Part 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-clFL503NPyY.mp4218.29KB

Part 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-ztkKTrMZHXg.mp4284.83KB

Part 02-Module 01-Lesson 03_Probability/14. Two Flips 2-pT0FXiH_5nI.mp4312.59KB

Part 02-Module 01-Lesson 08_Probability Distributions/10. Landing Probability-W9TOvnLH4fg.mp4347.03KB

Part 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-4qW7a5E74No.mp4390.91KB

Part 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-PfEYA6z-19w.mp4423.73KB

Part 06-Module 01-Lesson 03_The Search Problem/24. A Search Solution-_cPSOQ-sC2k.mp4434.84KB

Part 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-goEMc0w58xM.mp4473.3KB

Part 02-Module 01-Lesson 08_Probability Distributions/13. Range Probability-zHAl87ITDik.mp4476.74KB

Part 02-Module 01-Lesson 06_Bayes' Rule/16. Cancer Probabilities-7ZLe_JP5wRY.mp4479.6KB

Part 02-Module 01-Lesson 06_Bayes' Rule/32. Robot Sensing 6-Se-ddM2Wdac.mp4484.71KB

Part 02-Module 01-Lesson 06_Bayes' Rule/31. Robot Sensing 5-tIrqdYTT_9Q.mp4506.06KB

Part 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.mp4523.61KB

Part 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-fqt7NIvMB0s.mp4528.9KB

Part 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-uw51WQDqXAI.mp4540.67KB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/10. Objects-H8EBnCkKcds.mp4587.21KB

Part 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-G9yQ_URDrDQ.mp4603.29KB

Part 02-Module 01-Lesson 04_Conditional Probability/15. Medical Example 6-iyE5h48qPFQ.mp4639.69KB

Part 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-etrUbOAoh1U.mp4650.53KB

Part 02-Module 01-Lesson 03_Probability/16. Two Flips 4-rRPwknIDuI0.mp4663.4KB

Part 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2--pOzdj6pnbA.mp4671.97KB

Part 02-Module 01-Lesson 06_Bayes' Rule/13. Total Probability-_hXCgF-aMB0.mp4672.27KB

Part 02-Module 01-Lesson 08_Probability Distributions/11. Spinning Probability-VDQK8gnETqw.mp4712.02KB

Part 02-Module 01-Lesson 11_Robot Localization/30. Formal Definition of Probability 1-OQ2JS2wQzrs.mp4716.63KB

Part 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-E1ph6NP3_v4.mp4747.17KB

Part 02-Module 01-Lesson 06_Bayes' Rule/21. Disease Test 2-GsneDVJB75E.mp4747.61KB

Part 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-UERKMwmkAsM.mp4753.05KB

Part 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-W5i-gRAvZxs.mp4754.47KB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/17. Gaussian Motion-xNPEjY4dsds.mp4793.58KB

Part 02-Module 01-Lesson 03_Probability/07. Fair Coin-fSKL742j-zk.mp4797.83KB

Part 02-Module 01-Lesson 04_Conditional Probability/16. Medical Example 7-cw_zgQbAWNU.mp4803.67KB

Part 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-Y7tnbth-gag.mp4805.43KB

Part 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-PE-k3PGXeLY.mp4812.2KB

Part 02-Module 01-Lesson 08_Probability Distributions/19. Changing Density-dSyPBL0jozI.mp4821.35KB

Part 02-Module 01-Lesson 08_Probability Distributions/12. Stops Nowhere-Ua8DCPx8lhk.mp4824.86KB

Part 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-xFFxdNj6pTA.mp4825.33KB

Part 06-Module 01-Lesson 03_The Search Problem/26. A Search 2 Solution-kvDVL4G_njI.mp4869.76KB

Part 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-_sAkAALHyEg.mp4902.22KB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/09. Nd113 C6 L3 095 L Trigonometric Ratios Solution V2-c5iuVhWCOzc.mp4918.43KB

Part 02-Module 01-Lesson 03_Probability/15. Two Flips 3-uimwo-puQWY.mp4920.84KB

Part 02-Module 01-Lesson 11_Robot Localization/25. Move 1000-x2o1g3J-1nw.mp4922.19KB

