darwin and Design, Fall 2010 1ItXXlqK6eE 4912 Lec 17 | MIT 21L.448J Darwin and Design, Fall 2010 7eQ4Xt5mAXQ 4913 Lec 16 | MIT 21L.448J Darwin and Design, Fall 2010 7iIkKOSlWoI 4914 Lec 13 | MIT 21L.448J Darwin and Design, Fall 2010 G3OmGH1rvGc 4915 Lec 3 | MIT 21L.448J Darwin and Design, Fall 2010 KS-DHlqHcwo 4916 Lec 12 | MIT 21L.448J Darwin and Design, Fall 2010 NH5DNjFMpWA 4917 Lec 20 | MIT 21L.448J Darwin and Design, Fall 2010 Y7NWOuTjWVw 4918 Lec 5 | MIT 21L.448J Darwin and Design, Fall 2010 h3k4oawOCnw 4919 Lec 4 | MIT 21L.448J Darwin and Design, Fall 2010 sP6ueZ9dJqo 4920 Lec 6 | MIT 21L.448J Darwin and Design, Fall 2010 yMjDJdGTCOk 4921 Lec 7 | MIT 21L.448J Darwin and Design, Fall 2010 ySZtBGAaqbM 4922 Lec 22 | MIT 21L.448J Darwin and Design, Fall 2010 DRYBVzVb_Fg 4923 Lec 2 | MIT 21L.448J Darwin and Design, Fall 2010 N6AbhOVLB9s 4924 Lec 14 | MIT 21L.448J Darwin and Design, Fall 2010 VYOaj9-2CkU 4925 Lec 10 | MIT 21L.448J Darwin and Design, Fall 2010 fW4JKL0AFxA 4926 Lec 1 | MIT 21L.448J Darwin and Design, Fall 2010 kakFvp_WsvI 4927 Lec 11 | MIT 21L.448J Darwin and Design, Fall 2010 pGTaUcG2Woo 4928 Lec 8 | MIT 21L.448J Darwin and Design, Fall 2010 qTmA2LH2vCk 4929 Lec 9 | MIT 21L.448J Darwin and Design, Fall 2010 uyz1UQEu-kk 4930 Lec 15 | MIT 21L.448J Darwin and Design, Fall 2010 7WwuKAvtdq8 4931 Team V1: Body Design (Door, Windshield) IQAqP6SOHhQ 4932 Team M2: Rectenna Design Lm4p4YPC_q0 4933 Team V2: Powertrain - Electric Hub Motor bQrAhaXfSNA 4934 Team M1: m-wave Power Transmission rpWhvQc42qc 4935 Team M4: Mechanical Climber (Weight) 8KQR4NAl3Iw 4936 12. Renewal Rewards, Stopping Trials, and Wald's Inequality ImKFBTqLqdE 4937 19. Countable-state Markov Processes K-iHODiS0-8 4938 22. Random Walks and Thresholds TOvSJkC1nRI 4939 24. Martingales: Stopping and Converging _IDgYAGKyuo 4940 18. Countable-state Markov Chains and Processes fY7NgCWCWoQ 4941 15. The Last Renewal hzJpaNcAoko 4942 20. Markov Processes and Random Walks k2PjTm1JyuI 4943 16. Renewals and Countable-state Markov mq3nFovdG3o 4944 25. Putting It All Together pOhZUJ5BQXk 4945 13. Little, M/G/1, Ensemble Averages pY9ol9So2Yw 4946 14. Review s98jdWi2kEs 4947 17. Countable-state Markov Chains 0aqgeLTNfQ0 4948 7. Finite-state Markov Chains; The Matrix Approach 7CYXy9J4Aao 4949 1. Introduction and Probability Review GCFd0VVnWTw 4950 8. Markov Eigenvalues and Eigenvectors QWHtRR1jMEQ 4951 11. Renewals: Strong Law and Rewards cE6OD7DkCSU 4952 6. From Poisson to Markov ct0QGoi3n4Q 4953 5. Poisson Combining and Splitting d4xfax4_Iww 4954 2. More Review; The Bernoulli Process goT94BheP3E 4955 21. Hypothesis Testing and Random Walks k0UZNZwPO8Q 4956 3. Law of Large Numbers, Convergence mNGVkKeMUtc 4957 9. Markov Rewards and Dynamic Programming qxaBDDib9_A 4958 4. Poisson (the Perfect Arrival Process) uHMVJJHsym4 4959 10. Renewals and the Strong Law of Large Numbers GwVjWQykCDw 4960 23. Martingales (Plain, Sub, and Super) -kD4LUyVmQ0 4961 Chapter 9.4.1 (demo only): Measurement of B-H Characteristic Wlfd5wjFyYw 4962 Chapter 11.7.1 (demo only): Steady State Magnetic Levitation dqrtJb6dj5c 4963 Chapter 13.1.1 (demo only): Visualization of Standing Waves dt5VhUIBY28 4964 Chapter 4.7.1 (demo only): Charge Induced in Ground Plane by Overhead Conductor jPTyYCm4U6Q 4965 Chapter 10.2.1 (demo only): Edgerton's Boomer muXqn76eX0I 4966 Chapter 11.6.2 (demo only): Force on a Liquid Dielectric p_w8KYYXOOU 4967 Chapter 10.0.1 (demo only): Non Uniqueness of Voltage in an Magnetoquasistatic System qp6NzKF3G2M 4968 Chapter 10.7.1 (demo only): Skin Effect vS2LvYwkn3U 4969 Chapter 1.4.1 (demo only): Magnetic Field of a Line Current 4P_3VkNsKho 4970 Chapter 8.6.1 (demo only): Surface Currents Induced in Ground Plane by Overhead Conductor ACDxurDAmyg 4971 Chapter 11.6.2: Force on a liquid dielectric E-AQf4uR_Bw 4972 Chapter 8.5.1 (demo only): Field and Inductance of a Spherical Coil I_w8ruM-mmY 4973 Chapter 8.6.2 (demo only): Inductive Attenuator K-8nCXY-iSI 4974 Chapters 1.3.1, 1.5.1 (demo only): Coulomb's Force Law and Measurements of Charge N46RKNbKf2s 4975 Chapters 1.3.1, 1.5.1: Coulomb's Force Law and Measurements of Charge RDvH76Cj-UY 4976 Chapter 11.7.1: Steady state magnetic levitation RytA_qiN7TY 4977 Chapter 4.7.1: Charge induced in ground plane by overhead conductor TJbHwrjQBxc 4978 Chapter 6.6.1 (demo only): An Artificial Dielectric e6BWg8_PXII 4979 Chapter 7.7.2 (demo only): Electrostatic Precipitation els7niCiJrg 4980 Chapter 7.7.1 (demo only): Relaxation of Charge on Particle in Ohmic Conductor; Van de Graaff fz-jJahvwt8 4981 Chapter 13.1.1: Visualization of standing waves g_HD_17-Msw 4982 Chapter 1.6.1 (demo only): Voltmeter Reading Induced by Magnetic Induction jHSlZ1imn4Y 4983 Chapter 5.5.1 (demo only): Capacitance Attenuator kphOAvHVy0E 4984 Chapter 10.4.1 (demo only): Currents Induced in a Conducting Shell lgFBqG9d9U8 4985 Chapter 7.5.1 (demo only): Distribution of Unpaired Charge oYgN_CVHt0w 4986 Chapter 8.4.1 (demo only): Surface Used to Define the Flux Linkage pXukVix5Pcw 4987 Chapter 9.4.1: Measurement of B-H characteristic plrrHK_cNtM 4988 Chapter 8.2.1 (demo only): Field of a Circular Cylindrical Solenoid s9r4mLOQJuo 4989 Chapter 7.5.2 (demo only): Rotation of an Insulating Rod in a Steady Current wrEcliDbXQk 4990 Chapter 8.2.2 (demo only): Field of Square Pair of Coils 5wfP3GUGeWM 4991 Chapter 8.2.2: Field of square pair of coils AobB_-N_rGM 4992 Chapter 6.6.1: An artificial dielectric DkJnHukpn70 4993 Chapter 7.7.1: Relaxation of charge on particle in Ohmic conductor EGhRQTbtyAQ 4994 Chapter 7.5.2: Rotation of an insulating rod in a steady current KvxNqMMZ-2w 4995 Chapter 7.5.1: Distribution of unpaired charge L0xWTa8D_bw 4996 Chapter 8.5.1: Field and inductance of a spherical coil M6ibQYbbuq8 4997 Chapter 10.2.1: Edgerton's boomer MB63QIKU65s 4998 Chapter 1.6.1: Voltmeter reading induced by magnetic induction UDOw-DUMhX0 4999 Chapter 7.7.1: Supplement: Van de Graaff and Kelvin generators XNDk5YcycVM 5000 Chapter 10.7.1: Skin effect YTm8D0IXBHg 5001 Chapter 8.4.1: Surface used to define the flux linkage YVvg1fDd_u4 5002 Chapter 8.6.1: Surface currents induced in ground plane by overhead conductor Z9ppHdZXJxs 5003 Chapter 5.5.1: Capacitance attenuator aBEZyrqUV28 5004 Chapter 7.7.2: Electrostatic precipitation mOa1fZD9qC4 5005 Chapter 8.6.2: Inductive attenuator mVZ8Sx2wPMI 5006 Chapter 8.2.1: Field of a circular cylindrical solenoid oQUdMleUCTE 5007 Chapter 1.4.1: Magnetic Field of a Line Current u6ud7JD0fV4 5008 Chapter 10.0.1: Non Uniqueness of Voltage in a Magnetoquasistatic System vJ_zJllcKPE 5009 Chapter 10.4.1: Currents induced in a conducting shell ArW8jbDPhcs 5010 Laser fundamentals III: Dye laser induced fluorescence in iodine 4YPxRTFxy2A 5011 Optics: Fraunhofer diffraction - rectangular aperture KtOhRHLE7Q0 5012 Laser fundamentals III: Dye laser excitation of sodium RRi4dv9KgCg 5013 Optics: Destructive interference - Where does the light go? dBMtJEt6aO8 5014 Laser fundamentals I: Light inside and light outside laser jFY3BVXYj_s 5015 Optics: Fraunhofer diffraction - crossed multiple slits FVXkoNuI7bM 5016 Optics: Polarization of Light and Polarization Manipulation; Linear polarizer hJfqUAKMEdw 5017 Optics: Reflection at the air-glass boundary | MIT Video Demonstrations in Lasers and Optics G9kl6-lRHNs 5018 Optics: Optical isolator | MIT Video Demonstrations in Lasers and Optics RiPkBWXAQZE 5019 Laser fundamentals III: Multi-wavelength argon laser | MIT Video Demonstrations in Lasers and Optics YNueJ1Al-CI 5020 Optics: Scattered light in a dielectric | MIT Video Demonstrations in Lasers and Optics _sUVXHfUVsY 5021 Optics: Half-wave plate | MIT Video Demonstrations in Lasers and Optics f8_0AtM7PXk 5022 Optics: Phase shifts in total internal reflection | MIT Video Demonstrations in Lasers and Optics 1cEXNLP5uE0 5023 Overview of Demonstrations in Lasers and Optics | MIT Video Demonstrations in Lasers and Optics 95M4uD6WsSE 5024 Laser fundamentals III: Single-frequency argon laser | MIT Video Demonstrations in Lasers and Optics EBVNbRN805o 5025 Optics: Quarter-wave plate | MIT Video Demonstrations in Lasers and Optics mjwQTL6G8Fs 5026 Laser fundamentals I: Polarization of laser light | MIT Video Demonstrations in Lasers and Optics o1YjIyzshh8 5027 Laser fundamentals II: Laser transverse modes | MIT Video Demonstrations in Lasers and Optics uzXLhTW9wWQ 5028 Optics: Multi-mode fiber | MIT Video Demonstrations in Lasers and Optics zD6tTb74KdU 5029 Optics: Two-beam interference - diverging beams | MIT Video Demonstrations in Lasers and Optics aUF23ZJnN9M 5030 Laser fundamentals II: Laser linewidth | MIT Video Demonstrations in Lasers and Optics cpIVTXNC2s8 5031 Optics: Plane mirror cavity - collimated beams | MIT Video Demonstrations in Lasers and Optics goPg4-iVa1s 5032 Optics: Plane mirror cavity - diverging beams | MIT Video Demonstrations in Lasers and Optics jny_9JMBynU 5033 Laser fundamentals I: Light amplifier | MIT Video Demonstrations in Lasers and Optics kuht5Nv3Iio 5034 Optics: Polarization in a single mode fiber | MIT Video Demonstrations in Lasers and Optics mNFRaM-2cvg 5035 Optics: Reflection at the glass-air boundary | MIT Video Demonstrations in Lasers and Optics Qq_EFXj3wgw 5036 Optics: Fringe contrast - intensity ratio | MIT Video Demonstrations in Lasers and Optics SyEBd_VZXWQ 5037 Laser fundamentals II: Optics of laser beams | MIT Video Demonstrations in Lasers and Optics Vp4udMmeH7M 5038 Laser fundamentals III: Tunable dye laser | MIT Video Demonstrations in Lasers and Optics WyMF3TNm_UU 5039 Laser fundamentals III: High power argon laser | MIT Video Demonstrations in Lasers and Optics _uKBaTKZa6c 5040 Optics: Fringe contrast - polarization difference | MIT Video Demonstrations in Lasers and Optics 45X0puB3YK0 5041 Optics: Single mode fiber | MIT Video Demonstrations in Lasers and Optics 9pD-NW8rsdI 5042 Optics: Fringe contrast - vibrations | MIT Video Demonstrations in Lasers and Optics IZGnYe7BUms 5043 Optics: Fringe contrast - path difference | MIT Video Demonstrations in Lasers and Optics Iqp7NxnwaGY 5044 Laser fundamentals I: Simple laser | MIT Video Demonstrations in Lasers and Optics J4Ecq7hIzYU 5045 Optics: Two-beam interference - collimated beams | MIT Video Demonstrations in Lasers and Optics JYzKNjD1zEU 5046 Laser fundamentals III: Reflection back into laser | MIT Video Demonstrations in Lasers and Optics LixwAXsN8vg 5047 Optics: Coherence length and source spectrum | MIT Video Demonstrations in Lasers and Optics --Zi_cn4kPE 5048 Laser fundamentals I: Spectrum of laser light | MIT Video Demonstrations in Lasers and Optics KlKduOOHukU 5049 Optics: Fraunhofer diffraction - multiple slits | MIT Video Demonstrations in Lasers and Optics PgW7qaOZD0U 5050 Optics: Fraunhofer diffraction - adjustable slit | MIT Video Demonstrations in Lasers and Optics nhAfQ_551xo 5051 Optics: Curved mirror cavity - radial modes | MIT Video Demonstrations in Lasers and Optics rmg1XyOSAk0 5052 Optics: Fraunhofer diffraction - circular apertures | MIT Video Demonstrations in Lasers and Optics x_0TWhJ1nh4 5053 Optics: Fraunhofer diffraction - two slits | MIT Video Demonstrations in Lasers and Optics 1XdKoZKHj5M 5054 Optics: Fraunhofer diffraction - thin wires | MIT Video Demonstrations in Lasers and Optics aEd4FFeBV6U 5055 Optics: Fresnel diffraction - circular apertures | MIT Video Demonstrations in Lasers and Optics mNmvfSK-Dnw 5056 Optics: Optical spectrum analyzer | MIT Video Demonstrations in Lasers and Optics AVn49LbYoB8 5057 Optics: Polarization rotation using polarizers | MIT Video Demonstrations in Lasers and Optics DuPbUcsmNuI 5058 Optics: Fresnel diffraction - adjustable slit | MIT Video Demonstrations in Lasers and Optics 0ZiDIqEkSvw 5059 Class 18: TV Genres | MIT 21L.432 Understanding Television, Spring 2008 f8AdthNxozo 5060 Class 16: TV Genres | MIT 21L.432 Understanding Television, Fall 2001 fJx3baRGjj8 5061 Class 10: TV Genres | MIT 21L.432 Understanding Television, Fall 2001 hoE7pa2RzyQ 5062 Class 1: Introduction | MIT 21L.432 Understanding Television, Spring 2008 2hNfJwfEvkA 5063 Class 5: The Broadcast Era | MIT 21L.432 Understanding Television, Fall 2001 ZleQWZUqoVE 5064 Class 3: Television As A Cultural Form | MIT 21L.432 Understanding Television, Fall 2001 HS27vd1io8M 5065 Tutorial 3: AFM noise Measurement | MIT 20.309 Biological Engineering II, Fall 2006 Tyajd1ZddcQ 5066 Hands-on 2: AFM force spectroscopy | MIT 20.309 Biological Engineering II, Fall 2006 JIjr9CmN5eI 5067 Hands-on 3: AFM noise measurement | MIT 20.309 Biological Engineering II, Fall 2006 juTnY6Wad84 5068 Tutorial 2: More about force spectroscopy | MIT 20.309 Biological Engineering II, Fall 2006 nAPZvX2i7Fw 5069 Tutorial 1: Introduction to the lab AFM | MIT 20.309 Biological Engineering II, Fall 2006 eXusvz0bI4I 5070 Hands-on 1: AFM force spectroscopy | MIT 20.309 Biological Engineering II, Fall 2006 4Q1qQl10bmI 5071 The Merchant of Art UQqTMNJ3q7w 5072 Wedding Song: Henna Art among Pakistani Women in New York City QfuVAKCO61M 5073 1. Introduction to Reflective Practice VE-QUqS7ohs 5074 9. Conceptual Learning IxaTNJh9rXA 5075 2. The Practice of Reflection 9QVLu0n_bzg 5076 4. Theories, Knowledge and Practice AZVum94i7R0 5077 3. Ways of Knowledge Generation MqJW8ABqDpA 5078 6. Frames, Perceptions and Interpretations SsHQjxYJI94 5079 5. Virtual Worlds and Their Role in Creative Work AivFineIBqA 5080 7. Reframing for Resolving Intractable Controversies WbQYpeXWKHI 5081 10. Frontiers of Schön's Approach and Its Relevance in the 21st Century yffHXdEQO08 5082 8. Reframing for Strategic Creativity OK7_ReXhVaQ 5083 Polymerase Chain Reaction (PCR) | MIT 7.01SC Fundamentals of Biology Rn9zldxtZko 5084 Explanation of 5' and 3', C terminus, and N terminus | MIT 7.01SC Fundamentals of Biology SvjeCxVu2dI 5085 Genomic and cDNA Libraries | MIT 7.01SC Fundamentals of Biology 2TL8rY9Rc_A 5086 Lac operon | MIT 7.01SC Fundamentals of Biology LvLbaVW84nE 5087 Complementation (Part II) | MIT 7.01SC Fundamentals of Biology MqNq9S1_Ct8 5088 Lipids, Carbohydrates, and Nucleic Acids Practice Problem | MIT 7.01SC Fundamentals of Biology x_vlxGFrZLY 5089 Transcription & Translation | MIT 7.01SC Fundamentals of Biology K5n0BMKZR_Q 5090 Transformation and Protein Expression | MIT 7.01SC Fundamentals of Biology nCBTC3-xsLM 5091 Covalent Bonds | MIT 7.01SC Fundamentals of Biology qY0ixUWJx0g 5092 Pedigrees | MIT 7.01SC Fundamentals of Biology sAD1Xr3-rmI 5093 Basic Mechanisms of Cloning, excerpt 3 | MIT 7.01SC Fundamentals of Biology uERjKWXO4NQ 5094 Complementation | MIT 7.01SC Fundamentals of Biology 9dHBTckFvME 5095 Mendel's Laws, excerpt 1 | MIT 7.01SC Fundamentals of Biology CT9lYy6qSfg 5096 Mendel's Laws, excerpt 2 | MIT 7.01SC Fundamentals of Biology reYwbnuhFU0 5097 Basic Mechanisms of Cloning, excerpt 2 | MIT 7.01SC Fundamentals of Biology PzY0MWEEE6U 5098 Types of Organisms, Cell Composition, excerpt 1 | MIT 7.01SC Fundamentals of Biology YCeKtM6Hnmc 5099 DNA Structure and Classic experiments, excerpt 2 | MIT 7.01SC Fundamentals of Biology o_1dTvszV4Y 5100 Linkage and Recombination, Genetic maps | MIT 7.01SC Fundamentals of Biology 3edzxv_mYZk 5101 Proteins, Levels of Structure, Non-Covalent Forces, Excerpt 1 | MIT 7.01SC Fundamentals of Biology CdAgzk5tQhs 5102 Basic Mechanisms of Cloning, excerpt 1 | MIT 7.01SC Fundamentals of Biology DRBREvFL19g 5103 DNA Replication | MIT 7.01SC Fundamentals of Biology P-Ry4rRdDbk 5104 DNA Structure and Classic experiments, excerpt 1 | MIT 7.01SC Fundamentals of Biology uDXH6Uu0ghc 5105 Overview of Recombinant DNA, excerpt 1 | MIT 7.01SC Fundamentals of Biology ojrj-UVh9N4 5106 Macromolecules: Lipids, Carbohydrates, Nucleic Acid, Excerpt 2 | MIT 7.01SC Fundamentals of Biology tMr9XH64rtM 5107 Transcription and Translation, excerpt 1 | MIT 7.01SC Fundamentals of Biology uBRdfsz_YB4 5108 Transcription and Translation, excerpt 2 | MIT 7.01SC Fundamentals of Biology zLGHH9Rwvlw 5109 Types of Organisms, Cell Composition, excerpt 2 | MIT 7.01SC Fundamentals of Biology OBloWTHFPZc 5110 Biochemical Reactions, Enzymes, and ATP | MIT 7.01SC Fundamentals of Biology SxaoWJ2gkzc 5111 Photosynthesis | MIT 7.01SC Fundamentals of Biology htYyCEdc8B4 5112 Overview of Recombinant DNA | MIT 7.01SC Fundamentals of Biology pJDHi91yAaE 5113 Covalent Bonds, Hydrogen Bonds | MIT 7.01SC Fundamentals of Biology 0ZxeQqtAVl0 5114 Glycolysis, Respiration, and Fermentation | MIT 7.01SC Fundamentals of Biology QTb6YsxMbBY 5115 Agarose Gel Electrophoresis, DNA Sequencing, PCR, Excerpt 2 | MIT 7.01SC Fundamentals of Biology YnF1b_Kqf88 5116 Agarose Gel Electrophoresis, DNA Sequencing, PCR, Excerpt 1 | MIT 7.01SC Fundamentals of Biology zQfcPQpKZUk 5117 cDNA Libraries and Expression Libraries | MIT 7.01SC Fundamentals of Biology 1eGsdK1fPLM 5118 Macromolecules: Lipids, Carbohydrates, Nucleic Acid, Excerpt 1 | MIT 7.01SC Fundamentals of Biology BIIWlZqWxKg 5119 Constructing and Screening a Recombinant DNA Library | MIT 7.01SC Fundamentals of Biology TnpCMgtDPgk 5120 Alternative Approaches to Molecular Biology | MIT 7.01SC Fundamentals of Biology syXplPKQb_o 5121 Lec 2 | MIT 9.00SC Introduction to Psychology, Spring 2011 v4ur5mna060 5122 Lec 5 | MIT 9.00SC Introduction to Psychology, Spring 2011 -cK1og4ElKE 5123 Lec 4 | MIT 9.00SC Introduction to Psychology, Spring 2011 2fbrl6WoIyo 5124 Lec 1 | MIT 9.00SC Introduction to Psychology, Spring 2011 SjjGiqf96rI 5125 Lec 3 | MIT 9.00SC Introduction to Psychology, Spring 2011 lBU64nfe8nM 5126 Lec 7 | MIT 9.00SC Introduction to Psychology, Spring 2011 MYMYXhR2Ppw 5127 Lec 6 | MIT 9.00SC Introduction to Psychology, Spring 2011 lanmHS0JwYI 5128 Lec 22 | MIT 9.00SC Introduction to Psychology, Spring 2011 zPPsdsAQBx4 5129 Lec 23 | MIT 9.00SC Introduction to Psychology, Spring 2011 t73rjeOj0eY 5130 Lec 15 | MIT 9.00SC Introduction to Psychology, Spring 2011 vf1U3Nt3HQk 5131 Lec 24 | MIT 9.00SC Introduction to Psychology, Spring 2011 z9XQpjNgeBI 5132 Lec 19 | MIT 9.00SC Introduction to Psychology, Spring 2011 Vko17una2Zw 5133 Lec 16 | MIT 9.00SC Introduction to Psychology, Spring 2011 gRe7dy2HSTg 5134 Lec 12 | MIT 9.00SC Introduction to Psychology, Spring 2011 qZdm4mpQA_8 5135 Lec 13 | MIT 9.00SC Introduction to Psychology, Spring 2011 SFPPw6sDHEI 5136 Lec 21 | MIT 9.00SC Introduction to Psychology, Spring 2011 SBrCPDC21f4 5137 Lec 9 | MIT 9.00SC Introduction to Psychology, Spring 2011 kD3CswjYb2E 5138 Lec 11 | MIT 9.00SC Introduction to Psychology, Spring 2011 76O3rulk844 5139 Lec 10 | MIT 9.00SC Introduction to Psychology, Spring 2011 yBYebcVw8Zk 5140 Lec 17 | MIT 9.00SC Introduction to Psychology, Spring 2011 QvK6YdFKMY8 5141 Lec 8 | MIT 9.00SC Introduction to Psychology, Spring 2011 Qw4SkvZ03cc 5142 Lec 18 | MIT 9.00SC Introduction to Psychology, Spring 2011 bihrpOS0qtY 5143 Lec 14 | MIT 9.00SC Introduction to Psychology, Spring 2011 SXzdOK_J-xE 5144 Lec 20 | MIT 9.00SC Introduction to Psychology, Spring 2011 JNsNgXKFgdo 5145 Exploration of the Amplitude and Phase: First Order Applet TxG1iPXznBs 5146 Exploration of the Isoclines Applet Gb5o6VNboV0 5147 Exploration of the Damped Vibrations Applet JbuG6u2ko_0 5148 Exploration of the Convolution Accumulation Applet Wz1d0rHn_fU 5149 Exploration of the Euler's Method Applet d521hz0sGtE 5150 Exploration of the Phase Lines Applet pDfQHohL4Xs 5151 Exploration of the Fourier Coefficient Applet R_8beV_gXHc 5152 Exploration of the Amplitude and Phase: Second Order II Applet KJnAy6hzetw 5153 Lecture 1, Introduction | MIT RES.6.007 Signals and Systems, Spring 2011 Q7aZNgY18b4 5154 Lecture 18, Discrete-Time Processing of Continuous-Time Signals | MIT RES.6.007 Signals and Systems mC3TiBJiCsY 5155 Lecture 5, Properties of Linear, Time-invariant Systems | MIT RES.6.007 Signals and Systems ZYf0tz9oVz8 5156 Part III: Linear Algebra, Lec 8: Orthogonal Functions anA3P9McG5Y 5157 Part III: Linear Algebra, Lec 7: Dot Products Bk9SZMsPEHk 5158 Part III: Linear Algebra, Lec 6: Eigenvectors 6UXba5MKsfc 5159 Part III: Linear Algebra, Lec 4: Linear Transformations CEbrxYGpfZY 5160 Part III: Linear Algebra, Lec 5: Determinants KvQkRX1nIqQ 5161 Part III: Linear Algebra, Lec 1: Vector Spaces anICA1XFJ_M 5162 Part III: Linear Algebra, Lec 2: Spanning Vectors l59IX58Wce8 5163 Part III: Linear Algebra, Lec 3: Constructing Bases IYKULUq6YPQ 5164 Part II: Differential Equations, Lec 5: Variations of Parameters IkpQJSDK940 5165 Part II: Differential Equations, Lec 2: Linear Differential Equations an5E940fqZQ 5166 Part II: Differential Equations, Lec 7: Laplace Transforms dzKnv4ntH2g 5167 Part II: Differential Equations, Lec 4: Undetermined Coefficients oY0ItxI9xTk 5168 Part II: Differential Equations, Lec 6: Power Series Solutions DJO6ilwbWiI 5169 Part II: Differential Equations, Lec 3: Solving the Linear Equations L(y) = 0; Constant