Part 02-Module 01-Lesson 06_Bayes' Rule/34. Robot Sensing 8-hyAQ28MYmc4.mp4978.72KB

Part 02-Module 01-Lesson 03_Probability/17. Two Flips 5-HB8b7sZQFGs.mp4990.87KB

Part 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-GMC_T-hbTlc.mp41012.81KB

Part 02-Module 01-Lesson 03_Probability/20. One Head 2-64EjAbqrtmo.mp41.04MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/05. Nd113 C6 L3 055 L Moving At 53 Degrees Solution V2-Y_3M6eeYbd8.mp41.05MB

Part 06-Module 01-Lesson 03_The Search Problem/16. Uniform Cost Search 3-_LtVDVBskhk.mp41.06MB

Part 06-Module 01-Lesson 03_The Search Problem/25. A Search 1 Solution-pfSya9ScozE.mp41.06MB

Part 02-Module 01-Lesson 06_Bayes' Rule/30. Robot Sensing 4-d_fbDqAGVdE.mp41.06MB

Part 06-Module 01-Lesson 04_Implement Route Planner/04. Nd113 Navigating Last Video V1-yJfKK3Mg-BE.mp41.08MB

Part 06-Module 01-Lesson 03_The Search Problem/09. Breath First Search 2-1VykygxreWg.mp41.11MB

Part 06-Module 01-Lesson 03_The Search Problem/26. A Search 2-gYKBDz2kQJ8.mp41.11MB

Part 02-Module 01-Lesson 03_Probability/15. Two Flips 3-3NSPqjp6pFY.mp41.12MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/02. Intro To State-zfilXYrW4Gk.mp41.13MB

Part 02-Module 01-Lesson 08_Probability Distributions/21. Check Density-RJFD5ok1ZIc.mp41.14MB

Part 02-Module 01-Lesson 08_Probability Distributions/15. Range Probability 3-ub9oMx2x-5c.mp41.18MB

Part 04-Module 01-Lesson 05_Python and C++ Speed/01. Introduction-JklGKdn3_go.mp41.19MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/18. Predict Function-DV2cX9W0tT8.mp41.2MB

Part 02-Module 01-Lesson 06_Bayes' Rule/25. Disease Test 6-cdFrLeXIkZU.mp41.21MB

Part 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-V96RcbbVP7Q.mp41.22MB

Part 02-Module 01-Lesson 03_Probability/08. Loaded Coin 1-sNvQeSikRFY.mp41.24MB

Part 01-Module 01-Lesson 01_Introduction/10. Intro to Self-Driving Cars Readiness Introduction-sWKwL3NBa_E.mp41.25MB

Part 06-Module 01-Lesson 03_The Search Problem/27. A Search 3 Solution-Njd5k_I6Sqo.mp41.28MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/14. Separated Gaussians-fGcozDEwnwY.mp41.29MB

Part 02-Module 01-Lesson 04_Conditional Probability/16. Medical Example 7-jPspIs-fNxg.mp41.29MB

Part 06-Module 01-Lesson 03_The Search Problem/27. A Search 3-POXZl2jVy_4.mp41.32MB

Part 02-Module 01-Lesson 11_Robot Localization/07. Generalized Uniform Distribution-e21oU80gwWc.mp41.34MB

Part 06-Module 01-Lesson 03_The Search Problem/22. Search Comparison 3-4KHmQEoqmeI.mp41.35MB

Part 02-Module 01-Lesson 03_Probability/10. Loaded Coin 3-P4uljJ_OP6I.mp41.35MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/18. Predict Function-AMFig-sYGfM.mp41.37MB

Part 06-Module 01-Lesson 03_The Search Problem/29. A Search 5-7d4iHfJXPso.mp41.38MB

Part 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.mp41.4MB

Part 02-Module 01-Lesson 04_Conditional Probability/19. Two Coins 1-SYnYIjLpbjE.mp41.42MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/09. Measurement and Motion 2-1X8Tu6TmKhY.mp41.44MB

Part 06-Module 01-Lesson 01_How to Solve Problems/13. Next Step-1DVj00gpDOk.mp41.44MB