Coefficients GQKFkoy4VOw 5170 Part II: Differential Equations, Lec 1: The Concept of a General Solution gpZu5N1FFq0 5171 Part I: Complex Variables, Lec 5: Integrating Complex Functions BOx8LRyr8mU 5172 Part I: Complex Variables, Lec 1: The Complex Numbers UGiED1HPB08 5173 Part I: Complex Variables, Lec 4: Sequences and Series rVvGqWyQB_0 5174 Part I: Complex Variables, Lec 2: Functions of a Complex Variable s1DFa1dCss0 5175 Part I: Complex Variables, Lec 3: Conformal Mappings 0DCrIAxEv_Y 5176 Fiberoptics Fundamentals | MIT Understanding Lasers and Fiberoptics _qixt0NLc9I 5177 Laser Fundamentals III | MIT Understanding Lasers and Fiberoptics saVE7pMhaxk 5178 Laser Fundamentals I | MIT Understanding Lasers and Fiberoptics slNPMzQ4Nhw 5179 Laser Fundamentals III (cont.) | MIT Understanding Lasers and Fiberoptics urbZ8CTceu0 5180 Laser Fundamentals II | MIT Understanding Lasers and Fiberoptics 0Uz-TR_vZKs 5181 Part II: Vector Calculus, Lec 4 | MIT Calculus Revisited: Multivariable Calculus 2PpgEtgovN0 5182 Part V: Multiple Integration, Lec 2 | MIT Calculus Revisited: Multivariable Calculus Brmq13Waa_Y 5183 Part I: Vector Arithmetic, Lec 6 | MIT Calculus Revisited: Multivariable Calculus CxUEyN4exSg 5184 Part V: Multiple Integration, Lec 1 | MIT Calculus Revisited: Multivariable Calculus JAxRgACOQtA 5185 Part I: Vector Arithmetic, Lec 3 | MIT Calculus Revisited: Multivariable Calculus JSs_dqq2uWo 5186 Part III: Partial Derivatives, Lec 4 | MIT Calculus Revisited: Multivariable Calculus MfN1lqArwAg 5187 Part IV: Matrix Algebra, Lec 1 | MIT Calculus Revisited: Multivariable Calculus NG9hkGQwT3k 5188 Part II: Vector Calculus, Lec 1 | MIT Calculus Revisited: Multivariable Calculus Oc3ERNBhqGo 5189 Part V: Multiple Integration, Lec 4 | MIT Calculus Revisited: Multivariable Calculus Rvnv3bPDCs8 5190 Part III: Partial Derivatives, Lec 6 | MIT Calculus Revisited: Multivariable Calculus SFB2Fxel6iM 5191 Part III: Partial Derivatives, Lec 3 | MIT Calculus Revisited: Multivariable Calculus UGKL1wHouho 5192 Part III: Partial Derivatives, Lec 2 | MIT Calculus Revisited: Multivariable Calculus YeZ0J9Hxgb0 5193 Part V: Multiple Integration, Lec 3 | MIT Calculus Revisited: Multivariable Calculus Yw8vBDhVs8o 5194 Part I: Vector Arithmetic, Lec 5 | MIT Calculus Revisited: Multivariable Calculus ZyhCnulIApY 5195 Part II: Vector Calculus, Lec 3 | MIT Calculus Revisited: Multivariable Calculus __NxbJzEMCU 5196 Part III: Partial Derivatives, Lec 5 | MIT Calculus Revisited: Multivariable Calculus a-w4F0c57nE 5197 Part IV: Matrix Algebra, Lec 4 | MIT Calculus Revisited: Multivariable Calculus bBKzHydIl2c 5198 Part V: Multiple Integration, Lec 5 | MIT Calculus Revisited: Multivariable Calculus f93PZ9ZyvDk 5199 Part II: Vector Calculus, Lec 2 | MIT Calculus Revisited: Multivariable Calculus io8kTsSnOdE 5200 Part IV: Matrix Algebra, Lec 5 | MIT Calculus Revisited: Multivariable Calculus nFf_SJRwfaY 5201 Part I: Vector Arithmetic, Lec 2 | MIT Calculus Revisited: Multivariable Calculus rRCN5542U7E 5202 Part IV: Matrix Algebra, Lec 2 | MIT Calculus Revisited: Multivariable Calculus sSuZn6KHLnU 5203 Part III: Partial Derivatives, Lec 1 | MIT Calculus Revisited: Multivariable Calculus sZh-zowKEQQ 5204 Part IV: Matrix Algebra, Lec 3 | MIT Calculus Revisited: Multivariable Calculus wsOoClvZmic 5205 Part I: Vector Arithmetic, Lec 1 | MIT Calculus Revisited: Multivariable Calculus y9Sa8StSX-M 5206 Part I: Vector Arithmetic, Lec 4 | MIT Calculus Revisited: Multivariable Calculus WbWb0u8bJrU 5207 Lec 6 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 bX3jvD7XFPs 5208 Lec 1 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 ggxY20cXql8 5209 Lec 3 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 5gt2WDBl8-0 5210 Lec 7 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 6wTuOMgTrU4 5211 Lec 9 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 A2WFReES8CY 5212 Lec 26 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 B8is52oxHBw 5213 Lec 5 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 BRjwkgQct28 5214 Lec 18 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 C2BBAW78fYg 5215 Lec 12 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 FBpe3xFvPrQ 5216 Lec 11 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 GmkRmETGghw 5217 Lec 8 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 Iu4xTLKcbPo 5218 Lec 20 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 K1w2o5i0NGQ 5219 Lec 24 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 Mx0uXIBD-yA 5220 Lec 4 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 Q148jV9ljPM 5221 Lec 16 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 SLvTCHhu5SE 5222 Lec 2 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 TIQTYgmavC4 5223 Lec 17 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 UiZlaJX3IRk 5224 Lec 21 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 VqZBqoZgL7k 5225 Lec 15 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 aqd0sR5rygk 5226 Lec 25 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 ddtobc-AOK4 5227 Lec 14 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 hGQw3KJ7i6Q 5228 Lec 13 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 hmtXhZTfAes 5229 Lec 22 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 lFngfmE9RCc 5230 Lec 23 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 miw2CiKp1r0 5231 Lec 19 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 pjLbxB9TXJs 5232 Lec 10 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 yVkt3Px4KHA 5233 Rec 6 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 7BpomdjZ_Os 5234 Rec 4 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 88fqFjfxgwI 5235 Rec 1 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 AKDkrI6BCcw 5236 Quiz 2 Review Session | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 FBKxrPEeCSU 5237 Rec 7 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 Fixc8hVo_cY 5238 Rec 3 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 UHRhUufAlE4 5239 Rec 8 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 ZFc_utdoexI 5240 Rec 5 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 _QnAUd-em3E 5241 Rec 9 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 nx6NnzIGrKE 5242 Rec 2 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 rM3shFQyieU 5243 Rec 10 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 8I0BmT1ccuw 5244 Optional Recitation | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 StbJIv49Aco 5245 Course Introduction | MIT 18.085 Computational Science and Engineering I, Fall 2008 H3_TYEeswuM 5246 Lec 22 | MIT 14.01SC Principles of Microeconomics ni0aX0tUAd0 5247 Lec 24 | MIT 14.01SC Principles of Microeconomics kEJf57FF0Vs 5248 Lec 23 | MIT 14.01SC Principles of Microeconomics jmsPn679o5k 5249 Lec 15 | MIT 14.01SC Principles of Microeconomics eeauylMvOvA 5250 Lec 21 | MIT 14.01SC Principles of Microeconomics pmolioUklXI 5251 Lec 26 | MIT 14.01SC Principles of Microeconomics MfoAkzgpaoQ 5252 Lec 17 | MIT 14.01SC Principles of Microeconomics IuQjBqzmUKA 5253 Lec 18 | MIT 14.01SC Principles of Microeconomics oju-1Ogh1ks 5254 Lec 19 | MIT 14.01SC Principles of Microeconomics RFTa52F8YZ0 5255 Lec 25 | MIT 14.01SC Principles of Microeconomics f8Kn9GkR514 5256 Lec 20 | MIT 14.01SC Principles of Microeconomics e3Bsb1mELcc 5257 Lec 16 | MIT 14.01SC Principles of Microeconomics jDnoR7IF_eY 5258 Lec 10 | MIT 14.01SC Principles of Microeconomics WbE2USh7RKI 5259 Lec 14 | MIT 14.01SC Principles of Microeconomics Vss3nofHpZI 5260 Lec 1 | MIT 14.01SC Principles of Microeconomics TIWE0DaOlzU 5261 Lec 5 | MIT 14.01SC Principles of Microeconomics Q4iKuKAjzK0 5262 Lec 9 | MIT 14.01SC Principles of Microeconomics 9kH0x7V_0Ig 5263 Lec 4 | MIT 14.01SC Principles of Microeconomics yCd_OSJmtfg 5264 Lec 6 | MIT 14.01SC Principles of Microeconomics LpNKCJSZk_k 5265 Lec 13 | MIT 14.01SC Principles of Microeconomics Ye4vL7u6N2g 5266 Lec 3 | MIT 14.01SC Principles of Microeconomics A6FOBdtbcz4 5267 Lec 8 | MIT 14.01SC Principles of Microeconomics zeU8i3pxX9g 5268 Lec 11 | MIT 14.01SC Principles of Microeconomics zFIB8-30YhA 5269 Lec 2 | MIT 14.01SC Principles of Microeconomics -5XT0Mzl72E 5270 Lec 7 | MIT 14.01SC Principles of Microeconomics 1jLfD9ulntU 5271 Lec 12 | MIT 14.01SC Principles of Microeconomics aflMMnyAO0E 5272 Lec 8a | MIT 14.01SC Principles of Microeconomics Offa8tyTRQE 5273 Problem Set 5, Problem #4e-h | MIT 14.01SC Principles of Microeconomics qRkAq_G_9cs 5274 Problem Set 4, Problem #3 | MIT 14.01SC Principles of Microeconomics 35QyfmSFTZw 5275 Problem Set 1, Problem #3 | MIT 14.01SC Principles of Microeconomics FWkzErtrlIw 5276 Problem Set 8, Problem #2a-b | MIT 14.01SC Principles of Microeconomics WmnViAaMdGM 5277 Problem Set 2, Problem #4 | MIT 14.01SC Principles of Microeconomics 1dL8mTyyjRM 5278 Problem Set 3, Problem #5 | MIT 14.01SC Principles of Microeconomics xqmb6D2CpRc 5279 Problem Set 7, Problem #2a-e | MIT 14.01SC Principles of Microeconomics WRuAAoyEmY0 5280 Problem Set 1, Problem #4 | MIT 14.01SC Principles of Microeconomics O7IwAlval_0 5281 Problem Set 6, Problem #3 | MIT 14.01SC Principles of Microeconomics DZHguXpwuXU 5282 Problem Set 6, Problem #4 | MIT 14.01SC Principles of Microeconomics 4j8mTdmATVg 5283 Introduction | MIT 14.01SC Principles of Microeconomics rjAXFBWJt_o 5284 Frequency Response | MIT 18.03SC Differential Equations, Fall 2011 XbiEUwVQqVM 5285 Homogeneous Constant Coefficient Equations: Any Roots | MIT 18.03SC Differential Equations zNPK_t03zds 5286 Homogeneous Constant Coefficient Equations: Real Roots | MIT 18.03SC Differential Equations xMWcIb6XGVA 5287 Lec 12 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 e7Ptvu5Vu8k 5288 Lec 8 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 3S4cNfl0YF0 5289 Lec 1 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 FANl3evX0FQ 5290 Lec 9 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 CG4ihzTaGdM 5291 Lec 3 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 cQntMUMQyRw 5292 Lec 2 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 u_x67-kaedM 5293 Lec 10 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 5sLFTc10kg8 5294 Lec 7 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 oTNwGuI7Wic 5295 Lec 6 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 qB5wq5L6EL4 5296 Lec 5 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 vcDBNyKvLcs 5297 Lec 13 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 -kkocTdn0iY 5298 Ted Carr Guest Lecture | MIT MAS.771: Autism Theory and Technology, Spring 2011 _Fo3Jq1blKk 5299 Linear Systems of Equations | MIT 18.03SC Differential Equations, Fall 2011 BwIZ0VzKEDg 5300 First-order Constant Coefficient Linear ODE's | MIT 18.03SC Differential Equations, Fall 2011 jzzpxqVohhI 5301 Computing Fourier Series | MIT 18.03SC Differential Equations, Fall 2011 pGECDB15L9o 5302 Undetermined Coefficients | MIT 18.03SC Differential Equations, Fall 2011 oEskbXrhkkk 5303 Trace-Determinant Diagram | MIT 18.03SC Differential Equations, Fall 2011 q0PxCQWG3ic 5304 Step and Delta Functions | MIT 18.03SC Differential Equations, Fall 2011 zmzyW1rP-hk 5305 Phase Portraits | MIT 18.03SC Differential Equations, Fall 2011 qbyeQum8qTE 5306 Matrix Exponentials | MIT 18.03SC Differential Equations, Fall 2011 IrRgAWI6bmw 5307 Linear Equations | MIT 18.03SC Differential Equations, Fall 2011 TRVS5Wo9LoM 5308 Linear Systems: Complex Roots | MIT 18.03SC Differential Equations, Fall 2011 fkGAF5jHjdY 5309 Sinusoidal Inputs | MIT 18.03SC Differential Equations, Fall 2011 YUjdyKhWt6E 5310 Linear Systems: Matrix Methods | MIT 18.03SC Differential Equations, Fall 2011 LjqUV6vqwkg 5311 Unit Step and Impulse Response | MIT 18.03SC Differential Equations, Fall 2011 5av3kiejazQ 5312 Laplace: Solving ODE's | MIT 18.03SC Differential Equations, Fall 2011 4gJLEYc3p5w 5313 Solutions of First-order Linear Equations | MIT 18.03SC Differential Equations, Fall 2011 xJz3NZap1lw 5314 Forced Oscillations | MIT 18.03SC Differential Equations, Fall 2011 UCpMao94iFg 5315 Linearization | MIT 18.03SC Differential Equations, Fall 2011 wwfjLBWfiSI 5316 Gain and Phase Lag | MIT 18.03SC Differential Equations, Fall 2011 RzaB0t9dx0A 5317 Pure Resonance | MIT 18.03SC Differential Equations, Fall 2011 elMskF8Uzmg 5318 Autonomous Equations and Phase Lines | MIT 18.03SC Differential Equations, Fall 2011 2IBWxERRjvM 5319 Sinusoidal Functions | MIT 18.03SC Differential Equations, Fall 2011 v4YcejwdQC0 5320 Manipulating Fourier Series | MIT 18.03SC Differential Equations, Fall 2011 -0_vZ4t-q0I 5321 Linear ODE's with Periodic Input | MIT 18.03SC Differential Equations, Fall 2011 pUFSXhoazY8 5322 Pole Diagrams | MIT 18.03SC Differential Equations, Fall 2011 2-5oq-igwtU 5323 Damped Harmonic Oscillators | MIT 18.03SC Differential Equations, Fall 2011 X5-ucBtneVM 5324 Euler's Method | MIT 18.03SC Differential Equations, Fall 2011 BniJM-ireXQ 5325 Laplace Transform: Basics | MIT 18.03SC Differential Equations, Fall 2011 sn3orkHWqUQ 5326 Complex Numbers and Euler's Formula | MIT 18.03SC Differential Equations, Fall 2011 IGk-7EKR35A 5327 Convolution and Green's Formula | MIT 18.03SC Differential Equations, Fall 2011 D6Rd1K93nSA 5328 Partial Fractions and Laplace Inverse | MIT 18.03SC Differential Equations, Fall 2011 jOBBwI4CYjM 5329 Direction Fields | MIT 18.03SC Differential Equations, Fall 2011 76WdBlGpxVw 5330 Separable Equations | MIT 18.03SC Differential Equations, Fall 2011 hlXjQ4qtaYU 5331 Sonorous Currents | MIT 21M.380 Music and Technology, Spring 2011 dZfdKXxhnTM 5332 Differential Equations and exp (At) | MIT 18.06SC Linear Algebra, Fall 2011 FoI57cdSWM0 5333 An Overview of Key Ideas | MIT 18.06SC Linear Algebra, Fall 2011 QleELaAfTd4 5334 Rec 8 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 8FWfmvj3HYw 5335 Rec 4 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 UGdXwvB6K-w 5336 Rec 13 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 Y9r9dO7KQj4 5337 Rec 3 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 O6HHjiNKsco 5338 Rec 5 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 qGZy1CRoZdE 5339 Rec 9 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 J09o6QRVsfw 5340 Rec 16 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 l0tUtVRhmDs 5341 Rec 6 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 sNLB6_ZIfX0 5342 Rec 11 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 hdjWA3YcDII 5343 Rec 1 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 SpS3ud58yTI 5344 Rec 14 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 yWQYXEjxAnk 5345 Rec 15 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 dAZ-i9MsbRM 5346 Rec 10 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 abW4cppRABM 5347 Rec 2 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 rOA1VC5aQ7Q 5348 Rec 12 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 lF-7mmPHhG0 5349 Rec 7 | MIT 6.01SC Introduction to Electrical Engineering and Computer Science I, Spring 2011 tp0BuVRIUUU 5350 Final Exam Problem Solving | MIT 18.06SC Linear Algebra, Fall 2011 u9J5-LcYYeg 5351 Determinants and Volume | MIT 18.06SC Linear Algebra, Fall 2011 xhP2m3wwRTc 5352 Matrix Spaces | MIT 18.06SC Linear Algebra, Fall 2011 F7H6Ko0KL0Y 5353 Exam #1 Problem Solving | MIT 18.06SC Linear Algebra, Fall 2011 UNUrfM30DTk 5354 Exam #2 Problem Solving | MIT 18.06SC Linear Algebra, Fall 2011 eJqreNZPS64 5355 Least Squares Approximation | MIT 18.06SC Linear Algebra, Fall 2011 0-6a1SuihXM 5356 Powers of a Matrix | MIT 18.06SC Linear Algebra, Fall 2011 DaHJqeTDN1M 5357 Exam #3 Problem Solving | MIT 18.06SC Linear Algebra, Fall 2011 Ehteu_SG3tI 5358 Change of Basis | MIT 18.06SC Linear Algebra, Fall 2011 tccVVUnLdbc 5359 Positive Definite Matrices and Minima | MIT 18.06SC Linear Algebra, Fall 2011 Stn_otuhumU 5360 Symmetric Matrices and Positive Definiteness | MIT 18.06SC Linear Algebra, Fall 2011 N74V4CBO0sk 5361 Pseudoinverses | MIT 18.06SC Linear Algebra, Fall 2011 xCIXkm3-ocQ 5362 Elimination with Matrices | MIT 18.06SC Linear Algebra, Fall 2011 uNKDw46_Ev4 5363 Geometry of Linear Algebra | MIT 18.06SC Linear Algebra, Fall 2011 -X04WJoTDBc 5364 Linear Transformations | MIT 18.06SC Linear Algebra, Fall 2011 aKX5_DucNq8 5365 Properties of Determinants | MIT 18.06SC Linear Algebra, Fall 2011 75Q0ZN2njGQ 5366 Solving Ax=b | MIT 18.06SC Linear Algebra, Fall 2011 LttE1vDVrm0 5367 Solving Ax=0 | MIT 18.06SC Linear Algebra, Fall 2011 _GT4SZibf5E 5368 Orthogonal Vectors and Subspaces | MIT 18.06SC Linear Algebra, Fall 2011 eKlM1XRS3mg 5369 Vector Subspaces | MIT 18.06SC Linear Algebra, Fall 2011 efmjZq8qfqg 5370 Complex Matrices | MIT 18.06SC Linear Algebra, Fall 2011 3SkCNpFOshk 5371 Subspaces of Three Dimensional Space | MIT 18.06SC Linear Algebra, Fall 2011 nnssRe5DewE 5372 Markov Matrices | MIT 18.06SC Linear Algebra, Fall 2011 tZw_eux9Wno 5373 Projection into Subspaces | MIT 18.06SC Linear Algebra, Fall 2011 hisFn3gtnpg 5374 Graphs and Networks | MIT 18.06SC Linear Algebra, Fall 2011 TRktLuAktBQ 5375 Gram-Schmidt Orthogonalization | MIT 18.06SC Linear Algebra, Fall 2011 UZQGn1L2CzQ 5376 Determinants | MIT 18.06SC Linear Algebra, Fall 2011 cOUTpqlX-Xs 5377 Computing the Singular Value Decomposition | MIT 18.06SC Linear Algebra, Fall 2011 rhNKncraJMk 5378 LU Decomposition | MIT 18.06SC Linear Algebra, Fall 2011 ighcncy6qQ8 5379 Eigenvalues and Eigenvectors | MIT 18.06SC Linear Algebra, Fall 2011 CBi8SyXRn1Q 5380 Inverse Matrices | MIT 18.06SC Linear Algebra, Fall 2011 cU8uBaOfIuc 5381 Similar Matrices | MIT 18.06SC Linear Algebra, Fall 2011 7naSckRdOJM 5382 Computing the Four Fundamental Subspaces | MIT 18.06SC Linear Algebra, Fall 2011 AqXOYgpbMBM 5383 Basis and Dimension | MIT 18.06SC Linear Algebra, Fall 2011 SMnPZzlgtXU 5384 Lec 6 | MIT RES.6-008 Digital Signal Processing, 1975 xwRn_lTA6JY 5385 Lec 11 | MIT RES.6-008 Digital Signal Processing, 1975 JtJ3v__Rx7E 5386 Lec 16 | MIT RES.6-008 Digital Signal Processing, 1975 rF5sEfhttwo 5387 Lec 9 | MIT RES.6-008 Digital Signal Processing, 1975 AsSsGjaBbas 5388 Lec 13 | MIT RES.6-008 Digital Signal Processing, 1975 XT6o4IRTcLk 5389 Lec 3 | MIT RES.6-008 Digital Signal Processing, 1975 xRLaQ4My3ms 5390 Lec 20 | MIT RES.6-008 Digital Signal Processing, 1975 14Vg7GyCVLY 5391 Lec 18 | MIT RES.6-008 Digital Signal Processing, 1975 _KbfL3lVgag 5392 Lec 10 | MIT RES.6-008 Digital Signal Processing, 1975 mUpwOQ0w2vk 5393 Lec 12 | MIT RES.6-008 Digital Signal Processing, 1975 LrNXtw0E7Dk 5394 Lec 7 | MIT RES.6-008 Digital Signal Processing, 1975 oJv4dsUID0Q 5395 Lec 17 | MIT RES.6-008 Digital Signal Processing, 1975 dHveJh0UbY8 5396 Lec 4 | MIT RES.6-008 Digital Signal Processing, 1975 4Gy1mik0tr4 5397 Lec 19 | MIT RES.6-008 Digital Signal Processing, 1975 TuCYGjp7WKU 5398 Lec 2 | MIT RES.6-008 Digital Signal Processing, 1975 n9u9Vy_peHM 5399 Lec 8 | MIT RES.6-008 Digital Signal Processing, 1975 I9u15zdgJvI 5400 Lec 5 | MIT RES.6-008 Digital Signal Processing, 1975 U13m6L6R58w 5401 Lec 14 | MIT RES.6-008 Digital Signal Processing, 1975 ZbYAZLQHXSg 5402 Lec 15 | MIT RES.6-008 Digital Signal Processing, 1975 rkvEM5Y3N60 5403 Lec 1 | MIT RES.6-008 Digital Signal Processing, 1975 zBJMh-m9b1E 5404 Demonstration 1: Sampling OQNR099y8mM 5405 Demonstration 2: Sampling 2fjZhoifOiM 5406 Lec 3 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 _40zvhkmtM8 5407 Lec 12 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 xc9DDSbf0NQ 5408 Lec 2 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 F8yY7jri32M 5409 Lec 14 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 nukI0huUEiM 5410 Industry mentor overview | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 9Rb85cOXTKU 5411 Lec 19 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 n_Cqx8KamFA 5412 Lec 16 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 UUKTIhxznF0 5413 Lec 13 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 MFmxByf9x88 5414 Lec 17 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 l8GqOCN8M-w 5415 Lec 7 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 8dTMUigqBHM 5416 Lec 4 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 HH1k11sdlTc 5417 Lec 11 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 CxuZZcUKxWM 5418 Lec 9 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 GOlurMtkuWQ 5419 Lec 6 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 JzpkXLH9zLQ 5420 Lec 1 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 p0bc1f6ULxw 5421 Lec 10 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 gXRmNp4Wgb0 5422 Lec 15 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 T9LkSKK075M 5423 Lec 8 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 c45ieqaUU4k 5424 Lec 18 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 Ahnns47FKHM 5425 Lec 22 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 dvPJj-5X_uU 5426 Lec 23 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 sGFEsAphyLo 5427 Lec 20 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 ajXDBKIJsJ8 5428 Lec 21 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 7a89iFEEpTo 5429 Lec 5 | MIT 6.172 Performance Engineering of Software Systems, Fall 2010 JGgzgqIGgk0 5430 Day 5 | MIT 2.993 The Art and Science of Boat Design, IAP 2007 sKZfwhrf81I 5431 Day 1 Part 2 | MIT 2.993 The Art and Science of Boat Design, IAP 2007 XDsfydo1gkM 5432 Day 4 | MIT 2.993 The Art and Science of Boat Design, IAP 2007 izS-pGXFnrc 5433 Day 1 Part 1 | MIT 2.993 The Art and Science of Boat Design, IAP 2007 RiQNhZ1P9qs 5434 Day 2 | MIT 2.993 The Art and Science of Boat Design, IAP 2007 kqeTXnkLp78 5435 Lec 1 | MIT 4.367 Studio Seminar in Public Art, Spring 2006 c0fmG26jk7g 5436 Lec 2 | MIT 4.367 Studio Seminar in Public Art, Spring 2006 4UZD-arBlzg 5437 Lec 3 | MIT 4.367 Studio Seminar in Public Art, Spring 2006 PHkQ5u8omK4 5438 Welcome and Keynote with Tim O'Reilly V2s0SnknrtA 5439 Inaugural Awards for OpenCourseWare Excellence Waiy7Q96I1w 5440 Early OpenCourseWare Adopters gXJa7YutKfM 5441 MIT's Institutional Decision to do OpenCourseWare 5QHc0RK0FxA 5442 Course Introduction | MIT ESD.932 Engineering Ethics, Spring 2006 P7tCdhvhIKU 5443 Session 1 | MIT 24.264 Film as Visual and Literary Mythmaking, Fall 2005 vJnXKcHUzHM 5444 Session 1 | MIT 24.263 The Nature of Creativity, Fall 2005 9JXMg32f09w 5445 MIT 3.60 | Lec 10a: Symmetry, Structure, Tensor Properties of Materials YjUOaNbLnn0 5446 Sample Lecture M15 | MIT Unified Engineering, Fall 2005 jGk3w1b7UXQ 5447 Lecture 3, Signals and Systems: Part II | MIT RES.6.007 Signals and Systems, Spring 2011 6xaaeop7gJ8 5448 Lecture 2, Signals and Systems: Part 1 | MIT RES.6.007 Signals and Systems, Spring 2011 3UkGd3LK2NY 5449 Lecture 8, Continuous-Time Fourier Transform | MIT RES.6.007 Signals and Systems, Spring 2011 nuzA75DpSuw 5450 Lecture 7, Continuous-Time Fourier Series | MIT RES.6.007 Signals and Systems, Spring 2011 c6jKux_RkqI 5451 Lecture 6, Systems Represented by Differential Equations | MIT RES.6.007 Signals and Systems _vyke3vF4Nk 5452 Lecture 4, Convolution | MIT RES.6.007 Signals and Systems, Spring 2011 HFGkQF5v6TQ 5453 Lec 13 | MIT 6.868J The Society of Mind, Spring 2007 PXTQsHOSpv4 5454 Lec 11 | MIT 6.868J The Society of Mind, Spring 2007 raoGbWJeR50 5455 Lec 9 | MIT 6.868J The Society of Mind, Spring 2007 kZkLqCdMXWY 5456 Lec 7 | MIT 6.868J The Society of Mind, Spring 2007 7OHdAHWhPwQ 5457 Lec 6 | MIT 6.868J The Society of Mind, Spring 2007 UIgA0czNj5g 5458 Lecture 13, Continuous-Time Modulation | MIT RES.6.007 Signals and Systems, Spring 2011 pSN7t79RxC4 5459 Lecture 20, The Laplace Transform | MIT RES.6.007 Signals and Systems, Spring 2011 TkMsVwzd1C0 5460 Lecture 10, Discrete-Time Fourier Series | MIT RES.6.007 Signals and Systems, Spring 2011 _WV4JlBOQro 5461 Lecture 17, Interpolation | MIT RES.6.007 Signals and Systems, Spring 2011 4Q1fWMxVDZY 5462 Lecture 24, Butterworth Filters | MIT RES.6.007 Signals and Systems, Spring 2011 z8sXXQxcmN4 5463 Lecture 23, Mapping Continuous-Time Filters to Discrete-Time Filters | MIT RES.6.007 HKMY-8BqWWw 5464 Lecture 11, Discrete-Time Fourier Transform | MIT RES.6.007 Signals and Systems, Spring 2011 S7MG1hgn0dY 5465 Lecture 25, Feedback | MIT RES.6.007 Signals and Systems, Spring 2011 GrnYlDAsmuA 5466 Lecture 15, Discrete-Time Modulation | MIT RES.6.007 Signals and Systems, Spring 2011 P3eLer1edx8 5467 Lecture 16, Sampling | MIT RES.6.007 Signals and Systems, Spring 2011 0Gat_aSzi5Y 5468 Lecture 22, The z-Transform | MIT RES.6.007 Signals and Systems, Spring 2011 D3bblng-Kcc 5469 Lecture 26, Feedback Example: The Inverted Pendulum | MIT RES.6.007 Signals and Systems, Spring 2011 8g4UudyOetE 5470 Lecture 21, Continuous-Time Second-Order Systems | MIT RES.6.007 Signals and Systems, Spring 2011 P5Ce9tbK86M 5471 Lecture 12, Filtering | MIT RES.6.007 Signals and Systems, Spring 2011 D1WF9YKqf3o 5472 Lecture 9, Fourier Transform Properties | MIT RES.6.007 Signals and Systems, Spring 2011 mmkOAMOw73U 5473 Lecture 19, Discrete-Time Sampling | MIT RES.6.007 Signals and Systems, Spring 2011 KT3yNuY_FPM 5474 Lecture 14, Demonstration of Amplitude Modulation | MIT RES.6.007 Signals and Systems, Spring 2011 Q-hMG2_cNxg 5475 Lecture 3, Signals and Systems: Part II | MIT RES.6.007 Signals and Systems, Spring 2011 t-HiowRQjgE 5476 MIT 24.120, Spring 2009 Faculty Introduction Tf0FDnIUHCI 5477 Lec 5 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis BekDicq9MdM 5478 Lec 10 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis ieV1yZ1l7-c 5479 Lec 16 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis N6rt_YxXuoA 5480 Lec 11 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis BH06RODmHsc 5481 Lec 15 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis 4XFvqOSRsa8 5482 MIT OpenCourseWare Press Conference - April 4, 2001 bd7nFEea0t0 5483 Celebrating a Decade of MIT OpenCourseWare lLmt2UPPuY4 5484 Unit II: Lec 5 | MIT Calculus Revisited: Single Variable Calculus EsiGSf2bt9k 5485 Lec 20 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis D_lVfCfGVao 5486 Lec 14 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis 4M-ijbL1gsk 5487 Lec 12 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis GpV_9EtObvs 5488 Lec 17 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis -BYC6cNSO78 5489 Lec 19 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis Jfibd3L_E_o 5490 Lec 21 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis Us2Myb5csu4 5491 Lec 18 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis NJUIkyavUD4 5492 Lec 22 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis GyeJwReGKWg 5493 Lec 13 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis L98VIorbFB0 5494 Lec 9 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis iOilZsS_cnM 5495 Lec 3 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis L27JVpZoz_Y 5496 Lec 6 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis _d27jyqzoKQ 5497 Lec 5 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis gzG2p-Su8Vw 5498 Lec 10 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis TJh7KPABk6I 5499 Lec 1 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis lsS2NysCVM4 5500 Lec 7 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis ejZtBwLUE3Y 5501 Lec 12 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis pSdxdfBnu0I 5502 Lec 11 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis E2HglWZcfKw 5503 Lec 6 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis 4-ehnTIyV0A 5504 Lec 4 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis uVavsfJOsKc 5505 Lec 2 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis 6pHHh67t6F8 5506 Lec 8 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis o2Vlt1avXCs 5507 Lec 2 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis Krb1fF2Ycgo 5508 Lec 7 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis 20WSeL4tz2k 5509 Lec 3 | MIT MIT Finite Element Procedures for Solids and Structures, Linear Analysis tkU3bM_6YLk 5510 Lec 4 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis ChYAqW_MnW0 5511 Lec 9 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis ut04RoDL-gk 5512 Lec 8 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis oNqSzzycRhw 5513 Lec 1 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis 7GZTjIxm32I 5514 Unit IV: Lec 3 | MIT Calculus Revisited: Single Variable Calculus -S5GwNe0xXg 5515 Unit II: Lec 10 | MIT Calculus Revisited: Single Variable Calculus w_JWcGLiifU 5516 Unit II: Lec 3 | MIT Calculus Revisited: Single Variable Calculus EeLD_40wDoU 5517 Unit IV: Lec 1 | MIT Calculus Revisited: Single Variable Calculus U40Q3SzzEtU 5518 Unit V: Lec 4 | MIT Calculus Revisited: Single Variable Calculus 9tYUmwvLyIA 5519 Unit I: Lec 5 | MIT Calculus Revisited: Single Variable Calculus XaxjVRXonPg 5520 Unit VII: Lec 4 | MIT Calculus Revisited: Single Variable Calculus zKtYCGbCfSc 5521 Unit I: Lec 4 | MIT Calculus Revisited: Single Variable Calculus dNyLGmiYQY0 5522 Unit I: Lec 2 | MIT Calculus Revisited: Single Variable Calculus 2f8CoFvB8uk 5523 Unit V: Lec 1 | MIT Calculus Revisited: Single Variable Calculus AaucguWxpqU 5524 Unit VII: Lec 2 | MIT Calculus Revisited: Single Variable Calculus elputTS7tAA 5525 Unit I: Lec 3 | MIT Calculus Revisited: Single Variable Calculus GqVQTRb-QoA 5526 Unit II: Lec 9 | MIT Calculus Revisited: Single Variable Calculus iM4DRgFqPso 5527 Unit VII: Lec 5 | MIT Calculus Revisited: Single Variable Calculus aWYwHnH-ptI 5528 Unit VI: Lec 2 | MIT Calculus Revisited: Single Variable Calculus Fe9DPXvt2ps 5529 Unit II: Lec 2 | MIT Calculus Revisited: Single Variable Calculus A1bPRw9VBQo 5530 Unit IV: Lec 4 | MIT Calculus Revisited: Single Variable Calculus 4Ywsdc6pCOk 5531 Unit VI: Lec 1 | MIT Calculus Revisited: Single Variable Calculus ehDAxjFK1jU 5532 Unit II: Lec 8 | MIT Calculus Revisited: Single Variable Calculus y4EcXTVqFb4 5533 Unit II: Lec 6 | MIT Calculus Revisited: Single Variable Calculus 8-7daeS7hYY 5534 Unit IV: Lec 2 | MIT Calculus Revisited: Single Variable Calculus 1z39nKVbh_w 5535 Unit VI: Lec 4 | MIT Calculus Revisited: Single Variable Calculus FdwTROVfEPE 5536 Unit III: Lec 1 | MIT Calculus Revisited: Single Variable Calculus rXOGLlKuvzU 5537 Unit I: Lec 1 | MIT Calculus Revisited: Single Variable Calculus HI_7Ml16O6Y 5538 Unit V: Lec 3 | MIT Calculus Revisited: Single Variable Calculus tGTCt3Dewtw 5539 Unit VI: Lec 3 | MIT Calculus Revisited: Single Variable Calculus IVVwFEnmFUk 5540 Unit II: Lec 11 | MIT Calculus Revisited: Single Variable Calculus MFRWDuduuSw 5541 Preface | MIT Calculus Revisited: Single Variable Calculus WfdBrggGJyg 5542 Unit III: Lec 2 | MIT Calculus Revisited: Single Variable Calculus mKMzFKgBluM 5543 Unit II: Lec 7 | MIT Calculus Revisited: Single Variable Calculus iWphmEIO-1E 5544 Unit VII: Lec 1 | MIT Calculus Revisited: Single Variable Calculus MNhkoylpyNA 5545 Unit II: Lec 4 | MIT Calculus Revisited: Single Variable Calculus 3Dz59nKUafo 5546 Unit VII: Lec 6 | MIT Calculus Revisited: Single Variable Calculus xlamQGapfbY 5547 Unit II: Lec 1 | MIT Calculus Revisited: Single Variable Calculus cm0io4R0tOM 5548 Unit I: Lec 6 | MIT Calculus Revisited: Single Variable Calculus jUkuRYDU4jA 5549 Unit VII: Lec 3 | MIT Calculus Revisited: Single Variable Calculus r9Jwtxf4SA0 5550 Unit V: Lec 2 | MIT Calculus Revisited: Single Variable Calculus nvcvALTXiKY 5551 Forum 2 | MIT 21M.542 Interdisciplinary Approaches to Musical Time, IAP 2010 NE2UztTuZ8A 5552 Forum 3 | MIT 21M.542 Interdisciplinary Approaches to Musical Time, IAP 2010 iyE1_dreJ-c 5553 Forum 1 | MIT 21M.542 Interdisciplinary Approaches to Musical Time, IAP 2010 TUdbHKlhOjs 5554 Class 12 | MIT 21M.542 Interdisciplinary Approaches to Musical Time, IAP 2010 4KheWy0pTro 5555 Class 10 | MIT 21M.542 Interdisciplinary Approaches to Musical Time, IAP 2010 8Ji3Gkjqo5M 5556 Lec 24 | MIT 22.091 Nuclear Reactor Safety, Spring 2008 JmK0vSLULP8 5557 Lec 5 | MIT 2.71 Optics, Spring 2009 ML5yVI18uaI 5558 Lec 19 | MIT 2.71 Optics, Spring 2009 MK5uZttfWfM 5559 Lec 13 | MIT 2.71 Optics, Spring 2009 VHIJPHqwV_0 5560 Lec 7 | MIT 2.71 Optics, Spring 2009 s8XKzciLgak 5561 Lec 26 | MIT 2.71 Optics, Spring 2009 X6cea7dAhBc 5562 Lec 3 | MIT 2.71 Optics, Spring 2009 OWgogzEUC5E 5563 Lec 20 | MIT 2.71 Optics, Spring 2009 933cBlGFDcs 5564 Lec 15 | MIT 2.71 Optics, Spring 2009 8u0Mfs1m_r8 5565 Lec 11 | MIT 2.71 Optics, Spring 2009 W-7gI87IG1A 5566 Lec 22 | MIT 2.71 Optics, Spring 2009 WCw7gzz5RZY 5567 Accuracy Requirements in the Mechanical Assessment of Photonic Crystals | MIT 2.71 Optics IYBYmOVmICg 5568 Lec 1 | MIT 2.71 Optics, Spring 2009 8WXUYdXNFy8 5569 Lec 9 | MIT 2.71 Optics, Spring 2009 Xke7rX3QO-k 5570 Lec 17 | MIT 2.71 Optics, Spring 2009 vcqPRPkyWPU 5571 Lec 23 | MIT 2.71 Optics, Spring 2009 u6GbFCWIH_0 5572 Lec 18 | MIT 2.71 Optics, Spring 2009 roATER6-1yI 5573 Lec 12 | MIT 2.71 Optics, Spring 2009 JmWguqCZRxk 5574 Lec 16 | MIT 2.71 Optics, Spring 2009 IpFIp68ODNI 5575 Lec 25 | MIT 2.71 Optics, Spring 2009 _jKHejk45Sg 5576 Lec 6 | MIT 2.71 Optics, Spring 2009 LDlGKU0ryQ8 5577 Lec 14 | MIT 2.71 Optics, Spring 2009 gAL5fCEBfac 5578 Lec 4 | MIT 2.71 Optics, Spring 2009 Q84-DIyl5wQ 5579 Lec 2 | MIT 2.71 Optics, Spring 2009 vRhpH8siTNk 5580 Design of a Cooke Triplet | MIT 2.71 Optics, Spring 2009 jNSvbmc_ecM 5581 Lec 8 | MIT 2.71 Optics, Spring 2009 dWK25XcqFL4 5582 Wigner Distribution Function and Integral Imaging | MIT 2.71 Optics, Spring 2009 lazME0LEUzA 5583 Holographic Particle Image Velocimetry | MIT 2.71 Optics, Spring 2009 _8TPfNfgH0I 5584 Light Propagation in Sub-wavelength Modulated Media | MIT 2.71 Optics, Spring 2009 RizM3cD3XSA 5585 Holographic Tomography | MIT 2.71 Optics, Spring 2009 CUrlh0yrQ8s 5586 Cell Growth and Division | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 hov6w7QFjBY 5587 Lec 2 | MIT 22.091 Nuclear Reactor Safety, Spring 2008 SX7B76R8eaQ 5588 Lec 3 | MIT 22.091 Nuclear Reactor Safety, Spring 2008 s2F4FtF6U30 5589 Lec 13 | MIT 22.091 Nuclear Reactor Safety, Spring 2008 YQwDoQYAoK0 5590 Lec 10 | MIT 22.091 Nuclear Reactor Safety, Spring 2008 v_NcOpoHBsk 5591 Lec 1 | MIT 22.091 Nuclear Reactor Safety, Spring 2008 VW47eFayFvQ 5592 Advancing the OpenCourseWare Movement: Challenges and Achievements 8gGbViZjoRw 5593 Implicit Differentiation and Linear Approximation | MIT 18.01SC Single Variable Calculus, Fall 2010 dGKvUUmMGoU 5594 Comparison Tests | MIT 18.01SC Single Variable Calculus, Fall 2010 aYMt2ZVGd7g 5595 Graphing the Arctan Function | MIT 18.01SC Single Variable Calculus, Fall 2010 2y4tCiWbVRI 5596 Recitation Introduction for MIT 18.01SC, 18.02SC uc4xJsi99bk 5597 Explanation of Simpson's rule | MIT 18.01SC Single Variable Calculus, Fall 2010 iHErQuZ8M-I 5598 Summation Notation Practice | MIT 18.01SC Single Variable Calculus, Fall 2010 7EKztFcTiUU 5599 Antidiff. With Discontinuity | MIT 18.01SC Single Variable Calculus, Fall 2010 rUis1mSzwyA 5600 Ratio Test for Convergence | MIT 18.01SC Single Variable Calculus, Fall 2010 y_CA5btuoQk 5601 Trig Integral Practice | MIT 18.01SC Single Variable Calculus, Fall 2010 _nbtaQtX6JA 5602 Definition of the Derivative | MIT 18.01SC Single Variable Calculus, Fall 2010 G5BP8mTzkyk 5603 Definite Integrals of tan(x) | MIT 18.01SC Single Variable Calculus, Fall 2010 _7vVBtiVXIw 5604 Second fundamental theorem and quadratic approximation | MIT 18.01SC Single Variable Calculus Wj0oH3ehk18 5605 Trig Integrals and a Volume of Revolution | MIT 18.01SC Single Variable Calculus, Fall 2010 1cejTnuMo1Y 5606 Integration Practice II | MIT 18.01SC Single Variable Calculus, Fall 2010 tMVwXglUp60 5607 Surface Area of a Torus | MIT 18.01SC Single Variable Calculus, Fall 2010 oTTo3qP0Z-I 5608 Ratio Test -- Radius of Convergence | MIT 18.01SC Single Variable Calculus, Fall 2010 QEBkT-Pgqos 5609 Integral Test as Estimation | MIT 18.01SC Single Variable Calculus, Fall 2010 Fj7pbLwbSmU 5610 Smoothing a Piece-wise Function | MIT 18.01SC Single Variable Calculus, Fall 2010 LUdI4-YCIh8 5611 Integration Practice III | MIT 18.01SC Single Variable Calculus, Fall 2010 Q9iJWDFUspU 5612 Maximum Surface Area | MIT 18.01SC Single Variable Calculus, Fall 2010 hV5af_07ToE 5613 Integrating sin^n(x) Using Reduction | MIT 18.01SC Single Variable Calculus, Fall 2010 l2SjUREZk0c 5614 Using the Trapezoid and Simpson's rules | MIT 18.01SC Single Variable Calculus, Fall 2010 cdRMY39EYbs 5615 Arccos | MIT 18.01SC Single Variable Calculus, Fall 2010 MYXMC7koJyY 5616 Volume of Revolution via Shells | MIT 18.01SC Single Variable Calculus, Fall 2010 v1AQ8Yi3yB8 5617 Parametric Arclength | MIT 18.01SC Single Variable Calculus, Fall 2010 QLo5dRFEyl8 5618 Computing the Volume of a Paraboloid | MIT 18.01SC Single Variable Calculus, Fall 2010 Gbtma_UQpro 5619 Graphing a Derivative Function | MIT 18.01SC Single Variable Calculus, Fall 2010 98X2TyxXQdU 5620 Integral of tan^4 (theta) | MIT 18.01SC Single Variable Calculus, Fall 2010 aar099Xh5W4 5621 Quadratic Approximation | MIT 18.01SC Single Variable Calculus, Fall 2010 lEOjMAmkI-U 5622 Second fundamental theorem and chain rule | MIT 18.01SC Single Variable Calculus, Fall 2010 G_HS1Dan_x4 5623 Mean Value Theorem | MIT 18.01SC Single Variable Calculus, Fall 2010 C9luv3o6emw 5624 Definite Integral by Substitution | MIT 18.01SC Single Variable Calculus, Fall 2010 UsGBIfjUK7U 5625 Partial Fractions Decomposition | MIT 18.01SC Single Variable Calculus, Fall 2010 QKXAd2PhZGY 5626 Failure of L'Hospital's Rule | MIT 18.01SC Single Variable Calculus, Fall 2010 rqkvDrYmKcc 5627 4J3, Diffusion of a Chemical | MIT 18.01SC Single Variable Calculus, Fall 2010 _UBh66KVAJI 5628 Average x-Coordinate in a Region | MIT 18.01SC Single Variable Calculus, Fall 2010 2_7htv5eviM 5629 Integration of Taylor's Series | MIT 18.01SC Single Variable Calculus, Fall 2010 owkMzpN8WDc 5630 Improper Integrals | MIT 18.01SC Single Variable Calculus, Fall 2010 E7oR_JBgUzA 5631 Graph of r = 1 + cos(theta/2) | MIT 18.01SC Single Variable Calculus, Fall 2010 d484GRz9zjY 5632 Related rates 2 | MIT 18.01SC Single Variable Calculus, Fall 2010 zsKdRjP91Fs 5633 Integration Practice IV | MIT 18.01SC Single Variable Calculus, Fall 2010 aefQ2FYugAY 5634 Computing Differentials | MIT 18.01SC Single Variable Calculus, Fall 2010 HaOHUfymsuk 5635 Differential Equation | MIT 18.01SC Single Variable Calculus, Fall 2010 fK6cu99OSEU 5636 Implicit Differentiation | MIT 18.01SC Single Variable Calculus, Fall 2010 zcuYFf5R0NU 5637 Series Calculation Using a Riemann Sum | MIT 18.01SC Single Variable Calculus, Fall 2010 pWXh5t-37Qg 5638 Finding u and v' When Integrating by Parts | MIT 18.01SC Single Variable Calculus, Fall 2010 ycO0Vn_w9Q0 5639 l'Hospital Practice | MIT 18.01SC Single Variable Calculus, Fall 2010 CMbvq16z0gA 5640 Integration by completing the square | MIT 18.01SC Single Variable Calculus, Fall 2010 W7sNkRpcydk 5641 Antidifferentiation by substitution | MIT 18.01SC Single Variable Calculus, Fall 2010 9YgOmJdom6o 5642 Rules of Logs | MIT 18.01SC Single Variable Calculus, Fall 2010 ed-rB3k_56U 5643 Linear approx. with differentials | MIT 18.01SC Single Variable Calculus, Fall 2010 er_tQOBgo-I 5644 Hyperbolic trig functions | MIT 18.01SC Single Variable Calculus, Fall 2010 Bb-bgJdOqig 5645 Derivatives of Sine and Cosine | MIT 18.01SC Single Variable Calculus, Fall 2010 2keGgDBJKGU 5646 Minimum Triangle Area | MIT 18.01SC Single Variable Calculus, Fall 2010 aeQA5d3gZTI 5647 Chain Rule | MIT 18.01SC Single Variable Calculus, Fall 2010 Nv3C7q88MqA 5648 Hyperbolic Trig Sub | MIT 18.01SC Single Variable Calculus, Fall 2010 ELWqePHYjCk 5649 Riemann sum | MIT 18.01SC Single Variable Calculus, Fall 2010 U3ebQ5Z4Jt8 5650 Area Between y=x^3 and y=3x-2 | MIT 18.01SC Single Variable Calculus, Fall 2010 55ncRlBZstA 5651 Product Rule | MIT 18.01SC Single Variable Calculus, Fall 2010 aWV4khIBvCM 5652 Sketching a curve | MIT 18.01SC Single Variable Calculus, Fall 2010 BSqNgPkeWIM 5653 Finding Taylor's Series | MIT 18.01SC Single Variable Calculus, Fall 2010 e4cURLXGjrM 5654 Integral Test | MIT 18.01SC Single Variable Calculus, Fall 2010 TQTDkpZP02A 5655 Applying the Second Fundamental Theorem | MIT 18.01SC Single Variable Calculus, Fall 2010 FK1n3TVQIhc 5656 Taylor's Series for sec(x) | MIT 18.01SC Single Variable Calculus, Fall 2010 D7nf7pKddwM 5657 Quotient Rule | MIT 18.01SC Single Variable Calculus, Fall 2010 ksAdC6Z99dE 5658 Volume of a Paraboloid via Disks | MIT 18.01SC Single Variable Calculus, Fall 2010 Psks_KK0YZ8 5659 Average Velocity | MIT 18.01SC Single Variable Calculus, Fall 2010 19x213y_uk4 5660 Taylor's Series of a Polynomial | MIT 18.01SC Single Variable Calculus, Fall 2010 v90JNWCTupk 5661 Computing Antiderivatives | MIT 18.01SC Single Variable Calculus, Fall 2010 9J_VCHpvMbY 5662 Area Between the Graphs of Sine and Cosine | MIT 18.01SC Single Variable Calculus, Fall 2010 WHWyW5DIVSU 5663 Differential Equation With Graph | MIT 18.01SC Single Variable Calculus, Fall 2010 Eaei-Y5AO_E 5664 Constant Multiple Rule | MIT 18.01SC Single Variable Calculus, Fall 2010 al2lzKq4o5E 5665 Power Series Practice | MIT 18.01SC Single Variable Calculus, Fall 2010 apzEJCsycVM 5666 Integral of x^n e^(-x) | MIT 18.01SC Single Variable Calculus, Fall 2010 VOlbVNxyNfM 5667 Arc Length of y=x^(3/2) | MIT 18.01SC Single Variable Calculus, Fall 2010 ER5B_YBFMJo 5668 Using Newton's Method | MIT 18.01SC Single Variable Calculus, Fall 2010 wezQdmwolMU 5669 Log and Exponent Derivatives | MIT 18.01SC Single Variable Calculus, Fall 2010 RiRQDZjYkzo 5670 Related rates 1 | MIT 18.01SC Single Variable Calculus, Fall 2010 13UPhn32Mjs 5671 Integration Practice I | MIT 18.01SC Single Variable Calculus, Fall 2010 bnhIRhnBa1A 5672 Indeterminate forms | MIT 18.01SC Single