Part 02-Module 01-Lesson 11_Robot Localization/12. Sum of Probabilities-6c0XvswnGm0.mp41.46MB

Part 02-Module 01-Lesson 06_Bayes' Rule/29. Robot Sensing 3--6l4_oprDOk.mp41.48MB

Part 02-Module 01-Lesson 06_Bayes' Rule/21. Disease Test 2-FQM7i07EqGo.mp41.49MB

Part 02-Module 01-Lesson 03_Probability/19. One Head 1-T4A5uyqesjo.mp41.51MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/07. Maximize Gaussian-2cD8T65E-jM.mp41.52MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/05. A Different Model-Mh0g-SMpMI4.mp41.55MB

Part 02-Module 01-Lesson 11_Robot Localization/21. Inexact Motion 3-BldUOLB2U1Y.mp41.56MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/05. Preferred Gaussian-sBsju-6nQWI.mp41.56MB

Part 02-Module 01-Lesson 06_Bayes' Rule/32. Robot Sensing 6-hXyXlk0gYzk.mp41.58MB

Part 02-Module 01-Lesson 11_Robot Localization/12. Sum of Probabilities-z0oijOqN8K8.mp41.58MB

Part 02-Module 01-Lesson 08_Probability Distributions/18. Birth Time Density-U2tkinJKn28.mp41.59MB

Part 02-Module 01-Lesson 11_Robot Localization/32. Formal Definition of Probability 3-oDPbdGXH5nE.mp41.59MB

Part 06-Module 01-Lesson 03_The Search Problem/11. Breath First Search 4-WOANyG8rf0k.mp41.6MB

Part 06-Module 01-Lesson 02_Data Structures/05. Nd113 C5 L02 05 L Representing A Single Ticket V1 RENDER V1-wXTASv5R-VQ.mp41.6MB

Part 03-Module 01-Lesson 05_Implement Matrix Class/06. Nd113 Story 3 V1-Wa1CFHf3k54.mp41.61MB

Part 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-a61GPGk-Qy4.mp41.61MB

Part 02-Module 01-Lesson 08_Probability Distributions/22. Calculate Density-oZDLtTdhDy4.mp41.62MB

Part 04-Module 01-Lesson 01_C++ Getting Started/22. Nd113 C Basics Last Video V1-dtu-RXovl0U.mp41.63MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/05. Another Prediction-JNDsm_Gzxi0.mp41.68MB

Part 02-Module 01-Lesson 04_Conditional Probability/15. Medical Example 6--lC9xztr4zA.mp41.68MB

Part 02-Module 01-Lesson 03_Probability/10. Loaded Coin 3-HohMRlmHoMQ.mp41.69MB

Part 02-Module 01-Lesson 04_Conditional Probability/13. Medical Example 4-pL8Bf6tck_A.mp41.69MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/09. Measurement and Motion 2-dwVwSZuJDBQ.mp41.7MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/08. Measurement and Motion 1-EyE5vOSxPdI.mp41.72MB

Part 02-Module 01-Lesson 08_Probability Distributions/20. Changing Density 2-96Cao3VKUok.mp41.72MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/08. Nd113 C6 L3 08 L Opposite Adjacent Hypotenuse V2-hJ-7qj9iHWo.mp41.73MB

Part 02-Module 01-Lesson 06_Bayes' Rule/31. Robot Sensing 5-PGG9agooCvw.mp41.74MB

Part 02-Module 01-Lesson 04_Conditional Probability/03. Estimating Based on Conditions-RAIkZUZ2BeY.mp41.77MB

Part 02-Module 01-Lesson 11_Robot Localization/19. Inexact Motion 1-mGWGhgZG_jM.mp41.84MB

Part 06-Module 01-Lesson 03_The Search Problem/25. A Search 1-yMUqkCzFXts.mp41.86MB

Part 02-Module 01-Lesson 04_Conditional Probability/02. Introduction To Conditional Probability--_j5NZN2Tfs.mp41.91MB

Part 02-Module 01-Lesson 11_Robot Localization/32. Formal Definition of Probability 3-TF6AWXSlOcY.mp41.92MB