Variable Calculus, Fall 2010 rfx1x-2dwSI 5673 Tangent Line to a Polynomial | MIT 18.01SC Single Variable Calculus, Fall 2010 0YGiDaUOse4 5674 Quadratic Approximation of a Product | MIT 18.01SC Single Variable Calculus, Fall 2010 -CsEPYeSBsg 5675 Closest Point to the Origin | MIT 18.01SC Single Variable Calculus, Fall 2010 Bk5y6Elcy_Q 5676 Polar to Cartesian | MIT 18.01SC Single Variable Calculus, Fall 2010 bo8SFHppXZk 5677 A Solid With Finite Volume and Infinite Cross Section | MIT 18.01SC Single Variable Calculus LpW6zanbSf8 5678 Limit of a Series | MIT 18.01SC Single Variable Calculus, Fall 2010 z1FRDkxlmg8 5679 Mean value theorem | MIT 18.01SC Single Variable Calculus, Fall 2010 bJFqcqQcybg 5680 The iGEM Competition | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 gTtZrPy_SzQ 5681 The Abstraction Process | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 1N6Wvz-6FNI 5682 Open Reading Frames | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 uyNj56g5rHY 5683 Biosafety Levels | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 6a2YKft1ZxQ 5684 Controlling Growth | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 LRcYRm5daCU 5685 Genetic Digital Device | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 mXkOYxyChfg 5686 DNA Synthesis | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 MvXC1dUDxkg 5687 Building a Gene | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 o1bk4otKZw8 5688 Genetic Programs | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 XTUe-VMvRis 5689 Measurement | MIT 20.020 Introduction to Biological Engineering Design, Spring 2009 sjgX52rim2c 5690 Cells in scaffold | MIT 20.109 Laboratory Fundamentals in Biological Engineering, Spring 2010 EVfy8KT3Pyg 5691 Chemokinesis +CCL21 | MIT 20.109 Laboratory Fundamentals in Biological Engineering, Spring 2010 lm8dCTeu_l4 5692 Chemokinesis Control | MIT 20.109 Laboratory Fundamentals in Biological Engineering, Spring 2010 sy7dx_qzQak 5693 Extended Green's Theorem | MIT 18.02SC Multivariable Calculus, Fall 2010 G534bz09B4A 5694 Change of variables | MIT 18.02SC Multivariable Calculus, Fall 2010 XZ1QwS1IKgw 5695 Gradient and directional derivative | MIT 18.02SC Multivariable Calculus, Fall 2010 WwBaQCy4jfk 5696 Extended Gauss' Theorem | MIT 18.02SC Multivariable Calculus, Fall 2010 qA83eznsKp8 5697 Volume in cylindrical coordinates | MIT 18.02SC Multivariable Calculus, Fall 2010 U91touR6_UY 5698 The chain rule with constraints | MIT 18.02SC Multivariable Calculus, Fall 2010 BbNMKMicWy8 5699 Systems of linear equations | MIT 18.02SC Multivariable Calculus, Fall 2010 RoTz_ylFHfY 5700 Average distance on a sphere | MIT 18.02SC Multivariable Calculus, Fall 2010 2bF6H_xu0ao 5701 Total differentials and the chain rule | MIT 18.02SC Multivariable Calculus, Fall 2010 jAwWnppdcBE 5702 Gravity and a half-sphere | MIT 18.02SC Multivariable Calculus, Fall 2010 E8aYX_mW2DA 5703 Flux | MIT 18.02SC Multivariable Calculus, Fall 2010 I2Z6K_g5kpc 5704 Integration in polar coordinates | MIT 18.02SC Multivariable Calculus, Fall 2010 9rVojYcPeoU 5705 Fundamental theorem of line integrals | MIT 18.02SC Multivariable Calculus, Fall 2010 CCoTAyZ14XM 5706 Flux and the divergence theorem | MIT 18.02SC Multivariable Calculus, Fall 2010 2B7e19xi4Sw 5707 Consequences of Stokes' Theorem | MIT 18.02SC Multivariable Calculus, Fall 2010 7w1qqEUwn2k 5708 Extended Stokes' Theorem | MIT 18.02SC Multivariable Calculus, Fall 2010 hfyluFvlZ-o 5709 Dot products and angles | MIT 18.02SC Multivariable Calculus, Fall 2010 _5fpxkVFQUw 5710 Del and the product rule | MIT 18.02SC Multivariable Calculus, Fall 2010 YmAMEi-Faz8 5711 Line integral on a helix | MIT 18.02SC Multivariable Calculus, Fall 2010 j9GZjr05Heg 5712 Gradients - composition | MIT 18.02SC Multivariable Calculus, Fall 2010 YwZYSTQs-Hk 5713 Least squares | MIT 18.02SC Multivariable Calculus, Fall 2010 n9gSOBwauRw 5714 Non-conservative vector fields | MIT 18.02SC Multivariable Calculus, Fall 2010 oET16XXfcCI 5715 Area of a parallelogram | MIT 18.02SC Multivariable Calculus, Fall 2010 IYlzo-bxrqs 5716 Conservative fields and exact differentials | MIT 18.02SC Multivariable Calculus, Fall 2010 gzbWF-IdscE 5717 Level curves and critical points | MIT 18.02SC Multivariable Calculus, Fall 2010 -PGcTRLh1u4 5718 Flux through surfaces | MIT 18.02SC Multivariable Calculus, Fall 2010 BefxsWy1HqY 5719 Regions of integration | MIT 18.02SC Multivariable Calculus, Fall 2010 MosaZngFjZY 5720 Flux through a square | MIT 18.02SC Multivariable Calculus, Fall 2010 vnWXYI4UQrs 5721 More Stokes' Theorem | MIT 18.02SC Multivariable Calculus, Fall 2010 KXof0q88xbg 5722 Green's Theorem: area under an arch | MIT 18.02SC Multivariable Calculus, Fall 2010 ImzS_gSbjK4 5723 Max/Min | MIT 18.02SC Multivariable Calculus, Fall 2010 6S3BJSsc72Q 5724 Simply connected regions | MIT 18.02SC Multivariable Calculus, Fall 2010 6paZkmBMZwQ 5725 Tangent planes | MIT 18.02SC Multivariable Calculus, Fall 2010 dUk_I1E5QxY 5726 Parametrized lines and intersections | MIT 18.02SC Multivariable Calculus, Fall 2010 iYFogDTPlRo 5727 Moment of inertia of a cylinder | MIT 18.02SC Multivariable Calculus, Fall 2010 jUrPIbJWpOA 5728 Green's Theorem: an off center circle | MIT 18.02SC Multivariable Calculus, Fall 2010 -pr1TLyPyDw 5729 Integrals with density | MIT 18.02SC Multivariable Calculus, Fall 2010 gBuIwfdoOn0 5730 Line integrals: path dependence | MIT 18.02SC Multivariable Calculus, Fall 2010 nDuS5uQ7-lo 5731 Lagrange multipliers (3 variables) | MIT 18.02SC Multivariable Calculus, Fall 2010 mEI7ACWmx_8 5732 Flux across a curve | MIT 18.02SC Multivariable Calculus, Fall 2010 2ieG1ka5pBw 5733 Stokes' Theorem | MIT 18.02SC Multivariable Calculus, Fall 2010 XmQM5pHxX-o 5734 Equations of planes | MIT 18.02SC Multivariable Calculus, Fall 2010 fWOGfzC3IeY 5735 Integral of exp(-x^2) | MIT 18.02SC Multivariable Calculus, Fall 2010 lCKxeRiBdjQ 5736 Change of variables | MIT 18.02SC Multivariable Calculus, Fall 2010 YWvBaLokEJY 5737 Domains of vector fields | MIT 18.02SC Multivariable Calculus, Fall 2010 cbSkFpO2jgQ 5738 Average height | MIT 18.02SC Multivariable Calculus, Fall 2010 P6fOgkC5kvc 5739 Matrix multiplication practice | MIT 18.02SC Multivariable Calculus, Fall 2010 grns_GNYWe4 5740 Application of Green's theorem | MIT 18.02SC Multivariable Calculus, Fall 2010 tkAgpKg-tPs 5741 Line integrals: parametrization independence | MIT 18.02SC Multivariable Calculus, Fall 2010 1ye7dm9aUj0 5742 Green's Theorem in normal form | MIT 18.02SC Multivariable Calculus, Fall 2010 oQgHo7acids 5743 Second derivative test | MIT 18.02SC Multivariable Calculus, Fall 2010 6T13yRjtd-o 5744 Solve a linear system using matrices | MIT 18.02SC Multivariable Calculus, Fall 2010 p06QDsAPY4g 5745 Changing the order of integration | MIT 18.02SC Multivariable Calculus, Fall 2010 HyqBcD_e_Uw 5746 Lagrange multipliers | MIT 18.02SC Multivariable Calculus, Fall 2010 AYixF5nY3Vc 5747 Coordinate free proofs: centroid of a triangle | MIT 18.02SC Multivariable Calculus, Fall 2010 QHaAoQQy07I 5748 Finding area using cross products | MIT 18.02SC Multivariable Calculus, Fall 2010 Tgk9wURblAw 5749 Potentials of gradient fields | MIT 18.02SC Multivariable Calculus, Fall 2010 idNIKTaBEaI 5750 Tangent plane approximation | MIT 18.02SC Multivariable Calculus, Fall 2010 ocdM30Wm_8g 5751 Line integrals by geometric reasoning | MIT 18.02SC Multivariable Calculus, Fall 2010 AYisLr9e0y4 5752 Flux through easy surfaces | MIT 18.02SC Multivariable Calculus, Fall 2010 u9YrIxLZJ6s 5753 Parametric curves: velocity, acceleration, length | MIT 18.02SC Multivariable Calculus, Fall 2010 KnVNFj53Eq4 5754 Partial derivatives | MIT 18.02SC Multivariable Calculus, Fall 2010 SgJo7_4mp6w 5755 Distance of a point to a plane | MIT 18.02SC Multivariable Calculus, Fall 2010 evxReCLA-fU 5756 Differentiating a vector valued function | MIT 18.02SC Multivariable Calculus, Fall 2010 f2KsJBClJ1g 5757 Graphing surfaces | MIT 18.02SC Multivariable Calculus, Fall 2010 uaHiAxFESc4 5758 Level curves | MIT 18.02SC Multivariable Calculus, Fall 2010 4kPz8aqm5yE 5759 Components of a vector | MIT 18.02SC Multivariable Calculus, Fall 2010 rtEaK_Jp7zU 5760 Parametric line intersecting a plane | MIT 18.02SC Multivariable Calculus, Fall 2010 PxkEoEbCJT8 5761 Determinants | MIT 18.02SC Multivariable Calculus, Fall 2010 QCGJVKaCDuI 5762 Volume of a parallelepiped | MIT 18.02SC Multivariable Calculus, Fall 2010 kI7D2lkcF8E 5763 Course Introduction | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 l-8-c7g-LY4 5764 Lec 25 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 malCa9kI7Ag 5765 Lec 20 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 Io_4ZckeQ1k 5766 Lec 3 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 h1dWUja7_5A 5767 Lec 23 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 K30HeE8fEq8 5768 Lec 5 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 up3zP2z81SE 5769 Lec 9 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 c_4dDw7iLn8 5770 Lec 7 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 56d9qcsHGwE 5771 Lec 14 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 uCK1z-h7Jbc 5772 Lec 17 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 RikovZJdUmg 5773 Lec 30 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 kZJgJCxcHZE 5774 Lec 8 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 _xu-p6Ffh-A 5775 Lec 26 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 Fg78tInX5Vg 5776 Lec 19 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 540Sggsblbg 5777 Lec 13 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 AFS4JbQGB0c 5778 Lec 27 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 zOOQALT2uu8 5779 Lec 35 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 rR8ZtI8m0Mo 5780 Lec 34 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 FRgckt9lDQ8 5781 Lec 31 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 5l_S8WwBVnM 5782 Lec 4 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 3dU0v-EvUmA 5783 Lec 15 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 FVzaznYPCes 5784 Lec 16 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 j7EBObU5Tjk 5785 Lec 32 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 wyoFOdR64U8 5786 Lec 10 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 xEnYH0KNkfA 5787 Lec 33 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 giPLtjL0Mnc 5788 Lec 6 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 FfBc3M5EaeU 5789 Lec 11 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 oDOs8Yxydo0 5790 Lec 24 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 kB2Ue4Fip2c 5791 Lec 21 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 fFg4uXMpnV0 5792 Lec 18 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 VL0pw-yVgjM 5793 Lec 28 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 2Q_fna3TTbs 5794 Lec 12 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 vPQ9a_xIqRg 5795 Lec 1 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 czAWbZLxFNM 5796 Lec 22 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 KlI1duF4K9o 5797 Lec 29 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 h57hFAsLAGo 5798 Lec 2 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 jogwl3z8wA8 5799 HST.921 Spring 2009 Course Introduction o2ZUHc4M4k8 5800 Part II: Lec 5 | MIT Calculus Revisited: Single Variable Calculus AUBkR1-8fLY 5801 Lec 36 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 LQRPRIsCQkI 5802 Lec 31 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 LXa9j8ZN5gU 5803 Lec 27 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 uz7GkOzULm8 5804 Lec 30 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 P2hxNOFiBb4 5805 Lec 29 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 aFh1ZyxcHbQ 5806 Lec 34 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 PjpLw1iqr4E 5807 Lec 38 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 xvUz7P-DjhI 5808 Lec 28 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 sXHck0ZjWmw 5809 Lec 26 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 fzU7FpMSD30 5810 Lec 37 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 AVqr7VXpTFk 5811 Lec 33 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 e2CGPcPNldA 5812 Lec 35 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 FwIKZIWJfg8 5813 Exam 2, Problem 1 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 b7SDngGtNDs 5814 Final Exam B, Problem 6 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 LHRZLeQ2aaM 5815 Exam 2, Problem 2 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 j9DVXVwVyc4 5816 Final Exam B, Problem 13 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 dbSKZx9sfsg 5817 Exam 1, Problem 3 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 0oqHExM3_Ko 5818 Final Exam B, Problem 11 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 wtyVfNC_5ms 5819 Final Exam A, Problem 8 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 U_dpm7SCIpg 5820 Exam 3, Problem 5 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 FYJJHMLv9oM 5821 Final Exam B, Problem 7 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 StY_01uUFSY 5822 Exam 3, Problem 2 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 YwKqzngTcLw 5823 Final Exam A, Problem 10 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 yg4M2xmY4bs 5824 Final Exam B, Problem 5 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 vJChxpbx_Oo 5825 Exam 1, Problem 2 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 NpBq_JnLKv8 5826 Exam 2, Problem 4 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 2eLeU6-0W7E 5827 Exam 1, Problem 5 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 CA7I2GLpgdo 5828 Exam 3, Problem 4 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 xEm2h8yiADY 5829 Exam 1, Problem 4 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 IKJJ1SiMbjg 5830 Exam 3, Problem 3 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 qKh4mOlEZpE 5831 Exam 2, Problem 5 (Part A) | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 cMaryERGZmY 5832 Exam 2, Problem 3 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 RXTvZGj1MDA 5833 Exam 3, Problem 1 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 iRh3Kpgg0Uc 5834 Exam 1, Problem 1 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 p6isgsReWmI 5835 Final Exam A, Problem 9 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 UwZU-Lk26X4 5836 Exam 1, Problem 6 | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 NuoT9XPOjJ0 5837 Exam 2, Problem 5 (Part B) | MIT 3.091SC Introduction to Solid State Chemistry, Fall 2010 WU1m2QQrlho 5838 Growth Rate and Log Graphs hQbxesMB_N0 5839 Lec 16 | MIT 5.74 Introductory Quantum Mechanics II, Spring 2009 Uic47mwXNuQ 5840 Lec 13 | MIT 5.74 Introductory Quantum Mechanics II, Spring 2009 eBkhAL-0l50 5841 Lec 15 | MIT 5.74 Introductory Quantum Mechanics II, Spring 2009 NzHt2WqrS88 5842 Lec 14 | MIT 5.74 Introductory Quantum Mechanics II, Spring 2009 LgWFurXHX8U 5843 Six Functions, Six Rules, and Six Theorems I_ril7ToAi4 5844 Inverse Functions f ^-1 (y) and the Logarithm x = ln y IDo4uPyqQbQ 5845 Differential Equations of Growth FtQl1gAo12E 5846 Derivative of sin x and cos x 4PBYm3FuUNQ 5847 Differential Equations of Motion kAv5pahIevE 5848 Limits and Continuous Functions cRsptYEK1G4 5849 Derivatives of ln y and sin ^-1 (y) N4ceWhmXxcs 5850 Power Series/Euler's Great Formula 5ZpqI8zz1HM 5851 Product Rule and Quotient Rule U0xlKuFqCuI 5852 Linear Approximation/Newton's Method yQrKXo89nHA 5853 Chains f(g(x)) and the Chain Rule 9RqFFlZgf60 5854 Lec 10 | MIT 6.002 Circuits and Electronics, Spring 2007 CxlV7_w4TZQ 5855 MIT 6.901, Fall 2005 Faculty Introduction Kw-FtXrG3WA 5856 MIT 24.118, Fall 2006 Faculty Introduction j3CaKev2GnQ 5857 MIT 24.729, Fall 2005 Faculty Introduction V8G7aic6vnU 5858 Faculty Introduction for MIT ESD.932, Spring 2006 S9uGFKoRGUU 5859 Faculty Introduction for MIT 5.95J, Spring 2009 6v9cN4-do64 5860 MIT 2.60 Spring 2004 Faculty Introduction WxqdIRbQp0c 5861 MIT 5.80, Spring 2008 Faculty Introduction JM9n5J40gjc 5862 MIT 6.641, Spring 2009 Faculty Introduction 0XzBJbfN4-M 5863 MIT OpenCourseWare Staff Picks - July 2010 Gho0bmTsnA4 5864 Lecture 8 | MIT 6.832 Underactuated Robotics, Spring 2009 ja56bJ8ogUw 5865 Lecture 20 | MIT 6.832 Underactuated Robotics, Spring 2009 QI09XKVW_8E 5866 Lecture 6 | MIT 6.832 Underactuated Robotics, Spring 2009 oWr1_LybOZI 5867 Lecture 3 | MIT 6.832 Underactuated Robotics, Spring 2009 xwgIkdBQku4 5868 Lecture 10 | MIT 6.832 Underactuated Robotics, Spring 2009 EqAYRo4wXxY 5869 Lecture 18 | MIT 6.832 Underactuated Robotics, Spring 2009 qtmmwILxVR4 5870 Lecture 19 | MIT 6.832 Underactuated Robotics, Spring 2009 Z8oMbOj9IWM 5871 Lecture 1 | MIT 6.832 Underactuated Robotics, Spring 2009 9qnpQ1hVlqw 5872 Lecture 7 | MIT 6.832 Underactuated Robotics, Spring 2009 -RRYZ-b9NpI 5873 Lecture 2 | MIT 6.832 Underactuated Robotics, Spring 2009 CUygqWS7occ 5874 Lecture 13 | MIT 6.832 Underactuated Robotics, Spring 2009 7nnFGxqRwNE 5875 Lecture 15 | MIT 6.832 Underactuated Robotics, Spring 2009 89GQHKOeUcU 5876 Lecture 4 | MIT 6.832 Underactuated Robotics, Spring 2009 4kB94UDwJ0M 5877 Lecture 5 | MIT 6.832 Underactuated Robotics, Spring 2009 KNRMz9YPCOY 5878 Lecture 16 | MIT 6.832 Underactuated Robotics, Spring 2009 -fCLJ1pGht4 5879 Lecture 11 | MIT 6.832 Underactuated Robotics, Spring 2009 7LLUz7A1--Q 5880 Lecture 21 | MIT 6.832 Underactuated Robotics, Spring 2009 ufM3HLTZ47k 5881 Lecture 14 | MIT 6.832 Underactuated Robotics, Spring 2009 6v3Ln2ACtqI 5882 Lecture 17 | MIT 6.832 Underactuated Robotics, Spring 2009 7la43dvoLh0 5883 Lecture 23 | MIT 6.832 Underactuated Robotics, Spring 2009 E-sOMfDVe8o 5884 Lecture 12 | MIT 6.832 Underactuated Robotics, Spring 2009 Bhbk4bWV1Uc 5885 Lecture 22 | MIT 6.832 Underactuated Robotics, Spring 2009 g-VehRFsDcI 5886 Lecture 9 | MIT 6.832 Underactuated Robotics, Spring 2009 RdkB7tbufYI 5887 Lecture 12w | MIT 21M.380 Music and Technology (Contemporary History and Aesthetics), Fall 2009 GM4pqoiS6Vg 5888 Lecture 12d | MIT 21M.380 Music and Technology (Contemporary History and Aesthetics), Fall 2009 uKe1yzt1IrI 5889 Lecture 16 | MIT 21M.380 Music and Technology (Contemporary History and Aesthetics), Fall 2009 BGL8we3QUxI 5890 Lecture 13 | MIT 21M.380 Music and Technology (Contemporary History and Aesthetics), Fall 2009 hwUTfNdgUaA 5891 Lec 15 | ESD.172J X PRIZE Workshop: Grand Challenges in Energy, Fall 2009 EtPw85aeLtg 5892 MIT OpenCourseWare Staff Picks - May 2010 ICa_4xUr8BA 5893 MIT OpenCourseWare Site Tour tBBJ2TSTa1Q 5894 Max and Min and Second Derivative oo1ZZlvT2LQ 5895 The Exponential Function UcWsDwg1XwM 5896 Big Picture of Calculus 2qxY859dzzQ 5897 Big Picture: Integrals T_I-CUOc_bk 5898 Big Picture: Derivatives X9t-u87df3o 5899 Gil Strang's Introduction to Calculus for Highlights for High School FqtMJ2EFo5s 5900 MIT OpenCourseWare Staff Picks - April 2010 SW5Zfs97wSw 5901 Ses 6 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training Hz1S82W8F04 5902 Ses 1 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training EYANqW4zwwo 5903 Ses 7 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training a7sDTYmqdSY 5904 Ses 2 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training Z1iXHd349bo 5905 Ses 8 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training UZzWXYgQ4YM 5906 Ses 4 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training JIAOaRFwDic 5907 Ses 5 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training DUyOjsFTOgQ 5908 Ses 3 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training cG6QrqS4ruQ 5909 Using a Balance | MIT Digital Lab Techniques Manual Ke2CpF8M0mc 5910 MIT OpenCourseWare Staff Picks - February 2010 SJI-SAs1Rnk 5911 A Funny Thing Happened on the way to the Moon | MIT 16.346 Astrodynamics, Fall 2008 wy-LqFDwMuM 5912 Lec 1 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 5uTd3WzQulo 5913 Lec 6 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 AcNtVgOp0bI 5914 Automatic Pipet | MIT Digital Lab Techniques Manual iinr4-0C0Yc 5915 Melting Point | MIT Digital Lab Techniques Manual 7LBGQHjgHEw 5916 Recrystallization | MIT Digital Lab Techniques Manual fHEk2WFgmXQ 5917 Refluxing a Reaction | MIT Digital Lab Techniques Manual P-UBuAFxJiA 5918 Filtration | MIT Digital Lab Techniques Manual HZFIdpThd-s 5919 Buffers and pH Meter | MIT Digital Lab Techniques Manual B_QyhG2-VBI 5920 Column Chromatography | MIT Digital Lab Techniques Manual DmvaOb1xb1o 5921 Reaction Work-Up I | MIT Digital Lab Techniques Manual e99nsCAsJrw 5922 TLC-The Basics | MIT Digital Lab Techniques Manual dBNELFi5XiY 5923 Sublimation | MIT Digital Lab Techniques Manual ml58GCq078o 5924 TLC-Advanced | MIT Digital Lab Techniques Manual 3DQj4dibr78 5925 Reaction Work-Up II | MIT Digital Lab Techniques Manual 8djXBVSrDRw 5926 Volumetric Techniques | MIT Digital Lab Techniques Manual GtuMlWMajtw 5927 Distillation I | MIT Digital Lab Techniques Manual a4hLUCX893M 5928 Titration | MIT Digital Lab Techniques Manual mn-u-7fRQv4 5929 Distillation II | MIT Digital Lab Techniques Manual 8YQf4xOEhag 5930 Lec 4 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 gyboshu425k 5931 Lec 2 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 PaYY0e9eE2A 5932 Lec 9 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 etbY4_d3peg 5933 Lec 3 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 RyKmgyGH5dw 5934 Lec 7 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 QcRteDU9Eco 5935 Lec 8 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 IXjwZlJ9Uvk 5936 Lec 10 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 V-eWuHXZGnw 5937 Lec 5 | MIT 5.95J Teaching College-Level Science and Engineering, Spring 2009 ZCqgBRoH_Tk 5938 Course Introduction | The Nature of Engineering 8KB9sHZZdQM 5939 Course Introduction | Numerical Marine Hydrodynamics, Spring 2003 pC6Svpdiqoc 5940 Evening Workshop | MIT 21M.342 Composing for Jazz Orchestra, Fall 2008 1mKJXp1HvpQ 5941 Lecture 21 | MIT 21M.342 Composing for Jazz Orchestra, Fall 2008 00_O45wYZm0 5942 Concert | MIT 21M.342 Composing for Jazz Orchestra, Fall 2008 Yp67PhU7Jt0 5943 "Empty Bottles" by Mike Lee | MIT 21M.342 Composing for Jazz Orchestra, Fall 2008 7R5DF-w94Zk 5944 "Totality" by Chris Kottke | MIT 21M.342 Composing for Jazz Orchestra, Fall 2008 y9YtI8nVfmA 5945 Space Shuttle Operations Video _qDdzzBDoPc 5946 Highlights for High School Guided Tour 2009 6utcvADn6_0 5947 MIT 21M.304 Writing in Tonal Forms II, Spring 2009 v10zD6z-JDM 5948 Project: Bicycle-powered centrifuge | MIT SP.718, Spring 2009 z9JJp8DHMYc 5949 Project: Nebulizer | MIT SP.718, Spring 2009 NAGh1gII_HA 5950 Project: Infection detection bandage | MIT SP.718, Spring 2009 GrXkZYhkUS8 5951 Lec 2 | MIT 2.830J Control of Manufacturing Processes, S08 XTGU4Vh-t_M 5952 MIT OpenCourseWare Staff Picks - November 2009 lY0nUBRRd10 5953 Running Clinic with Danny Abshire | MIT SP.235 Chemistry of Sports, Spring 2009 7T30ihcHFmk 5954 MIT OpenCourseWare Staff Pick - October 2009 tQz6iktxQqM 5955 Control Lab | MIT 2.830J Control of Manufacturing Processes, S08 5gI1aF81Saw 5956 Course Introduction | 3.20 Materials at Equilibrium, Fall 2003 FccfP6Em-3o 5957 Course Introduction | 1.00 Introduction to Computers and Engineering Problem Solving, Fall 2005 4HEi-ZDXYho 5958 Course Introduction | 3.53 Electrochemical Processing of Materials, Spring 2001 N867pCLaz04 5959 Course Introduction | 4.614 Religious Architecture and Islamic Cultures, Fall 2002 tdjAGitQHDo 5960 Course Introduction | 4.196 Architecture Design, Level II: Cuba Studio, Spring 2004 qQqtsa1e-Jg 5961 Course Introduction | CMS.801 Media in Transition, Fall 2004 7mOpiYDCX08 5962 Course Introduction by Prof. Waitz | Unified Engineering, Fall 2005 - Spring 2006 qlLUs2hRa_A 5963 Course Introduction | 1.050 Solid Mechanics, Fall 2004 fASyFNukWP8 5964 Course Introduction | 3.185 Transport Phenomena in Materials Engineering, Fall 2003 ZWjh9KoEyqg 5965 Course Introduction | 12.000 Solving Complex Problems, Fall 2003 N9z2u1TqOrw 5966 Course Introduction by Prof. Coleman | Unified Engineering, Fall 2005 - Spring 2006 X5ivIqH5rB4 5967 Course Introduction | 2.71 Optics, Fall 2004 OpO1Pj4z1hI 5968 Course Introduction | HST.725 Music Perception and Cognition 6swIAqXcvDQ 5969 Lec 18 | MIT 2.830J Control of Manufacturing Processes, S08 qvX-3FWgAVA 5970 Lec 21 | MIT 2.830J Control of Manufacturing Processes, S08 ra5yBfC9ztE 5971 Lec 22 | MIT 2.830J Control of Manufacturing Processes, S08 LIADaqdI1Y8 5972 Lec 17 | MIT 2.830J Control of Manufacturing Processes, S08 R4lUaI7VsK4 5973 Lec 4 | MIT 2.830J Control of Manufacturing Processes, S08 ZUkM3_qPBo0 5974 Lec 15 | MIT 2.830J Control of Manufacturing Processes, S08 6ILIA7h7B8I 5975 Lec 2 | MIT 2.830J Control of Manufacturing Processes, S08 AhKNoBxPkJs 5976 Lec 16 | MIT 2.830J Control of Manufacturing Processes, S08 W20WvURZAIE 5977 Lec 6 | MIT 2.830J Control of Manufacturing Processes, S08 aHuYrIHveJo 5978 Lec 12 | MIT 2.830J Control of Manufacturing Processes, S08 FuGcyIynuxg 5979 Lec 13 | MIT 2.830J Control of Manufacturing Processes, S08 0INq0CFpXpo 5980 Lec 10 | MIT 2.830J Control of Manufacturing Processes, S08 qyAoSHisZtU 5981 Lec 20 | MIT 2.830J Control of Manufacturing Processes, S08 MyWivgwDPtg 5982 Lec 8 | MIT 2.830J Control of Manufacturing Processes, S08 vHxLQwZtAD8 5983 Lec 14 | MIT 2.830J Control of Manufacturing Processes, S08 OQ-534Ovf4U 5984 Lec 5 | MIT 2.830J Control of Manufacturing Processes, S08 turMcLH-o_o 5985 Lec 3 | MIT 2.830J Control of Manufacturing Processes, S08 MeFCYYCATw0 5986 Lec 9 | MIT 2.830J Control of Manufacturing Processes, S08 -EgKluVR2Ug 5987 Lec 19 | MIT 2.830J Control of Manufacturing Processes, S08 TvrU_6NYBFs 5988 Lec 7 | MIT 2.830J Control of Manufacturing Processes, S08 kC2SEiGaqoA 5989 Lec 1 | MIT 2.830J Control of Manufacturing Processes, S08 zx_DA70lYww 5990 Lec 11 | MIT 2.830J Control of Manufacturing Processes, S08 LeNCseTD7FA 5991 Song 5 | MIT 21M.303 Writing in Tonal Forms I, Spring 2009 mQdvMGUEpHw 5992 Song 6 | MIT 21M.303 Writing in Tonal Forms I, Spring 2009 XuTosmTlktM 5993 Song 2 | MIT 21M.303 Writing in Tonal Forms I, Spring 2009 CazYO1ET4ic 5994 Song 3 | MIT 21M.303 Writing in Tonal Forms I, Spring 2009 3k7enjPPLSI 5995 Song 4 | MIT 21M.303 Writing in Tonal Forms I, Spring 2009 4aiTCDvlUeI 5996 Song 1 | MIT 21M.303 Writing in Tonal Forms I, Spring 2009 rzD4knm4--I 5997 MIT OpenCourseWare Staff Pick - September 2009 CXKoCMVqM9s 5998 Lec 28 | MIT 18.01 Single Variable Calculus, Fall 2007 aeXp1zC6Hls 5999 Lec 30 | MIT 18.01 Single Variable Calculus, Fall 2007 wOHrNt9ScYs 6000 Lec 38 | MIT 18.01 Single Variable Calculus, Fall 2007 PNTnmH6jsRI 6001 Lec 35 | MIT 18.01 Single Variable Calculus, Fall 2007 XRkgBWbWvg4 6002 Lec 32 | MIT 18.01 Single Variable Calculus, Fall 2007 HgEqXhsIq_g 6003 Lec 29 | MIT 18.01 Single Variable Calculus, Fall 2007 KhwQKE_tld0 6004 Lec 36 | MIT 18.01 Single Variable Calculus, Fall 2007 MK_0QHbUnIA 6005 Lec 37 | MIT 18.01 Single Variable Calculus, Fall 2007 TpWQlKHPyJ4 6006 Lec 31 | MIT 18.01 Single Variable Calculus, Fall 2007 BGE3wb7H2PA 6007 Lec 33 | MIT 18.01 Single Variable Calculus, Fall 2007 Bv9kVDcj7yo 6008 Lec 27 | MIT 18.01 Single Variable Calculus, Fall 2007 --lPz7VFnKI 6009 Lec 39 | MIT 18.01 Single Variable Calculus, Fall 2007 IjFKbYqt0ik 6010 Lec 14 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 xnn2r4KuJeY 6011 Lec 24 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 QnE_fuUCrg0 6012 Lec 18 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 ic9ei_hEeJs 6013 Lec 23 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 O1OZqHaRZNg 6014 Lec 22 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 h2hAmn7cUxE 6015 Lec 25 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 aNe5O7dxYOc 6016 Lec 21 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 b4x3cdUY2VU 6017 Lec 17 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 qOAs4HVCR48 6018 Lec 20 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 _ax_ViGCxLI 6019 Lec 19 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 LYH8iiuvApI 6020 Lec 2 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 Z-Ow4zRoI30 6021 Lec 1 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 zsxqmbdUXuo 6022 Lec 3 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 yl8bygSTGTE 6023 Lec 4 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 GbuXLQ08n4A 6024 Lec 8 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 pGpyDJwAI8A 6025 Lec 9 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 pXHeut3qV2Y 6026 Lec 16 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 gJkHjo5lxGU 6027 Lec 12 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 W1FtRnLslSA 6028 Lec 13 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 DaLRx48fnt4 6029 Lec 5 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 C-72lxj3b-g 6030 Lec 10 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 a4krZtUkzMM 6031 Lec 6 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 RnOQjczFcBY 6032 Lec 7 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 3p-AfjvEDqs 6033 Lec 15 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 C1mHR4mkjd8 6034 Lec 11 | MIT 5.80 Small-Molecule Spectroscopy and Dynamics, Fall 2008 eiDX9dw866E 6035 Lec 21 | MIT 7.014 Introductory Biology, Spring 2005 SuOIpJnn888 6036 Lec 21 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 UNHQ7CRsEtU 6037 Lec 9 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 IZaAUwW7OsU 6038 Lec 19 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 hVHqs38fPe8 6039 Lec 6 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 y81AhLQN-NI 6040 Lec 15 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 SXR9CDof7qw 6041 Lec 4 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 le8tpXQyYcM 6042 Lec 14 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 kDhR4Zm53zc 6043 Lec 10 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 WGDbIKtjmSs 6044 Lec 22 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 Pij6J0HsYFA 6045 Lec 2 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 raTzkzML31w 6046 Lec 23 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 k6U-i4gXkLM 6047 Lec 1 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 QJ_MPc0TobI 6048 Lec 18 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 DkPsD58nUIE 6049 Lec 11 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 udnyuHzJsjM 6050 Lec 12 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 X6ilT3uUOBo 6051 Lec 3 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 Pfo7r6bjSqI 6052 Lec 5 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 Q8SoG1OIveU 6053 Lec 16 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 ewd7Lf2dr5Q 6054 Lec 8 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 ZKBUu_ahSR4 6055 Lec 13 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 ZbIpjf0QEPI 6056 Lec 17 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 tuRYbBvOMRo 6057 Lec 7 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 ENrAsRoR97I 6058 Lec 20 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 2q--tAPkVXI 6059 Lec 24 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008 zUEuKrxgHws 6060 Lec 25 | MIT 18.01 Single Variable Calculus, Fall 2007 ShGBRUx2ub8 6061 Lec 22 | MIT 18.01 Single Variable Calculus, Fall 2007 60VGKnYBpbg 6062 Lec 16 | MIT 18.01 Single Variable Calculus, Fall 2007 7K1sB05pE0A 6063 Lec 1 | MIT 18.01 Single Variable Calculus, Fall 2007 jBkXbAgMj6s 6064 Lec 24 | MIT 18.01 Single Variable Calculus, Fall 2007 R9a_NHXrBcg 6065 Lec 23 | MIT 18.01 Single Variable Calculus, Fall 2007 eRCN3daFCmU 6066 Lec 10 | MIT 18.01 Single Variable Calculus, Fall 2007 1RLctDS2hUQ 6067 Lec 19 | MIT 18.01 Single Variable Calculus, Fall 2007 hjZhPczMkL4 6068 Lec 18 | MIT 18.01 Single Variable Calculus, Fall 2007 Pd2xP5zDsRw 6069 Lec 20 | MIT 18.01 Single Variable Calculus, Fall 2007 _JXPe2J069c 6070 Lec 21 | MIT 18.01 Single Variable Calculus, Fall 2007 SBe03vJr8-Y 6071 Pres: Christian Hedrick | MIT 4.696 A Global History of Architecture Writing Seminar, Spring 2008 cPohVoQM9EE 6072 Pres: Karin Oen | MIT 4.696 A Global History of Architecture Writing Seminar, Spring 2008 I5r_4tzl0u4 6073 Pres: Nancy Demerdash | MIT 4.696 A Global History of Architecture Writing Seminar, Spring 2008 J1QaLzBuE4k 6074 Pres: John Ellis | MIT 4.696 A Global History of Architecture Writing Seminar, Spring 2008 GGVls5jofiM 6075 Ses 1-4 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 Swo3Lvw7ivg 6076 Ses 2-1 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 JZRusgbh-lA 6077 Pres: Zameer Basrai | MIT 4.696 A Global History of Architecture Writing Seminar, Spring 2008 yExu8MFD4dc 6078 Pres: Shiben Banerji | MIT 4.696 A Global History of Architecture Writing Seminar, Spring 2008 nHcpzcATn1c 6079 Ses 3-5 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 PQspf3q12mo 6080 Ses 1-2 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 dYYULn2A9FA 6081 Ses 1-3 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 pfZ6CTEPc9s 6082 Ses 1-7 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 lPUjMOR0z4Q 6083 Ses 3-3-2 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 BGJ6vytOGJY 6084 Ses 3-6 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 2cFtUc7VdDs 6085 Ses 3-2 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 vYURcLuJEZs 6086 Ses 3-3-1 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 S_VLW77bN5E 6087 Ses 2-4 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 8RlA0D6cjDc 6088 Ses 2-2 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 4ql4kfIBMX8 6089 Ses 1-6 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 sjgFbLjMgZw 6090 Ses 3-4 | MIT 16.660 Introduction to Lean Six Sigma Methods, January (IAP) 2008 l_oKZG_PqlA 6091 27. Transition metals and the treatment of lead poisoning l6Bf5ktvM_g 6092 13. Polar covalent bonds; VSEPR theory 5qTCy2wTL_s 6093 10. Periodic trends continued; Covalent bonds Pj2fkkZ6Gto 6094 6. Hydrogen atom wavefunctions (orbitals) 8b56I8U24xU 6095 11. Lewis structures rGAcOfOZToA 6096 34. Temperature and kinetics wnOOQnW5Un4 6097 33. Reaction mechanism pkNwvhEm1GQ 6098 35. Enzyme catalysis PJFW3Vrv-5w 6099 32. Nuclear chemistry and elementary reactions qTrw6f_sbOw 6100 36. Biochemistry I3g7KRIvQPI 6101 24. Balancing oxidation/reduction equations C_Kg0EMPEJ8 6102 29. Metals in biology iev2WlpKoGc 6103 25. Electrochemical cells llaa-iEYDLI 6104 14. Molecular orbital theory oQ-qDHADAaM 6105 31. Rate laws TgbFcaozNzs 6106 30. Magnetism and spectrochemical theory pZEjVRqe-N4 6107 28. Crystal field theory sQx1Y_CArYA 6108 26. Chemical and biological oxidation/reduction reactions SbabED1wRMo 6109 16. Determining hybridization in complex molecules; Thermochemistry, bond energies/bond enthalpies XxvD0Yh9qCM 6110 23. Acid-base titrations 3AVSORIJJJY 6111 15. Valence bond theory and hybridization Y9QVFYjiOIA 6112 12. Exceptions to Lewis structure rules; Ionic bonds MUUl2yd3C9s 6113 20. Le Chatelier's principle and applications to blood-oxygen levels pAuRZr0AHhI 6114 22. Chemical and biological buffers 7mcSMG0-3FU 6115 18. Free energy and control of spontaneity GOBzZMaiMss 6116 21. Acid-base equilibrium: Is MIT water safe to drink? ZjVicrRxFtM 6117 17. Entropy and disorder eyDAcbzXgb4 6118 19. Chemical equilibrium f7RRqxv2pzg 6119 8. Multielectron atoms and electron configurations iWZDVWdtjMY 6120 4. Wave-particle duality of matter, Schrödinger equation MBz0swcfztQ 6121 5. Hydrogen atom energy levels l-BNoAPe6qo 6122 2. Discovery of electron and nucleus, need for quantum mechanics LPh2Ut7D4WA 6123 9. Periodic trends Ey25vULQ6YM 6124 3. Wave-particle duality of light N1FTKBCq8V0 6125 7. p-orbitals -c-X8zk0ywo 6126 1. The importance of chemical principles NW4TqKfPQLw 6127 Course Introduction to MIT 1.061 by Professor Nepf ZD2sKqPxPIk 6128 Lec 10 | MIT 6.189 Multicore Programming Primer, IAP 2007 Y1mrnc1hz9g 6129 Lec 5 | MIT 6.189 Multicore Programming Primer, IAP 2007 WikcTwXQXfA 6130 Lec 2 | MIT 6.189 Multicore Programming Primer, IAP 2007 V1BIvbUlhgU 6131 Lec 7 | MIT 6.189 Multicore Programming Primer, IAP 2007 UJji2L8XFZQ 6132 Lec 17 | MIT 6.189 Multicore Programming Primer, IAP 2007 4_B2x3UVLAo 6133 Lec 6 | MIT 6.189 Multicore Programming Primer, IAP 2007 qR9y8dx_pW4 6134 Lec 9 | MIT 6.189 Multicore Programming Primer, IAP 2007 o8XojnApGc4 6135 Lec 3 | MIT 6.450 Principles of Digital Communications I, Fall 2006 SLcZXbyGC3E 6136 Lecture 9B | MIT 6.001 Structure and Interpretation, 1986 jPDAPmx4pXE 6137 Lecture 9A | MIT 6.001 Structure and Interpretation, 1986 IZqwi0wJovM 6138 23. Differential Equations and exp(At) Go2aLo7ZOlU 6139 33. Left and Right Inverses; Pseudoinverse M0Sa8fLOajA 6140 26. Complex Matrices; Fast Fourier Transform QNpj-gOXW9M 6141 20. Cramer's Rule, Inverse Matrix, and Volume umt6BB1nJ4w 6142 Lec 25 | MIT 18.06 Linear Algebra, Spring 2005 13r9QY6cmjc 6143 22. Diagonalization and Powers of A srxexLishgY 6144 18. Properties of Determinants vF7eyJ2g3kU 6145 27. Positive Definite Matrices and Minima Ts3o2I8_Mxc 6146 30. Linear Transformations and Their Matrices 8o5Cmfpeo6g 6147 6. Column Space and Nullspace l88D4r74gtM 6148 13. Quiz 1 Review yjBerM5jWsc 6149 9. Independence, Basis, and Dimension FX4C-JpTFgY 6150 3. Multiplication and Inverse Matrices 9Q1q7s1jTzU 6151 8. Solving Ax = b: Row Reduced Form R 23LLB9mNJvc 6152 19. Determinant Formulas and Cofactors QVKj3LADCnA 6153 2. Elimination with Matrices. VqP2tREMvt0 6154 7. Solving Ax = 0: Pivot Variables, Special Solutions HgC1l_6ySkc 6155 32. Quiz 3 Review RWvi4Vx4CDc 6156 34. Final Course Review YzZUIYRCE38 6157 14. Orthogonal Vectors and Subspaces nHlE7EgJFds 6158 10. The Four Fundamental Subspaces JibVXBElKL0 6159 5. Transposes, Permutations, Spaces R^n osh80YCg_GM 6160 16. Projection Matrices and Least Squares Y_Ac6KiQ1t0 6161 15. Projections onto Subspaces 6-wh6yvk6uc 6162 12. Graphs, Networks, Incidence Matrices 2IdtqGM6KWU 6163 11. Matrix Spaces; Rank 1; Small World Graphs QstZW4N4SX8 6164 Lec 9 | MIT 6.450 Principles of Digital Communications I, Fall 2006 zkR2TT7x8uQ 6165 Lec 22 | MIT 6.450 Principles of Digital Communications I, Fall 2006 2DbwtCePzWg 6166 Lec 21 | MIT 6.450 6.450 Principles of Digital Communications I, Fall 2006 zJ56b-aErN4 6167 Lec 14 | MIT 6.450 Principles of Digital Communications I, Fall 2006 cfL8blVkE1E 6168 Lec 24 | MIT 6.450 Principles of Digital Communications I, Fall 2006 4TvgSw4SKdk 6169 Lec 16 | MIT 6.450 Principles of Digital Communications I, Fall 2006 skW0oXoAU0M 6170 Lec 12 | MIT 6.450 Principles of Digital Communications I, Fall 2006 DnQruAbpusc 6171 Lec 19 | MIT 6.450 Principles of Digital Communications I, Fall 2006 8PScXRfu2po 6172 Lec 18 | MIT 6.450 Principles of Digital Communications I, Fall 2006 kJR59TZz1CI 6173 Lec 20 | MIT 6.450 Principles of Digital Communications I, Fall 2006 _7qq1JYj2kM 6174 Lec 11 | MIT 6.450 Principles of Digital Communications I, Fall 2006 qU6NkB4xE7U 6175 Lec 10 | MIT 6.450 Principles of Digital Communications I, Fall 2006 _oKLtT7F9hg 6176 Lec 17 | MIT 6.450 Principles of Digital Communications I, Fall 2006 zB9aY8tzd74 6177 Lec 15 | MIT 6.450 Principles of Digital Communications I, Fall 2006 PMd2ZmcvMBI 6178 Lec 13 | MIT 6.450 Principles of Digital Communications I, Fall 2006 pQDVHvW19vI 6179 Lec 23 | MIT 6.450 Principles of Digital Communications I, Fall 2006 dSviy9E6Pz0 6180 Lec 4 | MIT 6.450 Principles of Digital Communications I, Fall 2006 wzUaJmN9Mf0 6181 Lec 7 | MIT 6.450 Principles of Digital Communications I, Fall 2006 IgN5JQSh8w4 6182 Lec 5 | MIT 6.450 Principles of Digital Communications I, Fall 2006 KXFF8m4uGDc 6183 Lec 1 | MIT 6.450 Principles of Digital Communications I, Fall 2006 503wzjz8czs 6184 Lec 2 | MIT 6.450 Principles of Digital Communications I, Fall 2006 rei6tud0Tsg 6185 Lec 6 | MIT 6.450 Principles of Digital Communications I, Fall 2006 vulw9qGXbH0 6186 Lec 8 | MIT 6.450 Principles of Digital Communications I, Fall 2006 DCub3iqteuI 6187 Lecture 6B | MIT 6.001 Structure and Interpretation, 1986 -MI0b4h3rS0 6188 Lec 15 | MIT 18.01 Single Variable Calculus, Fall 2007 sRIDVAcoG5A 6189 Lec 13 | MIT 18.01 Single Variable Calculus, Fall 2007 4Q37iOyBq44 6190 Lec 14 | MIT 18.01 Single Variable Calculus, Fall 2007 2s2_FAf-yQs 6191 Lecture 10B | MIT 6.001 Structure and Interpretation, 1986 kNmiTTKiYd4 6192 Lecture 10A | MIT 6.001 Structure and Interpretation, 1986 0m6hoOelZH8 6193 Lecture 7A | MIT 6.001 Structure and Interpretation, 1986 R3uRidfSpc4 6194 Lecture 8B | MIT 6.001 Structure and Interpretation, 1986 cyVXjnFL2Ps 6195 Lecture 8A | MIT 6.001 Structure and Interpretation, 1986 t5EI5fXX8K0 6196 Lecture 7B | MIT 6.001 Structure and Interpretation, 1986 a2Qt9uxhNSM 6197 Lecture 6A | MIT 6.001 Structure and Interpretation, 1986 h6Z7vx9iUB8 6198 Lecture 4B | MIT 6.001 Structure and Interpretation, 1986 jl8EHP1WrWY 6199 Lecture 5A | MIT 6.001 Structure and Interpretation, 1986 SsBxcpkyMMw 6200 Lecture 5B | MIT 6.001 Structure and Interpretation, 1986 amf5lTZ0UTc 6201 Lecture 4A | MIT 6.001 Structure and Interpretation, 1986 2QgZVYI3tDs 6202 Lecture 3A | MIT 6.001 Structure and Interpretation, 1986 ymsbTVLbyN4 6203 Lecture 2B | MIT 6.001 Structure and Interpretation, 1986 X21cKVtGvYk 6204 Lecture 3B | MIT 6.001 Structure and Interpretation, 1986 erHp3r6PbJk 6205 Lecture 2A | MIT 6.001 Structure and Interpretation, 1986 dlbMuv-jix8 6206 Lecture 1B | MIT 6.001 Structure and Interpretation, 1986 2Op3QLzMgSY 6207 Lecture 1A | MIT 6.001 Structure and Interpretation, 1986 aGnegoNe8Xo 6208 Lec 33 | MIT 18.085 