Part 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2--wT7h9Gdm_8.mp41.93MB

Part 02-Module 01-Lesson 11_Robot Localization/25. Move 1000-nYt9b_pNvEE.mp41.94MB

Part 06-Module 01-Lesson 01_How to Solve Problems/17. Harder Example--eAKNo9cA6Y.mp41.95MB

Part 06-Module 01-Lesson 03_The Search Problem/08. Breath First Search 1-70yXCOfKMPA.mp41.95MB

Part 06-Module 01-Lesson 03_The Search Problem/10. Breath First Search 3--ed_C9x8rWs.mp41.97MB

Part 02-Module 01-Lesson 11_Robot Localization/08. Probability After Sense-dEiQObhi2J4.mp41.99MB

Part 02-Module 01-Lesson 11_Robot Localization/24. Move Twice-oqlgQa1IdcY.mp41.99MB

Part 06-Module 01-Lesson 03_The Search Problem/13. Uniform Cost Search-oPe45CJ_o0k.mp42.02MB

Part 02-Module 01-Lesson 06_Bayes' Rule/28. Robot Sensing 2-aBBmlnd7okQ.mp42.03MB

Part 01-Module 02-Lesson 02_Get Ready/01. Intro to Self-Driving Cars How Did You Do-LGZJrihKAg4.mp42.03MB

Part 02-Module 01-Lesson 04_Conditional Probability/17. Medical Example 8-7k5oAaZamCA.mp42.04MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/05. Another Prediction-cUKlYjQEQGY.mp42.05MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/03. Motion Models-qSdbn_PVQnk.mp42.07MB

Part 02-Module 01-Lesson 06_Bayes' Rule/13. Total Probability-fAaE5K9OZJc.mp42.08MB

Part 02-Module 01-Lesson 03_Probability/21. One Of Three 1-rxfHfjy9Mm4.mp42.08MB

Part 02-Module 01-Lesson 06_Bayes' Rule/08. Cancer Test-FnNveASivMA.mp42.08MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/11. Trigonometry And Vehicle Motion-WY3T-9GHI_0.mp42.09MB

Part 02-Module 01-Lesson 04_Conditional Probability/12. Medical Example 3-Rf6WfB_1EJQ.mp42.1MB

Part 02-Module 01-Lesson 11_Robot Localization/22. Inexact Move Function-68Kao9dkIKA.mp42.11MB

Part 02-Module 01-Lesson 03_Probability/17. Two Flips 5-G28YyiGFGWA.mp42.15MB

Part 02-Module 01-Lesson 06_Bayes' Rule/19. Normalizing Probability-V_Gqm42WodI.mp42.17MB

Part 02-Module 01-Lesson 12_Histogram Filter in Python/01. Project Overview-uaWZNKGTtgM.mp42.17MB

Part 04-Module 01-Lesson 01_C++ Getting Started/17. Function Signatures 3 V1-U3QAFb3AS1M.mp42.2MB

Part 02-Module 01-Lesson 08_Probability Distributions/01. Probability Distribution-Srt0yZSCrbY.mp42.21MB

Part 02-Module 01-Lesson 06_Bayes' Rule/10. Normalizing 1-9SbUxcyDTaQ.mp42.23MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/06. Evaluate Gaussian-4-0nBfsD4jo.mp42.23MB

Part 02-Module 01-Lesson 08_Probability Distributions/15. Range Probability 3-q9698qIrPT0.mp42.24MB

Part 06-Module 01-Lesson 01_How to Solve Problems/31. Test for Valid Inputs-6ZV_SjrnvJQ.mp42.24MB

Part 02-Module 01-Lesson 03_Probability/20. One Head 2-JHx3ucNS9f4.mp42.26MB

Part 06-Module 01-Lesson 01_How to Solve Problems/13. Next Step-3XiisY0IPPU.mp42.26MB

Part 02-Module 01-Lesson 09_Programming Probability Distributions/01. Nd113 Bayesian L9 01 V1-dWLZSQiN5vI.mp42.27MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/05. Nd113 C6 L3 05 L Moving At 53 Degrees V2-VmoknN6xLKs.mp42.28MB