Computational Science and Engineering I, Fall 2008 tkyv1D1tZGg 6209 Rec 11 | MIT 18.085 Computational Science and Engineering I, Fall 2008 gYME3EbIqV4 6210 Lec 27 | MIT 18.085 Computational Science and Engineering I, Fall 2008 Y_lWzD2vigk 6211 Lec 35 | MIT 18.085 Computational Science and Engineering I, Fall 2008 Kv7eOsMVx6E 6212 Lec 34 | MIT 18.085 Computational Science and Engineering I, Fall 2008 4ctngXQrmDc 6213 Lec 32 | MIT 18.085 Computational Science and Engineering I, Fall 2008 StnOg-q2tS8 6214 Lec 28 | MIT 18.085 Computational Science and Engineering I, Fall 2008 fJSSVcFhA0Y 6215 Rec 10 | MIT 18.085 Computational Science and Engineering I, Fall 2008 UdpdZ0diXUg 6216 Lec 31 | MIT 18.085 Computational Science and Engineering I, Fall 2008 9iJryWzLDIw 6217 Lec 29 | MIT 18.085 Computational Science and Engineering I, Fall 2008 E1o1h-_4Bn4 6218 Lec 25 | MIT 18.085 Computational Science and Engineering I, Fall 2008 a6sPpQXST5E 6219 Lec 26 | MIT 18.085 Computational Science and Engineering I, Fall 2008 J0pZyXThRmM 6220 Lec 36 | MIT 18.085 Computational Science and Engineering I, Fall 2008 w0jVqJlzdI8 6221 Rec 13 | MIT 18.085 Computational Science and Engineering I, Fall 2008 bElQTlIWCr8 6222 Lec 30 | MIT 18.085 Computational Science and Engineering I, Fall 2008 JWrrPuJf2nA 6223 Rec 12 | MIT 18.085 Computational Science and Engineering I, Fall 2008 PwKN0blvNkk 6224 Lec 20 | MIT 18.085 Computational Science and Engineering I, Fall 2008 0egP7_kq23E 6225 Rec 5 | MIT 18.085 Computational Science and Engineering I, Fall 2008 Q95lUJagN0A 6226 Lec 13 | MIT 18.085 Computational Science and Engineering I, Fall 2008 w26JaJX8GMk 6227 Rec 6 | MIT 18.085 Computational Science and Engineering I, Fall 2008 28tqrlZSMhk 6228 Rec 7 | MIT 18.085 Computational Science and Engineering I, Fall 2008 wTM4v2gIeqk 6229 Lec 19 | MIT 18.085 Computational Science and Engineering I, Fall 2008 uMdPZuT7f70 6230 Lec 24 | MIT 18.085 Computational Science and Engineering I, Fall 2008 GQbq9G__--Y 6231 Lec 12 | MIT 18.085 Computational Science and Engineering I, Fall 2008 mFGdF9TAfmE 6232 Lec 16 | MIT 18.085 Computational Science and Engineering I, Fall 2008 Siqu0aOOQCM 6233 Lec 21 | MIT 18.085 Computational Science and Engineering I, Fall 2008 SreJp2U0Vio 6234 Lec 22 | MIT 18.085 Computational Science and Engineering I, Fall 2008 4B9aIlwEZcQ 6235 Lec 18 | MIT 18.085 Computational Science and Engineering I, Fall 2008 Vw4Gw9No008 6236 Lec 17 | MIT 18.085 Computational Science and Engineering I, Fall 2008 zI9cSV3QKz0 6237 Rec 9 | MIT 18.085 Computational Science and Engineering I, Fall 2008 mhLI51d9LDc 6238 Lec 23 | MIT 18.085 Computational Science and Engineering I, Fall 2008 bciGyT6eeOE 6239 Lec 14 | MIT 18.085 Computational Science and Engineering I, Fall 2008 oZnCOIbesiA 6240 Lec 11 | MIT 18.085 Computational Science and Engineering I, Fall 2008 XUB7FcjaLRI 6241 Rec 8 | MIT 18.085 Computational Science and Engineering I, Fall 2008 ZOBgPxmXeVM 6242 Lec 15 | MIT 18.085 Computational Science and Engineering I, Fall 2008 SI_GKdFQmds 6243 Lec 16 | MIT 6.189 Multicore Programming Primer, IAP 2007 SR6dDuTbEwo 6244 Recitation 4: Cell debugging tools | MIT 6.189 Multicore Programming Primer, IAP 2007 zg1bHfos6U8 6245 Rec 6 | MIT 6.189 Multicore Programming Primer, IAP 2007 hd4roBsrYA8 6246 Project: Battery simulation | MIT 6.189 Multicore Programming Primer, IAP 2007 e2WwaVi6VwA 6247 Project: Backgammon tutor | MIT 6.189 Multicore Programming Primer, IAP 2007 gIuL_WdfH74 6248 Rec 5 | MIT 6.189 Multicore Programming Primer, IAP 2007 xDnq_b2784c 6249 Project: Global illumination | MIT 6.189 Multicore Programming Primer, IAP 2007 EkMfTvmLJl0 6250 Project: Blue-steel ray tracer | MIT 6.189 Multicore Programming Primer, IAP 2007 s8dZi6eqsJU 6251 Project: Software radio | MIT 6.189 Multicore Programming Primer, IAP 2007 Nd2SBfrsaw4 6252 Project: Molecular dynamics | MIT 6.189 Multicore Programming Primer, IAP 2007 A0f4HUTooM4 6253 Project: Speech synthesis | MIT 6.189 Multicore Programming Primer, IAP 2007 r7rLHHd43MU 6254 Projects award ceremony | MIT 6.189 Multicore Programming Primer, IAP 2007 Wn3QDv-Dt3M 6255 Projects Closing | MIT 6.189 Multicore Programming Primer, IAP 2007 0a1EYZLXQRM 6256 Projects Introduction | MIT 6.189 Multicore Programming Primer, IAP 2007 zgbsyim8uUQ 6257 Lec 14 | MIT 6.189 Multicore Programming Primer, IAP 2007 X3_SfVMyE3k 6258 Lec 15 | MIT 6.189 Multicore Programming Primer, IAP 2007 5F3HVitoWHc 6259 Lec 8 | MIT 6.189 Multicore Programming Primer, IAP 2007 vhmiSugPlW0 6260 Lec 18 | MIT 6.189 Multicore Programming Primer, IAP 2007 sOiuF18PTIs 6261 Lec 11 | MIT 6.189 Multicore Programming Primer, IAP 2007 f2_lvRuqp50 6262 Lec 3 | MIT 6.189 Multicore Programming Primer, IAP 2007 SemWOqUfMAY 6263 Lec 12 | MIT 6.189 Multicore Programming Primer, IAP 2007 G0iYkb9YiRg 6264 Lec 1 (cont.) | MIT 6.189 Multicore Programming Primer, IAP 2007 vhIwuNJzVG4 6265 Lec 1 | MIT 6.189 Multicore Programming Primer, IAP 2007 qhH6ysHlaiM 6266 Lec 4 | MIT 6.189 Multicore Programming Primer, IAP 2007 tynCH4dosA8 6267 Lec 1 | MIT 3.320 Atomistic Computer Modeling of Materials 0oBJN8F616U 6268 Rec 1 | MIT 18.085 Computational Science and Engineering I, Fall 2008 h5KiY9lvHc4 6269 Lec 5 | MIT 18.085 Computational Science and Engineering I, Fall 2008 5Pw5k0z1L4Q 6270 Lec 4 | MIT 18.085 Computational Science and Engineering I, Fall 2008 pN7zitwRq58 6271 Lec 8 | MIT 18.085 Computational Science and Engineering I, Fall 2008 2OmTX1AeVAg 6272 Rec 4 | MIT 18.085 Computational Science and Engineering I, Fall 2008 wt7UJckgvxs 6273 Rec 3 | MIT 18.085 Computational Science and Engineering I, Fall 2008 CgfkEUOFAj0 6274 Lec 1 | MIT 18.085 Computational Science and Engineering I, Fall 2008 fR_pGtAWHpY 6275 Lec 7 | MIT 18.085 Computational Science and Engineering I, Fall 2008 0BAMQmT-tf0 6276 Lec 9 | MIT 18.085 Computational Science and Engineering I, Fall 2008 2Ola674-PPw 6277 Lec 6 | MIT 18.085 Computational Science and Engineering I, Fall 2008 _hYaOtW4XY4 6278 Rec 2 | MIT 18.085 Computational Science and Engineering I, Fall 2008 11y8_XTbwGo 6279 Lec 3 | MIT 18.085 Computational Science and Engineering I, Fall 2008 -agCn_nWztQ 6280 Lec 2 | MIT 18.085 Computational Science and Engineering I, Fall 2008 V5EjSvx1vw0 6281 Lec 10 | MIT 18.085 Computational Science and Engineering I, Fall 2008 YN7k_bXXggY 6282 Lec 12 | MIT 18.01 Single Variable Calculus, Fall 2007 0qEcpuOy0Uo 6283 Lec 10 | MIT 18.01 Single Variable Calculus, Fall 2007 twzGBqPeW0M 6284 Lec 11 | MIT 18.01 Single Variable Calculus, Fall 2007 BSAA0akmPEU 6285 Lec 9 | MIT 18.01 Single Variable Calculus, Fall 2007 wu8kXZSAp20 6286 Lec 29: Divergence theorem (cont.): applications & proof | MIT 18.02 Multivariable Calculus, Fall 07 sr7kCpzAuYw 6287 Lec 32: Stokes' theorem (cont.); review | MIT 18.02 Multivariable Calculus, Fall 2007 WfEQabCGAqI 6288 Lec 28: Divergence theorem | MIT 18.02 Multivariable Calculus, Fall 2007 RMBGQtwkoyU 6289 Lec 26: Spherical coordinates; surface area | MIT 18.02 Multivariable Calculus, Fall 2007 phk05iSMezA 6290 Lec 27: Vector fields in 3D; surface integrals & flux | MIT 18.02 Multivariable Calculus, Fall 2007 ZwpwmGP5ITM 6291 Lec 34: Final review | MIT 18.02 Multivariable Calculus, Fall 2007 44R5HgbrUmc 6292 Lec 25: Triple integrals in rectangular & cylindrical | MIT 18.02 Multivariable Calculus, Fall 2007 tzoYhe3H5dM 6293 Lec 31: Stokes' theorem | MIT 18.02 Multivariable Calculus, Fall 2007 24v9onS9Kcg 6294 Lec 35: Final review (cont.) | MIT 18.02 Multivariable Calculus, Fall 2007 seO7-TwXH_I 6295 Lec 30: Line integrals in space, curl, exactness... | MIT 18.02 Multivariable Calculus, Fall 2007 BChhAS1sFvA 6296 Lec 33: Topological considerations; Maxwell's equations | MIT 18.02 Multivariable Calculus, Fall 07 U1EcnfTKXJ0 6297 Lec 7: Review | MIT 18.02 Multivariable Calculus, Fall 2007 xrypSZU8cBE 6298 Lec 19: Vector fields and line integrals in the plane | MIT 18.02 Multivariable Calculus, Fall 2007 _CdoRiNSrqI 6299 Lec 23: Flux; normal form of Green's theorem | MIT 18.02 Multivariable Calculus, Fall 2007 o7UCBjGsRTE 6300 Lec 20: Path independence and conservative fields | MIT 18.02 Multivariable Calculus, Fall 2007 PnPIqh7Frlw 6301 Lec 24: Simply connected regions; review | MIT 18.02 Multivariable Calculus, Fall 2007 z5TPjZrsp2k 6302 Lec 21: Gradient fields and potential functions | MIT 18.02 Multivariable Calculus, Fall 2007 tYdoS0tkAHA 6303 Lec 22: Green's theorem | MIT 18.02 Multivariable Calculus, Fall 2007 YP_B0AapU0c 6304 Lec 16: Double integrals | MIT 18.02 Multivariable Calculus, Fall 2007 60e4hdCi1D4 6305 Lec 17: Double integrals in polar coords; applications | MIT 18.02 Multivariable Calculus, Fall 2007 UZb9hZIAvL4 6306 Lec 18: Change of variables | MIT 18.02 Multivariable Calculus, Fall 2007 3_goGnJm5sA 6307 Lec 10: Second derivative test; boundaries & infinity | MIT 18.02 Multivariable Calculus, Fall 2007 9v25gg2qJYE 6308 Lec 6 | MIT 18.01 Single Variable Calculus, Fall 2007 7eZVshlT33Q 6309 Lec 11: Differentials; chain rule | MIT 18.02 Multivariable Calculus, Fall 2007 15HVevXRsBA 6310 Lec 13: Lagrange multipliers | MIT 18.02 Multivariable Calculus, Fall 2007 kCPVBl953eY 6311 Lec 3 | MIT 18.01 Single Variable Calculus, Fall 2007 23xbkrpQuAo 6312 Lec 14: Non-independent variables | MIT 18.02 Multivariable Calculus, Fall 2007 UYe98CcxPbs 6313 Lec 9: Max-min problems; least squares | MIT 18.02 Multivariable Calculus, Fall 2007 2XraaWefBd8 6314 Lec 12: Gradient; directional derivative; tangent plane | MIT 18.02 Multivariable Calculus, Fall 07 dK3NEf13nPc 6315 Lec 8: Level curves; partial derivatives; tangent plane | MIT 18.02 Multivariable Calculus, Fall 07 ChiM2-MV-qM 6316 Lec 15: Partial differential equations; review | MIT 18.02 Multivariable Calculus, Fall 2007 ryLdyDrBfvI 6317 Lec 2 | MIT 18.01 Single Variable Calculus, Fall 2007 5q_3FDOkVRQ 6318 Lec 5 | MIT 18.01 Single Variable Calculus, Fall 2007 eHJuAByQf5A 6319 Lec 7: Exam 1 review | MIT 18.01 Single Variable Calculus, Fall 2007 jbIQW0gkgxo 6320 Lec 1 | MIT 18.01 Single Variable Calculus, Fall 2007 4sTKcvYMNxk 6321 Lec 4 | MIT 18.01 Single Variable Calculus, Fall 2007 bHdzkFrgRcA 6322 Lec 3: Matrices; inverse matrices | MIT 18.02 Multivariable Calculus, Fall 2007 9FLItlbBUPY 6323 Lec 2: Determinants; cross product | MIT 18.02 Multivariable Calculus, Fall 2007 57jzPlxf4fk 6324 Lec 5: Parametric equations for lines and curves | MIT 18.02 Multivariable Calculus, Fall 2007 YBajUR3EFSM 6325 Lec 4: Square systems; equations of planes | MIT 18.02 Multivariable Calculus, Fall 2007 0D4BbCa4gHo 6326 Lec 6: Velocity, acceleration; Kepler's second law | MIT 18.02 Multivariable Calculus, Fall 2007 PxCxlsl_YwY 6327 Lec 1: Dot product | MIT 18.02 Multivariable Calculus, Fall 2007 zjUDy6a5vx4 6328 Lec 25 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 cJOHERGcGm4 6329 Lec 24 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 F0VsQWWVWU4 6330 Lec 23 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 kBwUoWpeH_Q 6331 Lec 12 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 s7QSM_hlS1U 6332 Lec 8 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 vgELyZ9LXX4 6333 Lec 9 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 PYvJmLKhM-Y 6334 Lec 22 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 O3hI9FdxFOM 6335 Lec 10 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 JZHBa-rLrBA 6336 Lec 7 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 qh5lSHCBiRs 6337 Lec 13 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 RHyGlha7bjE 6338 Lec 11 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 Sygq1e0xWnM 6339 Lec 19 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 FPEMBWg_WlY 6340 Lec 16 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 2RxCCEHlEys 6341 Lec 14 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 xhG2DyCX3uA 6342 Lec 17 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 Ttezuzs39nk 6343 Lec 18 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 V5hZoJ6uK-s 6344 Lec 15 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 mR_RUjsJnV8 6345 Lec 6 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 0VqawRl3Xzs 6346 Lec 5 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 vK_q-C-kXhs 6347 Lec 4 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 JPyuH4qXLZ0 6348 Lec 1 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 whjt_N9uYFI 6349 Lec 2 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 -EQTVuAhSFY 6350 Lec 3 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 SqfNSRi7_bc 6351 Lec 20 | MIT 6.451 Principles of Digital Communication II, Spring 2005 qYqI9IWyv-c 6352 Lec 33 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 dkHcgAzsvAk 6353 Lec 35 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 6LYuK8qI0_s 6354 Lec 29 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 HYh3aq_NG8Q 6355 Lec 27 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 lLdUm6AU0aw 6356 Lec 32 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 oKwGNgCTd-Q 6357 Lec 34 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 Q7mrSQkSB9U 6358 Lec 31 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 RT_v0PhXP5E 6359 Lec 26 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 DZ138JSpoxQ 6360 Lec 30 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 U2BNmEnry6E 6361 Lec 36 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 u6s_jy0n6vI 6362 Lec 24 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 2QdI6_gEyx4 6363 Lec 20 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 BTNsoSNR5B0 6364 Lec 28 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 wCSl5eeMSDY 6365 Lec 23 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 RUz-DJz3--I 6366 Lec 21 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 xgUCzL3TD1g 6367 Lec 25 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 eXUFm8lA5yE 6368 Lec 22 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 rWLeg-W4EF0 6369 Lec 5 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 RrVq7Yduz2g 6370 Lec 3 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 DqEmrt_xQTg 6371 Lec 9 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 e124JF_DHCQ 6372 Lec 8 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 g14939TMTCE 6373 Lec 4 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 8Xpn2jorigU 6374 Lec 6 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 QrzHB9_kHPE 6375 Lec 10 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 DOq2YChGmlg 6376 Lec 16 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 Cc2l1QTTZA4 6377 Lec 15 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 6uLKZSoHnrc 6378 Lec 7 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 r4fGG_7NQr8 6379 Lec 11 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 TDqx8Zv1rRo 6380 Lec 2 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 6kBqi9vVC6s 6381 Lec 18 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 gLo958Kdeoo 6382 Lec 14 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 srjNMMtPATo 6383 Lec 13 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 Bd7PVX7rohQ 6384 Lec 19 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 jsoD3oZAAXI 6385 Lec 12 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 _PmJoExiSPo 6386 Lec 17 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 vT_6DlaHcWQ 6387 MIT 3.60 | Lec 1a: Symmetry, Structure, Tensor Properties of kLqduWF6GXE 6388 Lec 1 | MIT 5.60 Thermodynamics & Kinetics, Spring 2008 It2ggiEoIoI 6389 Lec 2 | MIT 11.309J Sensing Place: Photography as Inquiry Zk91WpvA0-c 6390 Lec 7 | MIT 11.309J Sensing Place: Photography as Inquiry ptjKegETGuA 6391 Lec 6 | MIT 11.309J Sensing Place: Photography as Inquiry vvsFk4u_FeU 6392 Lec 4 | MIT 11.309J Sensing Place: Photography as Inquiry r9PqDkaGGcU 6393 Lec 8 | MIT 11.309J Sensing Place: Photography as Inquiry Fxy3tsWDcpY 6394 Lec 3 | MIT 11.309J Sensing Place: Photography as Inquiry 2t5e-6vvg48 6395 Lec 1 | MIT 11.309J Sensing Place: Photography as Inquiry H1k6JN63JTo 6396 Lec 5 | MIT 11.309J Sensing Place: Photography as Inquiry Mv2aDOe1o4w 6397 Lec 4 | MIT 11.945 Springfield Studio, Fall 2005 4jqpHCWVq6Y 6398 MIT: Joint Fact Finding in Science Intensive Policy Disputes 765wa_UWnLY 6399 MIT: Joint Fact Finding in Science Intensive Policy Disputes muvnmdiAJbM 6400 Lec 8 | MIT 11.945 Springfield Studio, Fall 2005 JS4JD2MpFN8 6401 Field Trip 2 | MIT 11.945 Springfield Studio, Fall 2005 mps0Zsi0-vU 6402 Field Trip 4 | MIT 11.945 Springfield Studio, Fall 2005 tWxhCS3fWrg 6403 MIT | Internet Technology in Local and Global Communities s_dn2M7JWy8 6404 Lec 1 | MIT STS.069 Technology in a Dangerous World 5jrZ_AxAb5s 6405 Lec 3 | MIT STS.069 Technology in a Dangerous World X2GJVlLC8bc 6406 Lec 4 | MIT STS.069 Technology in a Dangerous World mYaHarsAF5w 6407 13. Cosmic Structure Formation; From Inflation to Galaxies | MIT 8.224 Exploring Black Holes 4YRf-1mLlyw 6408 Lec 2 | MIT STS.069 Technology in a Dangerous World mVqLF6FU1-o 6409 8. X-Ray Binaries and the Search for Black Holes | MIT 8.224 Exploring Black Holes 8MWNs7Wfk84 6410 5. Einstein's Field Equations | MIT 8.224 Exploring Black Holes SEcVf93k0ZE 6411 2. The Universe: Questions You Were Afraid to Ask | MIT 8.224 Exploring Black Holes -fD51fZvZH8 6412 10. The Universe and Three Examples | MIT 8.224 Exploring Black Holes bFGiQEEvh18 6413 1. Introduction to the Class | MIT 8.224 Exploring Black Holes ozjMIKustF4 6414 Lec 29 | MIT 18.085 Computational Science and Engineering I wcVY654ZCd8 6415 Lec 26 | MIT 18.085 Computational Science and Engineering I gv-AB35V2k8 6416 Lec 1 | MIT 18.086 Mathematical Methods for Engineers II GTKVDKuh9Qc 6417 Lec 19 | MIT 18.085 Computational Science and Engineering I YfmkNaRq9yc 6418 Lec 24 | MIT 18.085 Computational Science and Engineering I LeafEHx9d0c 6419 Lec 28 | MIT 18.085 Computational Science and Engineering I OsVJf-P7uHk 6420 Lec 11 | MIT 18.085 Computational Science and Engineering I 4fQAlD5wZKA 6421 Lec 27 | MIT 18.085 Computational Science and Engineering I 38ZN2IhWgOE 6422 Lec 21 | MIT 18.085 Computational Science and Engineering I 0vVPy62Zpe8 6423 Lec 2 | MIT 18.085 Computational Science and Engineering I e9oP4O0P2R8 6424 Lec 6 | MIT 18.085 Computational Science and Engineering I 5a2Poe_N0sQ 6425 Lec 30 | MIT 18.085 Computational Science and Engineering I Ew4VqTsP2js 6426 Lec 7 | MIT 18.085 Computational Science and Engineering I 5e5PPseWX6Y 6427 Lec 13 | MIT 18.085 Computational Science and Engineering I nj4Al7MVAO0 6428 Lec 23 | MIT 18.085 Computational Science and Engineering I KkyO_u6Ze98 6429 Lec 18 | MIT 18.085 Computational Science and Engineering I oluUlr0Uxz8 6430 Lec 25 | MIT 18.085 Computational Science and Engineering I 4t_Fqd5Hd2c 6431 Lec 3 | MIT 18.085 Computational Science and Engineering I 4oIsQdCjMeE 6432 Lec 31 | MIT 18.085 Computational Science and Engineering I d0D3VwBh5UQ 6433 Lec 16 | MIT 18.085 Computational Science and Engineering I HzLSToubVI8 6434 Lec 8 | MIT 18.085 Computational Science and Engineering I ZV9n85XpEfg 6435 Lec 12 | MIT 18.085 Computational Science and Engineering I 7pxSbSmPv2g 6436 Lec 9 | MIT 18.085 Computational Science and Engineering I ywK_miSFVew 6437 Lec 14 | MIT 18.085 Computational Science and Engineering I FWtYuLFIUUM 6438 Lec 22 | MIT 18.085 Computational Science and Engineering I fvrbkQOzffg 6439 Lec 10 | MIT 18.085 Computational Science and Engineering I HG43z9xopU8 6440 Lec 4 | MIT 18.085 Computational Science and Engineering I RpeaxINv2Yk 6441 Lec 15 | MIT 18.085 Computational Science and Engineering I h8S3HJktpsA 6442 Lec 17 | MIT 18.085 Computational Science and Engineering I f2eYLK6TpRs 6443 Lec 1 | MIT 18.085 Computational Science and Engineering I kIl6LsJuxqI 6444 Lec 5 | MIT 18.085 Computational Science and Engineering I 00ERnGKqzrQ 6445 Lec 20 | MIT 18.085 Computational Science and Engineering I QCQYzdxBaJU 6446 Lec 32 | MIT 18.085 Computational Science and Engineering I iVUsEwSg-lw 6447 Lec 27 | MIT 18.086 Mathematical Methods for Engineers II c9XosfcouiM 6448 Lec 24 | MIT 18.086 Mathematical Methods for Engineers II vIydsgrYGIY 6449 Lec 18 | MIT 18.086 Mathematical Methods for Engineers II kyx2QgGkEpc 6450 Lec 20 | MIT 18.086 Mathematical Methods for Engineers II pEuuJ5E7ZS0 6451 Lec 14 | MIT 18.086 Mathematical Methods for Engineers II ByGXz_uHEdM 6452 Lec 7 | MIT 18.086 Mathematical Methods for Engineers II NEsObJTwDXI 6453 Lec 29 | MIT 18.086 Mathematical Methods for Engineers II j-C6QC5ufSw 6454 Lec 25 | MIT 18.086 Mathematical Methods for Engineers II dxNyJxI_2eI 6455 Lec 3 | MIT 18.086 Mathematical Methods for Engineers II fpwsw7SdkyY 6456 Lec 28 | MIT 18.086 Mathematical Methods for Engineers II 94nmfDkTL-E 6457 Lec 23 | MIT 18.086 Mathematical Methods for Engineers II NpTzMWTYbM8 6458 Lec 10 | MIT 18.086 