Part 02-Module 01-Lesson 04_Conditional Probability/13. Medical Example 4-udduksMWMB4.mp42.29MB

Part 05-Module 01-Lesson 02_C++ Optimization Practice/19. Nd113 C L2 01 V1-h_P7ceb5ido.mp42.31MB

Part 02-Module 01-Lesson 11_Robot Localization/14. Normalized Sense Function-GqWszyHTYas.mp42.34MB

Part 02-Module 01-Lesson 06_Bayes' Rule/28. Robot Sensing 2-t22oDruXhuo.mp42.36MB

Part 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-ys9w-NNKCcU.mp42.36MB

Part 02-Module 01-Lesson 11_Robot Localization/24. Move Twice-sKiumVTdpgY.mp42.37MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/04. Nd113 C6 L3 045 L Moving At An Angle Part2 V2-iI6zCp0RegM.mp42.43MB

Part 06-Module 01-Lesson 02_Data Structures/10. Nd113 C5 L02 09 L Adding Labels V2-VZcXBAHs5ts.mp42.46MB

Part 02-Module 01-Lesson 11_Robot Localization/20. Inexact Motion 2-gZbPZLFKS68.mp42.49MB

Part 02-Module 01-Lesson 04_Conditional Probability/11. Medical Example 2-VLLG0rYC7To.mp42.49MB

Part 06-Module 01-Lesson 01_How to Solve Problems/06. First Step-7WNYd36EDh4.mp42.5MB

Part 06-Module 01-Lesson 03_The Search Problem/32. Sliding Blocks Puzzle 1-jchVkcBg9HQ.mp42.52MB

Part 02-Module 01-Lesson 08_Probability Distributions/17. Density-4FbhjgHIu10.mp42.53MB

Part 02-Module 01-Lesson 08_Probability Distributions/02. Intro To Probability Distribution 1-gqPjMDVFvNg.mp42.55MB

Part 02-Module 01-Lesson 06_Bayes' Rule/17. Probability Given Test-41HCYR-NW-w.mp42.56MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/19. Outro-K1Pj-cr1nFc.mp42.57MB

Part 02-Module 01-Lesson 11_Robot Localization/11. pHit and pMiss-FnhHQht4vDo.mp42.59MB

Part 06-Module 01-Lesson 01_How to Solve Problems/02. Nd113 C5 L1 02 L About This Lesson V1-XOSFGuB2mRs.mp42.59MB

Part 02-Module 01-Lesson 03_Probability/08. Loaded Coin 1-T0EjWSjLGjQ.mp42.63MB

Part 06-Module 01-Lesson 02_Data Structures/04. Nd113 C5 L02 04 L Three Approaches V1 RENDER V1-ptLUqOBlNzU.mp42.64MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/04. Nd113 C6 L3 04 L Moving At An Angle V2-2KDq_ZzN3Mk.mp42.66MB

Part 06-Module 01-Lesson 01_How to Solve Problems/26. What Should We Do Next-kieducUmiD0.mp42.67MB

Part 02-Module 01-Lesson 08_Probability Distributions/23. Density Properties-TxNrRo3jNAM.mp42.68MB

Part 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-mFfbts1lAEo.mp42.69MB

Part 06-Module 01-Lesson 04_Implement Route Planner/01. Nd113 Navigating L3 01 V1-NGSaeofqZPc.mp42.71MB

Part 06-Module 01-Lesson 01_How to Solve Problems/21. Simple Mechanical Algorithm-wN445aeFEFI.mp42.76MB

Part 06-Module 01-Lesson 01_How to Solve Problems/31. Test for Valid Inputs-7c7wYMftRSg.mp42.78MB

Part 02-Module 01-Lesson 06_Bayes' Rule/20. Disease Test 1-05upwXtARuo.mp42.81MB

Part 02-Module 01-Lesson 04_Conditional Probability/04. Dependent Events and Conditional Probability-GDWdCH4ilDI.mp42.85MB

Part 02-Module 01-Lesson 06_Bayes' Rule/16. Cancer Probabilities-CMQBKuYjPBM.mp42.85MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/08. Lesson Outline-jh7wLGXrm3E.mp42.86MB

Part 02-Module 01-Lesson 03_Probability/01. Nd113 C1 L3 01 L Introducing Uncertainty V1-NDOm-0qN8e8.mp42.87MB

Part 02-Module 01-Lesson 03_Probability/03. Learning Objectives Explained-tAkq3iZLJ-c.mp42.89MB

Part 02-Module 01-Lesson 06_Bayes' Rule/02. Bayes' Rule and Robotics-meNSO42JF6I.mp42.91MB

Part 02-Module 01-Lesson 04_Conditional Probability/01. Conditional Probability-Fda3U2HGNVM.mp42.91MB

Part 02-Module 01-Lesson 06_Bayes' Rule/10. Normalizing 1-5Tbd3_a5Vug.mp42.92MB

Part 06-Module 01-Lesson 03_The Search Problem/28. A Search 4-B_rOIxwLzr8.mp42.93MB

Part 02-Module 01-Lesson 03_Probability/16. Two Flips 4-bNoS6LQEFrI.mp42.98MB

Part 02-Module 01-Lesson 03_Probability/14. Two Flips 2-uhrL5fatt3E.mp43MB

Part 06-Module 01-Lesson 03_The Search Problem/30. Optimistic Heuristic-Q5YJtZc37uc.mp43.05MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/12. Parameter Update-Lwn6FJgyyYI.mp43.07MB

Part 02-Module 01-Lesson 11_Robot Localization/11. pHit and pMiss-wOfAyDvun5w.mp43.11MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/09. Nd113 C6 L3 09 L Trigonometric Ratios V2-wquwvrT9g_U.mp43.12MB

Part 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-ysebYA6tDZ4.mp43.15MB

Part 06-Module 01-Lesson 01_How to Solve Problems/08. The First Rule-yh00phtQ-vE.mp43.16MB

Part 02-Module 01-Lesson 08_Probability Distributions/23. Density Properties-U8I0vgojlcY.mp43.17MB

Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/05. 06 L Reasoning About Two Peaks H1 V1-bgPS1GO1EJs.mp43.2MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/23. State Transformation Matrix-DRRuQMYo800.mp43.21MB

Part 06-Module 01-Lesson 01_How to Solve Problems/24. Define Simple nextDay-84mZj582H64.mp43.22MB

Part 05-Module 01-Lesson 01_C++ Intro to Optimization/01. Course Introduction-Lwc5oYApdUM.mp43.25MB

Part 02-Module 01-Lesson 11_Robot Localization/10. Normalize Distribution-Uc_rHR6U70U.mp43.26MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/27. Working With Matrices-nruxu8pr6i8.mp43.27MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/10. Shifting the Mean-HmcurWkA0fQ.mp43.3MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/15. Separated Gaussians 2-0FmTokjoRgo.mp43.31MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/06. Evaluate Gaussian-mQtjczyAxQs.mp43.31MB

Part 02-Module 01-Lesson 06_Bayes' Rule/34. Robot Sensing 8-lmuonrQp_lM.mp43.35MB

Part 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-dGffszQYzqc.mp43.36MB

Part 02-Module 01-Lesson 08_Probability Distributions/13. Range Probability-Vohy3kpnBsk.mp43.39MB

Part 02-Module 01-Lesson 11_Robot Localization/34. Cancer Test-OgC5M2XdIac.mp43.39MB

Part 06-Module 01-Lesson 03_The Search Problem/20. Search Comparison 1-JbJMxp3Lva4.mp43.39MB

Part 02-Module 01-Lesson 03_Probability/13. Two Flips 1-yUIz7SgUwJg.mp43.42MB

Part 02-Module 01-Lesson 08_Probability Distributions/11. Spinning Probability-aS0c5RrnPxU.mp43.44MB

Part 02-Module 01-Lesson 11_Robot Localization/15. Test Sense Function-F8AHaaJVmkw.mp43.47MB

Part 02-Module 01-Lesson 04_Conditional Probability/17. Medical Example 8-btGdX0ZpkNU.mp43.5MB