Mathematical Methods for Engineers II zIK5EnoiLL0 6459 Lec 22 | MIT 18.086 Mathematical Methods for Engineers II zha1744fTRs 6460 Lec 19 | MIT 18.086 Mathematical Methods for Engineers II S6dw885-SZI 6461 Lec 13 | MIT 18.086 Mathematical Methods for Engineers II LtNVodIs1dI 6462 Lec 15 | MIT 18.086 Mathematical Methods for Engineers II ZpOJJk6en2o 6463 Lec 11 | MIT 18.086 Mathematical Methods for Engineers II 0aa6fUHTTeU 6464 Lec 5 | MIT 18.086 Mathematical Methods for Engineers II nlO9ci0kPLg 6465 Lec 2 | MIT 18.086 Mathematical Methods for Engineers II sleOqiMUTXE 6466 Lec 9 | MIT 18.086 Mathematical Methods for Engineers II 7dVYOOHB4g4 6467 Lec 21 | MIT 18.086 Mathematical Methods for Engineers II r1-r1t5i58g 6468 Lec 12 | MIT 18.086 Mathematical Methods for Engineers II XPo4dHK48Nw 6469 Lec 16 | MIT 18.086 Mathematical Methods for Engineers II HHwDX-3IPT0 6470 Lec 4 | MIT 18.086 Mathematical Methods for Engineers II 9-NXsFQwzL4 6471 Lec 6 | MIT 18.086 Mathematical Methods for Engineers II xzUOJ-uQ8F0 6472 Lec 26 | MIT 18.086 Mathematical Methods for Engineers II FrrTXj13DNk 6473 Lec 8 | MIT 18.086 Mathematical Methods for Engineers II Y25UBGeu_2g 6474 Lec 17 | MIT 18.086 Mathematical Methods for Engineers II ljek94mCdOw 6475 Lec 8 | Community-Owned Enterprise and Civic Participation ktm3HYt2kVs 6476 Lec 6 | Community-Owned Enterprise and Civic Participation Z-KOtbLwjfM 6477 Lec 6 | Community-Owned Enterprise and Civic Participation HwiUiSx2pOc 6478 Lec 8 | Community-Owned Enterprise and Civic Participation 0QJRG7e2PPk 6479 Lec 5 | MIT 11.949 11.949 City Visions: Past and Future rJ8tk8p_V2U 6480 Day 2 | Deliberative Democracy and Dispute Resolution fvJBjtQiV6Q 6481 Lec 1 | MIT 11.949 11.949 City Visions: Past and Future HmqzZ-lb5zk 6482 Lec 11 | MIT 11.949 11.949 City Visions: Past and Future DWYDS3dFNLg 6483 Lec 13 | MIT 11.949 11.949 City Visions: Past and Future _dhcifVwZlA 6484 Day 1 | Deliberative Democracy and Dispute Resolution HAajO6u2of4 6485 Day 2 | Deliberative Democracy and Dispute Resolution KM8NxWOdJjk 6486 Day 2 | Deliberative Democracy and Dispute Resolution ZR-BWj_sMV0 6487 Day 2 | Deliberative Democracy and Dispute Resolution 2dms7bxzoXk 6488 MIT 3.60 | Lec 4b: Symmetry, Structure, Tensor Properties of Materials 8gOVW9fKOcY 6489 MIT 3.60 | Lec 14b: Symmetry, Structure, Tensor Properties of Materials -HJE0OYHTH4 6490 MIT 3.60 | Lec 6a: Symmetry, Structure, Tensor Properties of Materials pi1IagGYJ3E 6491 MIT 3.60 | Lec 2b: Symmetry, Structure, Tensor Properties of Materials 1v17Gfdydfg 6492 MIT 3.60 | Lec 11b: Symmetry, Structure, Tensor Properties of Materials ew9ujMlyOTU 6493 MIT 3.60 | Lec 22a: Symmetry, Structure, Tensor Properties of Materials aWdqvyhzzIY 6494 MIT 3.60 | Lec 1b: Symmetry, Structure, Tensor Properties of Materials eCPASv7NaHk 6495 MIT 3.60 | Lec 26: Symmetry, Structure, Tensor Properties of Materials pEOSGrQkn44 6496 MIT 3.60 | Lec 5b: Symmetry, Structure, Tensor Properties of Materials eDCS197EzU8 6497 MIT 3.60 | Lec 13a: Symmetry, Structure, Tensor Properties of Materials O8q7AqZxtXQ 6498 MIT 3.60 | Lec 23a: Symmetry, Structure, Tensor Properties of Materials Bd4Q4Dl4brc 6499 MIT 3.60 | Lec 18b: Symmetry, Structure, Tensor Properties of Materials 4v94PCyrQqo 6500 MIT 3.60 | Lec 20b: Symmetry, Structure, Tensor Properties of Materials XYKEtZiierI 6501 MIT 3.60 | Lec 7a: Symmetry, Structure, Tensor Properties of Materials lPgglz6xeZU 6502 MIT 3.60 | Lec 16a: Symmetry, Structure, Tensor Properties of Materials hVqoXS5PyzY 6503 MIT 3.60 | Lec 20a: Symmetry, Structure, Tensor Properties of Materials GvtsFAxn-H8 6504 MIT 3.60 | Lec 24a: Symmetry, Structure, Tensor Properties of Materials JyIsB5D3ZCg 6505 MIT 3.60 | Lec 21a: Symmetry, Structure, Tensor Properties of Materials THTQT2aykaA 6506 MIT 3.60 | Lec 5a: Symmetry, Structure, Tensor Properties of Materials 2SYV_b3OelQ 6507 MIT 3.60 | Lec 7b: Symmetry, Structure, Tensor Properties of Materials w1qapsDFz2g 6508 MIT 3.60 | Lec 10b: Symmetry, Structure, Tensor Properties of Materials DKDcpkK3pM8 6509 MIT 3.60 | Lec 8a: Symmetry, Structure, Tensor Properties of Materials cUzZ-qu3xws 6510 MIT 3.60 | Lec 4a: Symmetry, Structure, Tensor Properties of Materials I0vEDYqXLeg 6511 MIT 3.60 | Lec 18a: Symmetry, Structure, Tensor Properties of Materials e-DMqNXtT9Q 6512 MIT 3.60 | Lec 2a: Symmetry, Structure, Tensor Properties of Materials IPTyKqZpbCM 6513 MIT 3.60 | Lec 13b: Symmetry, Structure, Tensor Properties of Materials V1i2bknbWfc 6514 MIT 3.60 | Lec 23b: Symmetry, Structure, Tensor Properties of Materials 7rm5sVtj-hs 6515 MIT 3.60 | Lec 12a: Symmetry, Structure, Tensor Properties of Materials JKUrC05a-4k 6516 MIT 3.60 | Lec 14a: Symmetry, Structure, Tensor Properties of Materials FEsKwINx--I 6517 MIT 3.60 | Lec 24b: Symmetry, Structure, Tensor Properties of Materials B4xIxr3fB7c 6518 MIT 3.60 | Lec 11a: Symmetry, Structure, Tensor Properties of Materials KJheruCbwHU 6519 MIT 3.60 | Lec 8b: Symmetry, Structure, Tensor Properties of Materials kYgBLGwuBpw 6520 MIT 3.60 | Lec 3b: Symmetry, Structure, Tensor Properties of Materials xRWGiK2SMrw 6521 MIT 3.60 | Lec 6b: Symmetry, Structure, Tensor Properties of Materials APv1uyLL6ok 6522 MIT 3.60 | Lec 3a: Symmetry, Structure, Tensor Properties of Materials Z7ftUJAx-1E 6523 Lec 12b: Symmetry, Structure, Tensor Properties of Materials RoxLGn5VN4g 6524 Lec 22b: Symmetry, Structure, Tensor Properties of Materials dGd519SL114 6525 MIT 3.60 | Lec 15a: Symmetry, Structure, Tensor Properties of Materials Vyf-lQjk0rY 6526 MIT 3.60 | Lec 15b: Symmetry, Structure, Tensor Properties of Materials 4CBKF4LT8l8 6527 MIT 3.60 | Lec 16b: Symmetry, Structure, Tensor Properties of Materials QyJkYF-L1Kg 6528 MIT 3.60 | Lec 21b: Symmetry, Structure, Tensor Properties of Materials HcQ7bdBGbEs 6529 Lec 3 | MIT 3.320 Atomistic Computer Modeling of Materials 3HXG1kxmYVs 6530 Lec 5 | MIT 3.320 Atomistic Computer Modeling of Materials gQ1YPzcHZqo 6531 Lec 13 | MIT 3.320 Atomistic Computer Modeling of Materials TqHS4tpujnw 6532 Lec 19 | MIT 3.320 Atomistic Computer Modeling of Materials _CTZDDFaE5A 6533 Lec 14 | MIT 3.320 Atomistic Computer Modeling of Materials -B96m5X2xCM 6534 Lec 7 | MIT 3.320 Atomistic Computer Modeling of Materials U5SKba2lCuw 6535 Lec 6 | MIT 3.320 Atomistic Computer Modeling of Materials egK3Cih11J4 6536 Lec 8 | MIT 3.320 Atomistic Computer Modeling of Materials zyId5iqW6Ig 6537 Lec 11 | MIT 3.320 Atomistic Computer Modeling of Materials ZsqPyPe7B5w 6538 Lec 18 | MIT 3.320 Atomistic Computer Modeling of Materials LInWiab7q6Q 6539 Lec 15 | MIT 3.320 Atomistic Computer Modeling of Materials K8qD73y8jag 6540 Lec 20 | MIT 3.320 Atomistic Computer Modeling of Materials WAc7fQ1qzAc 6541 Lec 9 | MIT 3.320 Atomistic Computer Modeling of Materials yYAHcATzuno 6542 Lec 22 | MIT 3.320 Atomistic Computer Modeling of Materials kHdqdTe7G44 6543 Lec 2 | MIT 3.320 Atomistic Computer Modeling of Materials 3FumIu7Qito 6544 Lec 17 | MIT 3.320 Atomistic Computer Modeling of Materials SbtqjZk80Qc 6545 Lec 23 | MIT 3.320 Atomistic Computer Modeling of Materials qOTTNo9iXJc 6546 Lec 25 | MIT 3.320 Atomistic Computer Modeling of Materials IwF_N2IDB48 6547 Lec 24 | MIT 3.091 Introduction to Solid State Chemistry IM5UZCtNKsc 6548 Lec 8 | MIT 3.091 Introduction to Solid State Chemistry Wb34zGvpC3E 6549 Lec 16 | MIT 3.091 Introduction to Solid State Chemistry WCKuWTVJMko 6550 Lec 19 | MIT 3.091 Introduction to Solid State Chemistry mcwwXuYkBGY 6551 Lec 34 | MIT 3.091 Introduction to Solid State Chemistry gVUpETtIFPE 6552 Lec 3 | MIT 3.091 Introduction to Solid State Chemistry HWRHTNzwELo 6553 Lec 13 | MIT 3.091 Introduction to Solid State Chemistry YCzxXdJlZ-M 6554 Lec 23 | MIT 3.091 Introduction to Solid State Chemistry AbbajZZZxVE 6555 Lec 9 | MIT 3.091 Introduction to Solid State Chemistry Qh-GfY-5voo 6556 Lec 29 | MIT 3.091 Introduction to Solid State Chemistry UbjZgxIjQfk 6557 Lec 5 | MIT 3.091 Introduction to Solid State Chemistry WF9ftfGEGYw 6558 Lec 18 | MIT 3.091 Introduction to Solid State Chemistry oyPesljk2Ak 6559 Lec 28 | MIT 3.091 Introduction to Solid State Chemistry i2ZyuWy_USg 6560 Lec 21 | MIT 3.091 Introduction to Solid State Chemistry JwDWi-hPjxc 6561 Lec 2 | MIT 3.091 Introduction to Solid State Chemistry cBxDQR2AEJY 6562 Lec 6 | MIT 3.091 Introduction to Solid State Chemistry y54bsRU-eJw 6563 Lec 12 | MIT 3.091 Introduction to Solid State Chemistry US_75CwRIUM 6564 Lec 27 | MIT 3.091 Introduction to Solid State Chemistry z_ouix9X1Zg 6565 Lec 10 | MIT 3.091 Introduction to Solid State Chemistry _n1OOWghLPc 6566 Lec 26 | MIT 3.091 Introduction to Solid State Chemistry Y-eEV6WqAwg 6567 Lec 15 | MIT 3.091 Introduction to Solid State Chemistry dXtEEME3ue8 6568 Lec 11 | MIT 3.091 Introduction to Solid State Chemistry zcfQ0tVTEbs 6569 Lec 20 | MIT 3.091 Introduction to Solid State Chemistry qw0pfuCu8q0 6570 Lec 4 | MIT 3.091 Introduction to Solid State Chemistry 0V-vgwcPjGQ 6571 Lec 30 | MIT 3.091 Introduction to Solid State Chemistry R90sohp6h44 6572 Lec 1 | MIT 3.091 Introduction to Solid State Chemistry WaCXmcVVduI 6573 Lec 7 | MIT 3.091 Introduction to Solid State Chemistry CdBoRHRRG1A 6574 Lec 17 | MIT 3.091 Introduction to Solid State Chemistry upzI8ZxORyI 6575 Lec 14 | MIT 3.091 Introduction to Solid State Chemistry UhtI6el1gPw 6576 Lec 25 | MIT 3.091 Introduction to Solid State Chemistry NEsVZenlRSU 6577 Lec 35 | MIT 3.091 Introduction to Solid State Chemistry TVuG75QH0kA 6578 Lec 22 | MIT 3.091 Introduction to Solid State Chemistry E58_lRznkDg 6579 Lec 33 | MIT 3.091 Introduction to Solid State Chemistry rzGmSWxhwM8 6580 Introduction | MIT 3.091 Introduction to Solid State Chemist 9USOlpRnJGc 6581 Session 4 | MIT 24.262 Feeling and Imagination in Art, Science, and Technology, Spring 2004 Ji9rC9nGAlQ 6582 Session 2 | MIT 24.262 Feeling and Imagination in Art, Science, and Technology, Spring 2004 elYbxYJlKNc 6583 Session 3 | MIT 24.262 Feeling and Imagination in Art, Science, and Technology, Spring 2004 CxhgdRCiPvg 6584 Session 1 | MIT 24.262 Feeling and Imagination in Art, Science, and Technology, Spring 2004 K6jxuRHGVCQ 6585 Session 3 | 24.261 Philosophy of Love in the Western World 4AL95TcwXQc 6586 Session 1 | 24.261 Philosophy of Love in the Western World VvQhR9o1RPw 6587 Session 2 | 24.261 Philosophy of Love in the Western World FF4LeK2D0co 6588 Session 4 | 24.261 Philosophy of Love in the Western World zvu9SoCyDec 6589 Session 1 | 21F.223 Listening, Speaking, and Pronunciation uiUZ_KkZr8U 6590 Session 2 | 21F.223 Listening, Speaking, and Pronunciation K7jYPfOSmqk 6591 Session 4 | 21F.223 Listening, Speaking, and Pronunciation VRMakiEeVJM 6592 Session 3 | 21F.223 Listening, Speaking, and Pronunciation oAFufZvbBb0 6593 Lec 12 | Special Topics in Supply Chain Management IXddoba3uQ4 6594 Lec 5 | Special Topics in Supply Chain Management wvLUlPCbc5s 6595 Lec 14 | Special Topics in Supply Chain Management oRK2jN3yqOI 6596 Lec 16 | Special Topics in Supply Chain Management djrhQK-dBx0 6597 Lec 2 | Special Topics in Supply Chain Management msiE_LqgUEY 6598 Lec 9 | Special Topics in Supply Chain Management pqdN-zGWkfY 6599 Lec 13 | Special Topics in Supply Chain Management IqmrNUoiy7g 6600 Lec 1 | Special Topics in Supply Chain Management b9X0osuciZI 6601 Lec 15 | Special Topics in Supply Chain Management lgq6S9ARuZI 6602 Lec 8 | Special Topics in Supply Chain Management -3tiysis4BM 6603 Lec 6 | Special Topics in Supply Chain Management uON1av7YiHw 6604 Lec 3 | Special Topics in Supply Chain Management KIkTU03nGxc 6605 Lec 4 | Special Topics in Supply Chain Management YS-o3X0tazU 6606 Lec 10 | Special Topics in Supply Chain Management hAMwuUM8frc 6607 Lec 7 | Special Topics in Supply Chain Management H7vyIn6WtOk 6608 Lec 11 | Special Topics in Supply Chain Management RR6DHXgT_5E 6609 Lec 8 | MIT 6.033 Computer System Engineering, Spring 2005 Tpnla9TdOyY 6610 Lec 15 | MIT 6.033 Computer System Engineering, Spring 2005 mBd1nntUgHc 6611 Lec 23 | MIT 6.033 Computer System Engineering, Spring 2005 uKYAcK2JXo0 6612 Lec 9 | MIT 6.033 Computer System Engineering, Spring 2005 BOR5n_nP1ps 6613 Lec 19 | MIT 6.033 Computer System Engineering, Spring 2005 vMJshx7SO6Y 6614 Lec 7 | MIT 6.033 Computer System Engineering, Spring 2005 BmjKER_e7-s 6615 Lec 24 | MIT 6.033 Computer System Engineering, Spring 2005 s_fjGI6PSI8 6616 Lec 17 | MIT 6.033 Computer System Engineering, Spring 2005 HxOA8HrVzPg 6617 Lec 13 | MIT 6.033 Computer System Engineering, Spring 2005 xEgcKKE9GmA 6618 Lec 22 | MIT 6.033 Computer System Engineering, Spring 2005 TXgH4G81iH0 6619 Lec 25 | MIT 6.033 Computer System Engineering, Spring 2005 9500J3lgu6U 6620 Lec 18 | MIT 6.033 Computer System Engineering, Spring 2005 zm2VP0kHl1M 6621 Lec 4 | MIT 6.033 Computer System Engineering, Spring 2005 Oo4iCE48xCc 6622 Lec 16 | MIT 6.033 Computer System Engineering, Spring 2005 TPeKtQykujI 6623 Lec 6 | MIT 6.033 Computer System Engineering, Spring 2005 kIErDkOepts 6624 Lec 11 | MIT 6.033 Computer System Engineering, Spring 2005 SCpzazvhXaU 6625 Lec 21 | MIT 6.033 Computer System Engineering, Spring 2005 Z2ENBilJWN0 6626 Lec 12 | MIT 6.033 Computer System Engineering, Spring 2005 PcPSF8kdgAQ 6627 Lec 14 | MIT 6.033 Computer System Engineering, Spring 2005 r0o9DJmvYNg 6628 Lec 10 | MIT 6.033 Computer System Engineering, Spring 2005 RmdAWsvcsZw 6629 Lec 5 | MIT 6.033 Computer System Engineering, Spring 2005 o-orfTyTXow 6630 Lec 20 | MIT 6.033 Computer System Engineering, Spring 2005 djthk58aT6o 6631 Lec 13 | MIT 6.013 Electromagnetics and Applications, Fall 2 S8FDEtLNjz4 6632 Lec 15 | MIT 6.013 Electromagnetics and Applications, Fall 2 PawR5Qa3rgs 6633 Lec 14 | MIT 6.013 Electromagnetics and Applications, Fall 2 3HrLJfL70Bg 6634 Lec 5 | MIT 6.013 Electromagnetics and Applications, Fall 20 VItWivq_3pc 6635 Lec 12 | MIT 6.013 Electromagnetics and Applications, Fall 2 xcwaVWCM9rI 6636 Lec 11 | MIT 6.013 Electromagnetics and Applications, Fall 2 gGNbt1xxP4A 6637 Lec 23 | MIT 6.013 Electromagnetics and Applications, Fall 2 goq1L1Pb424 6638 Lec 3 | MIT 6.013 Electromagnetics and Applications, Fall 20 lhtGJF7YFt8 6639 Lec 2 | MIT 6.013 Electromagnetics and Applications, Fall 20 _aMhpf6CK90 6640 Lec 22 | MIT 6.013 Electromagnetics and Applications, Fall 2 OxJg8VJ-dBA 6641 Lec 24 | MIT 6.013 Electromagnetics and Applications, Fall 2 algECMeQFrE 6642 Lec 9 | MIT 6.013 Electromagnetics and Applications, Fall 20 6QpLTfU9WPM 6643 Lec 19 | MIT 6.013 Electromagnetics and Applications, Fall 2 _0LtZx6epcg 6644 Lec 21 | MIT 6.013 Electromagnetics and Applications, Fall 2 2n36bvsyGxo 6645 Lec 18 | MIT 6.013 Electromagnetics and Applications, Fall 2 jOl7xci58e8 6646 Lec 6 | MIT 6.013 Electromagnetics and Applications, Fall 20 rxqKXc3qPOA 6647 Lec 16 | MIT 6.013 Electromagnetics and Applications, Fall 2 NQvXrxrqshk 6648 Lec 10 | MIT 6.013 Electromagnetics and Applications, Fall 2 rFGvvlsveOk 6649 Lec 8 | MIT 6.013 Electromagnetics and Applications, Fall 20 53ECnP6ign0 6650 Lec 4 | MIT 6.013 Electromagnetics and Applications, Fall 20 ICMbb5ZIY1I 6651 Lec 20 | MIT 6.013 Electromagnetics and Applications, Fall 2 bxv6d3dicIw 6652 Lec 17 | MIT 6.013 Electromagnetics and Applications, Fall 2 xx8fH-r3Luk 6653 Lec 1 | MIT 6.013 Electromagnetics and Applications, Fall 20 3_VDIRa-dZE 6654 Lec 7 | MIT 6.013 Electromagnetics and Applications, Fall 20 piFmQGn6VXE 6655 Lec 1 | MIT 5.74 Introductory Quantum Mechanics II RPF_t-C55Fw 6656 Lec 3 | MIT 5.74 Introductory Quantum Mechanics II wnyiasdTE0U 6657 Lec 4 | MIT 5.74 Introductory Quantum Mechanics II 9yfcqI-lEj0 6658 Lec 2 | MIT 5.74 Introductory Quantum Mechanics II Ftq9vbN-WGw 6659 Lec 4 | MIT 4.370 Interrogative Design Workshop, Fall 2005 5Rj2Ga9Y7oU 6660 Session 16 | MIT 4.370 Interrogative Design Workshop u6GHfkq8Aq4 6661 Lec 19 | MIT 7.013 Introductory Biology 6DOpp8zuYDE 6662 Session 7 | MIT 4.370 Interrogative Design Workshop CpYFD01gSWM 6663 Lec 29 | MIT 7.013 Introductory Biology HPIethXGwnE 6664 Session 20 | MIT 4.370 Interrogative Design Workshop Ef1jCXGM97w 6665 Lec 28 | MIT 7.013 Introductory Biology UWxND4VTz-g 6666 Lec 23 | MIT 7.013 Introductory Biology H17P1Fk308I 6667 Lec 1 | MIT 24.213 Philosophy of Film ma0d0o1K9Ng 6668 Lec 4 | MIT 24.213 Philosophy of Film nBiUUQIeT0g 6669 Lec 3 | MIT 24.213 Philosophy of Film X86s94ylybQ 6670 Lec 2 | MIT 24.213 Philosophy of Film AcrQzMc95ko 6671 Lec 2 | MIT 24.209 Philosophy In Film and Other Media gLQYS3HS1MQ 6672 Lec 4 | MIT 24.209 Philosophy In Film and Other Media LJ58Pn44enk 6673 Session 2 | MIT 24.264 Film as Visual and Literary Mythmaking, Fall 2005 GzVEP1VkwvA 6674 Lec 1 | MIT 24.209 Philosophy In Film and Other Media qypsPGqNF6Q 6675 Lec 3 | MIT 24.209 Philosophy In Film and Other Media X1npDVcp9wU 6676 Lec 3 | MIT 6.912 Introduction to Copyright Law tEpU7QiRiUk 6677 Lec 1 | MIT 21H.931 Seminar in Historical Methods qi1iullsY-o 6678 Lec 2 | MIT 21H.931 Seminar in Historical Methods BkaJCbyyLEA 6679 Lec 4 | MIT 6.912 Introduction to Copyright Law zqtx0gA5K2s 6680 Lec 1 | MIT 6.912 Introduction to Copyright Law g9UwqdMHjnM 6681 Lec 2 | MIT 6.912 Introduction to Copyright Law 3eqYo1LCGdw 6682 Lec 15 | MIT 6.451 Principles of Digital Communication II 47yJ7g6DzkA 6683 Lec 9 | MIT 6.451 Principles of Digital Communication II dy44BdqxRAo 6684 Lec 19 | MIT 6.451 Principles of Digital Communication II DNoNTre2Cf4 6685 Lec 22 | MIT 6.451 Principles of Digital Communication II eyqoHN4-4jg 6686 Lec 23 | MIT 6.451 Principles of Digital Communication II CxgU2Gtg5ro 6687 Lec 24 | MIT 6.451 Principles of Digital Communication II SV08nmxzdAU 6688 Lec 8 | MIT 6.451 Principles of Digital Communication II OJafRrE21WE 6689 Lec 12 | MIT 6.451 Principles of Digital Communication II 8HvTaOrTokc 6690 Lec 1 | MIT 6.451 Principles of Digital Communication II DyRLOmVRQDw 6691 Lec 17 | MIT 6.451 Principles of Digital Communication II HwGd1CPfIYk 6692 Lec 14 | MIT 6.451 Principles of Digital Communication II mnkTn0Y6GsU 6693 Lec 11 | MIT 6.451 Principles of Digital Communication II Nnj9lHePqKM 6694 Lec 10 | MIT 6.451 Principles of Digital Communication II YegKLHb9TOU 6695 Lec 16 | MIT 6.451 Principles of Digital Communication II q4LsDylKZcI 6696 Lec 6 | MIT 6.451 Principles of Digital Communication II YPAbQU7NUZQ 6697 Lec 5 | MIT 6.451 Principles of Digital Communication II MVpmgHSBSc0 6698 Lec 2 | MIT 6.451 Principles of Digital Communication II vXB3QmTg8YQ 6699 Lec 4 | MIT 6.451 Principles of Digital Communication II GQVlVhGKfHc 6700 Lec 18 | MIT 6.451 Principles of Digital Communication II 4HtXKIbiOvI 6701 Lec 21 | MIT 6.451 Principles of Digital Communication II zWZCMrKIikw 6702 Lec 3 | MIT 6.451 Principles of Digital Communication II d_Mg_JnnevU 6703 Lec 7 | MIT 6.451 Principles of Digital Communication II KalMFMv3_IM 6704 Lec 25 | MIT 6.451 Principles of Digital Communication II 2ludHpG_Q60 6705 Lec 13 | MIT 6.451 Principles of Digital Communication II k-bpyDgBxAo 6706 Lec 1 | MIT 6.035 Computer Language Engineering, Fall 2005 Lkq-Y0VBdTw 6707 Lec 8 | MIT 6.035 Computer Language Engineering, Fall 2005 GmSXXUu5qzQ 6708 Lec 14 | MIT 6.035 Computer Language Engineering, Fall 2005 E-iL1Q4ys3k 6709 Rec 1 | MIT 6.035 Computer Language Engineering, Fall 2005 H94lCCyg7x8 6710 Lec 9 | MIT 6.035 Computer Language Engineering, Fall 2005 v9Xmajiraoc 6711 Lec 17 | MIT 6.035 Computer Language Engineering, Fall 2005 SZOJogbFEvc 6712 Lec 15 | MIT 6.035 Computer Language Engineering, Fall 2005 O3znBwtCRb4 6713 Lec 16 | MIT 6.035 Computer Language Engineering, Fall 2005 VhvLk6AY9M0 6714 Lec 5 | MIT CMS.930 Media, Education and the Marketplace qM-X1L3Sjsc 6715 Lec 3 | MIT CMS.930 Media, Education and the Marketplace xKL3J5iPnwE 6716 Lec 4 | MIT CMS.930 Media, Education and the Marketplace lE3V1pFB1D4 6717 Lec 11 | MIT CMS.930 Media, Education and the Marketplace 9Mw24zosTyo 6718 Lec 7 | MIT CMS.930 Media, Education and the Marketplace p9lXOe8YyaQ 6719 Lec 9 | MIT CMS.930 Media, Education and the Marketplace s7bkHu27P5o 6720 Lec 1 | MIT CMS.930 Media, Education and the Marketplace AA7_HBp566w 6721 Lec 14 | MIT CMS.930 Media, Education and the Marketplace 3DDkPxll_qQ 6722 Lec 2 | MIT CMS.930 Media, Education and the Marketplace SDKIsplqGmY 6723 Lec 6 | MIT CMS.930 Media, Education and the Marketplace mL40Mi5euyA 6724 Lec 8 | MIT CMS.930 Media, Education and the Marketplace qpdtzW8py0c 6725 Lec 10 | MIT CMS.930 Media, Education and the Marketplace llZi_4npNeo 6726 Lec 12 | MIT CMS.930 Media, Education and the Marketplace SAgWL1G5Bcw 6727 Lec 13 | MIT CMS.930 Media, Education and the Marketplace 6fzBJ8nuuzk 6728 Lec 10 | MIT 5.301 Chemistry Laboratory Techniques, IAP 2004 7c0XL-ZQn5I 6729 Lec 6 | MIT 5.301 Chemistry Laboratory Techniques, IAP 2004 Q47hTa1KvN0 6730 Lec 9 | MIT 5.301 Chemistry Laboratory Techniques, IAP 2004 ciWpS6SetdY 6731 Lec 5 | MIT 5.301 Chemistry Laboratory Techniques, IAP 2004 EUn2skAAjHk 6732 Lec 3 | MIT 5.301 Chemistry Laboratory Techniques, IAP 2004 qK6DgAM-q7U 6733 Lec 34 | MIT 5.112 Principles of Chemical Science, Fall 2005 hG8KdheMUeo 6734 Lec 32 | MIT 5.112 Principles of Chemical Science, Fall 2005 _YpkKYmQBwY 6735 Lec 24 | MIT 5.112 Principles of Chemical Science, Fall 2005 HT4sxODPR2Q 6736 Lec 5 | MIT 5.112 Principles of Chemical Science, Fall 2005 NVTHQwQ9IqA 6737 Lec 29 | MIT 5.112 Principles of Chemical Science, Fall 2005 tbWuyysnj9U 6738 Lec 19 | MIT 5.112 Principles of Chemical Science, Fall 2005 UGoGgkHYS10 6739 Lec 7 | MIT 5.112 Principles of Chemical Science, Fall 2005 MRJUxK-hhYw 6740 Lec 12 | MIT 5.112 Principles of Chemical Science, Fall 2005 oLbTUpxhE24 6741 Lec 6 | MIT 5.112 Principles of Chemical Science, Fall 2005 M8QoJojEklw 6742 Lec 17 | MIT 5.112 Principles of Chemical Science, Fall 2005 mJAf9OYfLV8 6743 Lec 3 | MIT 5.112 Principles of Chemical Science, Fall 2005 sNdTPKvsYXg 6744 Lec 16 | MIT 5.112 Principles of Chemical Science, Fall 2005 qm_hVsoM4OY 6745 Lec 18 | MIT 5.112 Principles of Chemical Science, Fall 2005 UesUBkX9HIQ 6746 Lec 27 | MIT 5.112 Principles of Chemical Science, Fall 2005 JrL2jlkoRUY 6747 Lec 26 | MIT 5.112 Principles of Chemical Science, Fall 2005 -uEwMV9DHZo 6748 Lec 20 | MIT 5.112 Principles of Chemical Science, Fall 2005 LRFbAo-RIIU 6749 Lec 23 | MIT 5.112 Principles of Chemical Science, Fall 2005 hjFnG8m6mCc 6750 Lec 30 | MIT 5.112 Principles of Chemical Science, Fall 2005 ZRxwArdDnac 6751 Lec 22 | MIT 5.112 Principles of Chemical Science, Fall 2005 u95Cxl2IeNc 6752 Lec 28 | MIT 5.112 Principles of Chemical Science, Fall 2005 CVRmu_aBSho 6753 Lec 2 | MIT 5.112 Principles of Chemical Science, Fall 2005 9Cl8mj5VIHA 6754 Lec 8 | MIT 5.112 Principles of Chemical Science, Fall 2005 UqQRXRtvM9o 6755 Lec 13 | MIT 5.112 Principles of Chemical Science, Fall 2005 gb60YssaSmI 6756 Lec 31 | MIT 5.112 Principles of Chemical Science, Fall 2005 m9AJwUCAWGQ 6757 Lec 4 | MIT 5.112 Principles of Chemical Science, Fall 2005 yi6a_COcfxw 6758 Lec 33 | MIT 5.112 Principles of Chemical Science, Fall 2005 OpmQh1ChWdE 6759 Lec 15 | MIT 5.112 Principles of Chemical Science, Fall 2005 dxR06Mi8ExI 6760 Lec 1 | MIT 5.112 Principles of Chemical Science, Fall 2005 dAgwg_8RyEU 6761 Lec 14 | MIT 5.112 Principles of Chemical Science, Fall 2005 4xRS6bdFsVM 6762 Lec 21 | MIT 5.112 Principles of Chemical Science, Fall 2005 lawooSesSfM 6763 Lec 10 | MIT 5.112 Principles of Chemical Science, Fall 2005 QyishgPCBfg 6764 Lec 11 | MIT 5.112 Principles of Chemical Science, Fall 2005 CgzHOo9NaOY 6765 Lec 36 | MIT 5.112 Principles of Chemical Science, Fall 2005 KUVB9S0QX-I 6766 Lec 9 | MIT 5.112 Principles of Chemical Science, Fall 2005 r8-cr6wrOgE 6767 Lec 25 | MIT 5.112 Principles of Chemical Science, Fall 2005 mJhgkUWLtX8 6768 Lec 9 | MIT 7.014 Introductory Biology, Spring 2005 LBR4pEC7kwU 6769 Lec 31 | MIT 7.014 Introductory Biology, Spring 2005 EO9SMD6fIsI 6770 Lec 25 | MIT 7.014 Introductory Biology, Spring 2005 BhS5s1T1as8 6771 Lec 13 | MIT 7.014 Introductory Biology, Spring 2005 fQKMD2iFe5w 6772 Lec 23 | MIT 7.014 Introductory Biology, Spring 2005 ONYokXoy04Q 6773 Lec 32 | MIT 7.014 Introductory Biology, Spring 2005 40Sum5KfG1Q 6774 Lec 12 | MIT 7.014 Introductory Biology, Spring 2005 zIXGgyOwtUk 6775 Lec 20 | MIT 7.014 Introductory Biology, Spring 2005 6BPDK1b3jDg 6776 Lec 4 | MIT 7.014 Introductory Biology, Spring 2005 RJf9jRf-Ekw 6777 Lec 2 | MIT 7.014 Introductory Biology, Spring 2005 3zJI3dYB7gc 6778 Lec 3 | MIT 7.014 Introductory Biology, Spring 2005 5_QWoGFUPaI 6779 Lec 34 | MIT 7.014 Introductory Biology, Spring 2005 rKquepVheyM 6780 Lec 30 | MIT 7.014 Introductory Biology, Spring 2005 7aNYj3zyVkc 6781 Lec 5 | MIT 7.014 Introductory Biology, Spring 2005 vES9nISxtjk 6782 Lec 14 | MIT 7.014 Introductory Biology, Spring 2005 Y8eEMYqkwz0 6783 Lec 28 | MIT 7.014 Introductory Biology, Spring 2005 Ncszdp4YQDY 6784 Lec 10 | MIT 7.014 Introductory Biology, Spring 2005 R3DI6W9iKtU 6785 Lec 7 | MIT 7.014 Introductory Biology, Spring 2005 gaHQ_1Sp5_s 6786 Lec 16 | MIT 7.014 Introductory Biology, Spring 2005 Uf7qNWklQkE 6787 Lec 11 | MIT 7.014 Introductory Biology, Spring 2005 5W4EnYzNRdA 6788 Lec 26 | MIT 7.014 Introductory Biology, Spring 2005 7ZlzvS7YoSM 6789 Lec 8 | MIT 7.014 Introductory Biology, Spring 2005 Yr-cZg9eqp4 6790 Lec 29 | MIT 7.014 Introductory Biology, Spring 2005 kAN_eTW_ig0 6791 Lec 27 | MIT 7.014 Introductory Biology, Spring 2005 g6VEnimixRk 6792 Lec 22 | MIT 7.014 Introductory Biology, Spring 2005 hWdAt9SzP0I 6793 Lec 18 | MIT 7.014 Introductory Biology, Spring 2005 1KcxRSsHrcI 6794 Lec 10 (repeat) | MIT 7.014 Introductory Biology, Spring 2005 4owydSnRHuE 6795 Lec 19 | MIT 7.014 Introductory Biology, Spring 2005 uQRTFmC5_GA 6796 Lec 15 | MIT 7.014 Introductory Biology, Spring 2005 GAArnLLlFtQ 6797 Lec 33 | MIT 7.014 Introductory Biology, Spring 2005 SGHx6jKvxr8 6798 Lec 6 | MIT 7.014 Introductory Biology, Spring 2005 5WqgNOSoD_M 6799 Lec 17 | MIT 7.014 Introductory Biology, Spring 2005 lm8ywGl9AIQ 6800 Lec 1 | MIT 7.014 Introductory Biology, Spring 2005 l5x9qAVUK7s 6801 Lec 24 | MIT 7.014 Introductory Biology, Spring 2005 g482Gi6o8Sg 6802 Faculty Interview | MIT Introduction to Bioengineering, Spri Nq6Fs0RkW9A 6803 Lec 3 | MIT Introduction to Bioengineering, Spring 2006 GfoM-s9ZKrI 6804 Lec 1 | MIT Introduction to Bioengineering, Spring 2006 UxdUvyBtfXY 6805 Lec 4 | MIT Introduction to Bioengineering, Spring 2006 gGQDQ0BSge4 6806 Lec 2 | MIT Introduction to Bioengineering, Spring 2006 lsqFfbpXbSQ 6807 Faculty Interview | MIT Introduction to Bioengineering, Spri -OQn43ZA2EM 6808 Lec 11 | MIT 4.125 Architecture Studio: Building in Landscap 82JCqqjnAgI 6809 Faculty Interview | MIT Introduction to Bioengineering, Spri kgaJf-mQSAE 6810 Faculty Interview | MIT Introduction to Bioengineering, Spri Z0d4z8FdmR0 6811 Faculty Interview | MIT Introduction to Bioengineering, Spri W_rm0DcTeqo 6812 Faculty Interview | MIT Introduction to Bioengineering, Spri whdOtrwi0oM 6813 Faculty Interview | MIT Introduction to Bioengineering, Spri TNDIZI1v4as 6814 Faculty Interview | MIT Introduction to Bioengineering GSFrP7BlOc8 6815 Faculty Interview | MIT Introduction to Bioengineering, Spri foFqF_OUq50 6816 Faculty Interview | MIT Introduction to Bioengineering, Spri EMy4v-oBTVk 6817 Faculty Interview | MIT Introduction to Bioengineering, Spri WyrBTEVku1I 6818 Faculty Interview | MIT Introduction to Bioengineering, Spri 2Gk4Vg2tuRQ 6819 Lec 8 | MIT 4.125 Architecture Studio: Building in Landscape P_av1O1HTk8 6820 Lec 9 | MIT 4.125 Architecture Studio: Building in Landscape RYUokJgCnYw 6821 Lec 5 | MIT 4.125 Architecture Studio: Building in Landscape 3hHesQcAYXI 6822 Lec 7 | MIT 4.125 Architecture Studio: Building in Landscape Dl94XBHHal8 6823 Lec 2 | MIT 4.125 Architecture Studio: Building in Landscape 7Cvytz8rLLo 6824 Lec 6 | MIT 4.125 Architecture Studio: Building in Landscape jVKmUpaE5Bw 6825 Lec 12 | MIT 4.125 Architecture Studio: Building in Landscap 44lqcpQcNzQ 6826 Lec 10 | MIT 4.125 Architecture Studio: Building in Landscap LodNVAJ1zE0 6827 Lec 4 | MIT 4.125 Architecture Studio: Building in Landscape aewmVftXm1Q 6828 Lec 3 | MIT 4.125 Architecture Studio: Building in Landscape WguhC64iAXI 6829 Lec 1 | MIT 4.125 Architecture Studio: Building in Landscape XsSQVdl0_EA 6830 Shuttle Operations Video | MIT 16.885J Aircraft Systems Engineering, Fall 2005 uP2Acm9uEGk 6831 Lec 22 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 AwjT1gJSsco 6832 Lec 13 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 xqwHRjUfECk 6833 Team 5: Post-Flight Interview | MIT Unified Engineering, Fall 2005 J5mwRqyxPIA 6834 Lec 11 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 Y8CXbAesjaU 6835 Sample Lecture P9 | MIT Unified Engineering, Fall 2005 qcpyFE3u3hw 6836 Lec 8 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 YxhoHe3BZ-g 6837 Lec 21 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 Fo8v7juSgRw 6838 Lec 17 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 nTDuTIvSYaI 6839 Team Firebolt: Flight Attempt | MIT Unified Engineering, Fall 2005 U9XakUrkwgw 6840 Team Firebolt: Post-Flight Interview | MIT Unified Engineering, Fall 2005 k2jN_26m8LM 6841 Lec 5 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 2QRfkG7jOfY 6842 Lec 7 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 bOAyzURugaw 6843 Lec 4 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 IHVf3ukiIiA 6844 Lec 19 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 0cKEQYulCD0 6845 Team Double-Stuft Reduced-Fat Oreos: Flight Attempt 1 | MIT Unified Engineering, Fall 2005 OksC02Xqe7Q 6846 Lec 16 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 XWjSXlxpDfU 6847 Lec 12 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 rV5eSoBqrsY 6848 Lec 14 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 iiYhQtGpRhc 6849 Lec 1 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 xJ2H06sseLM 6850 Lec 2 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 mgXDQtF0wl0 6851 Team 9: Post-Flight Interview | MIT Unified Engineering, Fall 2005 FB0pyYTs2mw 6852 Lec 18 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 1IJPugWssVs 6853 Lec 9 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 AODj-jM3-XI 6854 Lec 20 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 MfocEPhmyV0 6855 Team Double-Stuft Reduced-Fat Oreos: Flight Attempt 2 | MIT Unified Engineering, Fall 2005 KFOv1WtlAow 6856 Lec 15 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 cDMbBjH8ZSs 6857 Lec 3 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 XV7YjOer7HE 6858 Two Guys, Two Girls and an Airplane: Pre-Flight Interview | MIT Unified Engineering, Fall 2005 TEQ6va1goOY 6859 Team Double-Stuft Reduced-Fat Oreos: Post-Flight Interview | MIT Unified Engineering, Fall 2005 tf7t7YIQcMc 6860 Team 9: Flight Attempt | MIT Unified Engineering, Fall 2005 gxFsKhZcTW0 6861 Team 5: Flight Attempt 1 | MIT Unified Engineering, Fall 2005 bFi8yxWZhR4 6862 Team 15: Flight Attempt | MIT Unified Engineering, Fall 2005 AIucNcAQE3A 6863 Team Firebolt: Pre-Flight Interview | MIT Unified Engineering, Fall 2005 jlG7NyE06OQ 6864 Two Guys, Two Girls and an Airplane: Flight Attempt 1 | MIT Unified Engineering, Fall 2005 YRtRMhsXRdM 6865 Team 9: Pre-Flight Interview | MIT Unified Engineering, Fall 2005 bqurk7IEypQ 6866 Two Guys, Two Girls and an Airplane: Flight Attempt 2 | MIT Unified Engineering, Fall 2005 0xjqZ8sutzA 6867 Team 5: Pre-Flight Interview | MIT Unified Engineering, Fall 2005 CFowrRdLXuM 6868 Two Guys, Two Girls and an Airplane: Post-Flight Interview | MIT Unified Engineering, Fall 2005 bkJ7zVcBpaQ 6869 Team 5: Flight Attempt 2 | MIT Unified Engineering, Fall 2005 aYB5gCiissI 6870 Team 15: Post-Flight Interview | MIT Unified Engineering, Fall 2005 1_BTHGt6lwc 6871 Team 15: Pre-Flight Interview | MIT Unified Engineering, Fall 2005 uow6v1EuybE 6872 Lec 6 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 hzW2ZBtzrUE 6873 Lec 10 | MIT 16.885J Aircraft Systems Engineering, Fall 2005 odtKI7tEi5c 6874 Lec 10 | MIT 7.012 Introduction to Biology, Fall 2004 g2Iom3LgrzY 6875 Lec 17 | MIT 5.111 Principles of Chemical Science, Fall 2005 gFikVQt2UcE 6876 Lec 19 | MIT 5.111 Principles of Chemical Science, Fall 2005 qObvbkcU838 6877 Lec 16 | MIT 7.012 Introduction to Biology, Fall 2004 00LNy0Q_i6c 6878 Lec 13 | MIT 7.012 Introduction to Biology, Fall 2004 blBcCjIY7Sg 6879 Lec 14 | MIT 7.012 Introduction to Biology, Fall 2004 _TdJBLu6hPc 6880 Lec 15 | MIT 7.012 Introduction to Biology, Fall 2004 GbVdTqIvIPw 6881 Lec 5 | MIT 5.111 Principles of Chemical Science, Fall 2005 Ky_uVNs7__o 6882 Lec 36 | MIT 5.111 Principles of Chemical Science, Fall 2005 fdBTs6D2jpo 6883 Lec 29 | MIT 5.111 Principles of Chemical Science, Fall 2005 X_HvnH9Mlwc 6884 Lec 22 | MIT 5.111 Principles of Chemical Science, Fall 2005 p3uiUKiuyT8 6885 Lec 11 | MIT 5.111 Principles of Chemical Science, Fall 2005 Y9EzvtFM5gU 6886 Lec 32 | MIT 5.111 Principles of Chemical Science, Fall 2005 742FwwA0qKI 6887 Lec 15 | MIT 5.111 Principles of Chemical Science, Fall 2005 91fCFo_LbwM 6888 Lec 4 | MIT 5.111 Principles of Chemical Science, Fall 2005 LmiY4R6C2mM 6889 Lec 30 | MIT 5.111 Principles of Chemical Science, Fall 2005 -xJjrPmguxI 6890 Lec 25 | MIT 5.111 Principles of Chemical Science, Fall 2005 aAk1hYy7VuY 6891 Lec 35 | MIT 5.111 Principles of Chemical Science, Fall 2005 HeM4EzQoGOQ 6892 Lec 26 | MIT 5.111 Principles of Chemical Science, Fall 2005 wqNW2Nd8Xx4 6893 Lec 27 | MIT 5.111 Principles of Chemical Science, Fall 2005 7ciUw92IGs4 6894 Lec 18 | MIT 5.111 Principles of Chemical Science, Fall 2005 2x3F08_8B80 6895 Lec 1 | MIT 5.111 Principles of Chemical Science, Fall 2005 D-4cAzSmQUU 6896 Lec 34 | MIT 5.111 Principles of Chemical Science, Fall 2005 F8u6CDGr5wY 6897 Lec 21 | MIT 5.111 Principles of Chemical Science, Fall 2005 fz5sa6lFiS0 6898 Lec 7 | MIT 5.111 Principles of Chemical Science, Fall 2005 wcj5WV1BV28 6899 Lec 13 | MIT 5.111 Principles of Chemical Science, Fall 2005 44mSNs6kl8c 6900 Lec 24 | MIT 5.111 Principles of Chemical Science, Fall 2005 fdTzju3GTnk 6901 Lec 33 | MIT 5.111 Principles of Chemical Science, Fall 2005 E7W6x1Py0Ro 6902 Lec 31 | MIT 5.111 Principles of Chemical Science, Fall 2005 DAftayGT9P4 6903 Lec 10 | MIT 5.111 Principles of Chemical Science, Fall 2005 jNonxisBNlM 6904 Lec 6 | MIT 5.111 Principles of Chemical Science, Fall 2005 rQdOSLjEWcA 6905 Lec 16 | MIT 5.111 Principles of Chemical Science, Fall 2005 x0y7z-50ICc 6906 Lec 9 | MIT 5.111 Principles of Chemical Science, Fall 2005 G5q1_zhG86g 6907 Lec 8 | MIT 5.111 Principles of Chemical Science, Fall 2005 g01r2YRH9ok 6908 Lec 28 | MIT 5.111 Principles of Chemical Science, Fall 2005 vROqnyO-olU 6909 Lec 23 | MIT 5.111 Principles of Chemical Science, Fall 2005 p9mFf79aWg8 6910 Lec 20 | MIT 5.111 Principles of Chemical Science, Fall 2005 f-uEn1nZmB4 6911 Lec 12 | MIT 5.111 Principles of Chemical Science, Fall 2005 RUjePzTQfQg 6912 Lec 14 | MIT 5.111 Principles of Chemical Science, Fall 2005 ZzMdrYTCPO4 6913 Lec 3 | MIT 5.111 Principles of Chemical Science, Fall 2005 ZYMBrwSahMY 6914 Lec 2 | MIT 5.111 Principles of Chemical Science, Fall 2005 rWG1hLvoP-U 6915 Lec 28 | MIT 7.012 Introduction to Biology, Fall 2004 E2sRItjdLGI 6916 Lec 33 | MIT 7.012 Introduction to Biology, Fall 2004 R6AtInDjsrM 6917 Lec 21 | MIT 7.012 Introduction to Biology, Fall 2004 os0qdddXrMs 6918 Lec 23 | MIT 7.012 Introduction to Biology, Fall 2004 BAldLXDPWZM 6919 Lec 26 | MIT 7.012 Introduction to Biology, Fall 2004 Rqs_zVh5sr8 6920 Lec 17 | MIT 7.012 Introduction to Biology, Fall 2004 pTh8f0mWu1k 6921 Lec 30 | MIT 7.012 Introduction to Biology, Fall 2004 rxiAQe0t-ZU 6922 Lec 27 | MIT 7.012 Introduction to Biology, Fall 2004 T5d5PvPjUlU 6923 Lec 18 | MIT 7.012 Introduction to Biology, Fall 2004 ztgHcRV1zI0 6924 Lec 32 | MIT 7.012 Introduction to Biology, Fall 2004 xN-sQdVaDr4 6925 Lec 22 | MIT 7.012 Introduction to Biology, Fall 2004 Eqom7VcaEKI 6926 Lec 34 | MIT 7.012 Introduction to Biology, Fall 2004 N2jFzZA1e14 6927 Lec 29 | MIT 7.012 Introduction to Biology, Fall 2004 zrBZjcsQ_BQ 6928 Lec 20 | MIT 7.012 Introduction to Biology, Fall 2004 bO0WsF4anko 6929 Lec 24 | MIT 7.012 Introduction to Biology, Fall 2004 dENgjMVCHaA 6930 Lec 19 | MIT 7.012 Introduction to Biology, Fall 2004 5WhcMXP5yEU 6931 Lec 25 | MIT 7.012 Introduction to Biology, Fall 2004 VTWmccDMlDw 6932 Lec 31 | MIT 7.012 Introduction to Biology, Fall 2004 xGeBSiXoSoA 6933 Lec 35 | MIT 7.012 Introduction to Biology, Fall 2004 9iaoypSrIT0 6934 Lec 6 | MIT 7.012 Introduction to Biology, Fall 2004 ARjSihLe1K8 6935 Lec 12 | MIT 7.012 Introduction to Biology, Fall 2004 t5Y89b-3Zvc 6936 Lec 4 | MIT 7.012 Introduction to Biology, Fall 2004 UT6h56ii9s4 6937 Lec 8 | MIT 7.012 Introduction to Biology, Fall 2004 _CovlKXmuWo 6938 Lec 2 | MIT 7.012 Introduction to Biology, Fall 2004 PVv4ST8NZaA 6939 Lec 9 | MIT 7.012 Introduction to Biology, Fall 2004 QOdq7d34f7U 6940 Lec 11 | MIT 7.012 Introduction to Biology, Fall 2004 9WwJr2yrv2I 6941 Lec 7 | MIT 7.012 Introduction to Biology, Fall 2004 V3XHn35BLfo 6942 Lec 5 | MIT 7.012 Introduction to Biology, Fall 2004 _m4Gvu90Ydw 6943 Lec 1 | MIT 7.012 Introduction to Biology, Fall 2004 e3FfmXtkppM 6944 Lec 27 | MIT 18.03 Differential Equations, Spring 2006 heBvViSi9xQ 6945 Lec 25 | MIT 18.03 Differential Equations, Spring 2006 zreI4HllD80 6946 Lec 29 | MIT 18.03 Differential Equations, Spring 2006 UJG0f0BSX14 6947 Lec 31 | MIT 18.03 Differential Equations, Spring 2006 3ejfkMHr_DE 6948 Lec 21 | MIT 18.03 Differential Equations, Spring 2006 _YVcjNmjHik 6949 Lec 22 | MIT 18.03 Differential Equations, Spring 2006 MCrDzhpu3-s 6950 Lec 24 | MIT 18.03 Differential Equations, Spring 2006 sZ2qulI6GEk 6951 Lec 19 | MIT 18.03 Differential Equations, Spring 2006 qZHseRxAWZ8 6952 Lec 20 | MIT 18.03 Differential Equations, Spring 2006 uNOyxQwIV8o 6953 Lec 30 | MIT 18.03 Differential Equations, Spring 2006 kRR9EVzr4lc 6954 Lec 33 | MIT 18.03 Differential Equations, Spring 2006 z-meBrqcy_I 6955 Lec 32 | MIT 18.03 Differential Equations, Spring 2006 hEtWqTPPXuc 6956 Lec 26 | MIT 18.03 Differential Equations, Spring 2006 2SuTN8rpe4I 6957 Lec 28 | MIT 18.03 Differential Equations, Spring 2006 yD0_EQLxHcw 6958 Lec 17 | MIT 18.03 Differential Equations, Spring 2006 peYvLk_HZdw 6959 Lec 23 | MIT 18.03 Differential Equations, Spring 2006 rZ3-nFV6l8w 6960 Lec 11 | MIT 18.03 Differential Equations, Spring 2006 xWa5_OXI6VM 6961 Lec 16 | MIT 18.03 Differential Equations, Spring 2006 vP-oRQqmeg4 6962 Lec 9 | MIT 18.03 Differential Equations, Spring 2006 LbKKzMag5Rc 6963 Lec 2 | MIT 18.03 Differential Equations, Spring 2006 eyNm7XGJr4s 6964 Lec 12 | MIT 18.03 Differential Equations, Spring 2006 MdzfsfBNJIw 6965 Lec 8 | MIT 18.03 Differential Equations, Spring 2006 Y9_zrupnz0Q 6966 Lec 14 | MIT 18.03 Differential Equations, Spring 2006 EWWw0jryj1A 6967 Lec 15 | MIT 18.03 Differential Equations, Spring 2006 YQ7HEE8-OfA 6968 Lec 10 | MIT 18.03 Differential Equations, Spring 2006 tVzaX9u6YAE 6969 Lec 3 | MIT 18.03 Differential Equations, Spring 2006 WBJ_iXudb-s 6970 Lec 4 | MIT 18.03 Differential Equations, Spring 2006 SioXozu-Loo 6971 Lec 7 | MIT 18.03 Differential Equations, Spring 2006 EQJBp6Ym-6A 6972 Lec 6 | MIT 18.03 Differential Equations, Spring 2006 9KbpbBMThTE 6973 Lec 13 | MIT 18.03 Differential Equations, Spring 2006 te6Mplq3DCU 6974 Lec 5 | MIT 18.03 Differential Equations, Spring 2006 XDhJ8lVGbl8 6975 Lec 1 | MIT 18.03 Differential Equations, Spring 2006 v6vqWasIHaw 6976 Lec 5 | MIT 6.002 Circuits and Electronics, Spring 2007 OGtElTMJidE 6977 Lec 6 | MIT 6.002 Circuits and Electronics, Spring 2007 ke3SL_R92ys 6978 Lec 21 | MIT 6.002 Circuits and Electronics, Spring 2007 Km9YIdkc2Oo 6979 Lec 17 | MIT 6.002 Circuits and Electronics, Spring 2007 AfQxyVuLeCs 6980 Lec 1 | MIT 6.002 Circuits and Electronics, Spring 2007 ypX20WnHNQw 6981 Lec 15 | MIT 6.002 Circuits and Electronics, Spring 2007 V0z_f7qxLcY 6982 Lec 19 | MIT 6.002 Circuits and Electronics, Spring 2007 JqvKtMNz3RQ 6983 Lec 7 | MIT 6.002 Circuits and Electronics, Spring 2007 Nijya-QJ45Y 6984 Lec 9 | MIT 6.002 Circuits and Electronics, Spring 2007 4TCnYYpZxEc 6985 Lec 4 | MIT 6.002 Circuits and Electronics, Spring 2007 dyxcCoUgETU 6986 Lec 25 | MIT 6.002 Circuits and Electronics, Spring 2007 TXJIhDHtHSI 6987 Lec 13 | MIT 6.002 Circuits and Electronics, Spring 2007 RsJ1eg7XNVs 6988 Lec 3 | MIT 6.002 Circuits and Electronics, Spring 2007 2vHGYdepKLw 6989 Lec 2 | MIT 6.002 Circuits and Electronics, Spring 2007 wNuBD4PYWvs 6990 Lec 22 | MIT 6.002 Circuits and Electronics, Spring 2007 3GdMaDzIUeQ 6991 Lec 16 | MIT 6.002 Circuits and Electronics, Spring 2007 bEJ0-8pANA4 6992 Lec 8 | MIT 6.002 Circuits and Electronics, Spring 2007 WT-qzgaKeGI 6993 Lec 18 | MIT 6.002 Circuits and Electronics, Spring 2007 COdQmA9g9S8 6994 Lec 12 | MIT 6.002 Circuits and Electronics, Spring 2007 R4KxlqsuZ0A 6995 Lec 11 | MIT 6.002 Circuits and Electronics, Spring 2007 2SwT6JnfCq8 6996 Lec 20 | MIT 6.002 Circuits and Electronics, Spring 2007 jURSAKBlIZA 6997 Lec 9B | MIT 6.002 Circuits and Electronics, Spring 2007 bX8i2yECWaU 6998 Lec 14 | MIT 6.002 Circuits and Electronics, Spring 2007 JB2HgohNHYQ 6999 Lec 23 | MIT 6.002 Circuits and Electronics, Spring 2007 -gRXU-O1FY4 7000 Lec 15b | MIT 6.002 Circuits and Electronics, Spring 2007 7icUBzjlik4 7001 MIT Milestone Celebration | The Future of OCW and Education EcE2ufqtzyk 7002 MIT Milestone Celebration | Keynote Address zxg5hZ7WdjU 7003 MIT Milestone Celebration | Acknowledgements HhDuGRwb2_c 7004 MIT Milestone Celebration | Welcome tbQ-FeoEvTI 7005 MIT OpenCourseWare 1800 Event Video qMNWtUs7KoU 7006 MIT OpenCourseWare: Highlights for High School launch video