Part 06-Module 01-Lesson 03_The Search Problem/21. Search Comparison 2-Fh5b8xVJhR8.mp43.51MB

Part 02-Module 01-Lesson 11_Robot Localization/17. Exact Motion-Iky7rJXQU_4.mp43.54MB

Part 06-Module 01-Lesson 03_The Search Problem/07. Graph Search -A8GjRaPJQ5E.mp43.56MB

Part 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-qa9B4r5m8wM.mp43.58MB

Part 05-Module 01-Lesson 01_C++ Intro to Optimization/10. 04 L C And RAM V1 RENDER V1-60jEbKV1UOI.mp43.58MB

Part 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-nUxwwMNKIYo.mp43.59MB

Part 02-Module 01-Lesson 06_Bayes' Rule/20. Disease Test 1-qDGSvvabN18.mp43.62MB

Part 06-Module 01-Lesson 01_How to Solve Problems/39. Solution Step IV-H1oVKsgSsi0.mp43.63MB

Part 02-Module 01-Lesson 03_Probability/24. Doubles-On_Guw8wac8.mp43.65MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/09. Always Moving-EQBQlHvxAQA.mp43.65MB

Part 02-Module 01-Lesson 08_Probability Distributions/24. Summary-w5fm_dJrImE.mp43.65MB

Part 02-Module 01-Lesson 03_Probability/19. One Head 1-lHuZpDkfwq8.mp43.66MB

Part 06-Module 01-Lesson 02_Data Structures/09. Nd113 C5 L2 08 L Keys And Values V1-1FO2KHIJYwY.mp43.66MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/06. Delta X Over Delta T-AsBTLDf0vQs.mp43.71MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/33. Nd113 Matrices L3 12 V1-BRLmFGScL_k.mp43.75MB

Part 02-Module 01-Lesson 06_Bayes' Rule/09. Prior And Posterior-GlmS_jox08s.mp43.75MB

Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/03. Nd113 C6 L2 03 L Acceleration Basics V2-ea6b4PZ7YXU.mp43.76MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/01. Nd113 C2 L3 01 L Connection To Kalman Filters V1-bwaakDKn4nI.mp43.76MB

Part 06-Module 01-Lesson 03_The Search Problem/15. Uniform Cost Search 2-_cSf_1QNaOY.mp43.77MB

Part 06-Module 01-Lesson 03_The Search Problem/14. Uniform Cost Search 1-nBdlU4jIDqU.mp43.79MB

Part 02-Module 01-Lesson 06_Bayes' Rule/07. Bayes Rules-CohZnkZMOxE.mp43.79MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/11. Nd113 C2 L3 09 L Simplifying The Kalman Filter Equations V3-UpC0D-SEtD0.mp43.8MB

Part 02-Module 01-Lesson 11_Robot Localization/01. About This Lesson-xEBSzD-fwps.mp43.81MB

Part 06-Module 01-Lesson 01_How to Solve Problems/12. Obey the Rules-NZq4vDooURs.mp43.84MB

Part 02-Module 01-Lesson 11_Robot Localization/07. Generalized Uniform Distribution-nsSvTTA0p8E.mp43.86MB

Part 02-Module 01-Lesson 11_Robot Localization/30. Formal Definition of Probability 1--F2gJXWbN6s.mp43.86MB

Part 02-Module 01-Lesson 05_Programming Probability in Python/01. Learn by Doing-ypPeggeRdTE.mp43.88MB

Part 02-Module 01-Lesson 08_Probability Distributions/17. Density-4Ri4nhHKtU0.mp43.89MB

Part 06-Module 01-Lesson 01_How to Solve Problems/01. Nd113 Navigating L1 01 V1-5tdMvdcUF-E.mp43.9MB

Part 06-Module 01-Lesson 01_How to Solve Problems/35. Finish daysBetweenDates--70lzVJyS8Y.mp43.93MB

Part 02-Module 01-Lesson 03_Probability/23. Even Roll-M3L0a5V4Nf0.mp43.94MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/04. Variance Comparison-TGdMG81hXc8.mp43.96MB

Part 02-Module 01-Lesson 03_Probability/13. Two Flips 1-1txkcmxk3vU.mp44.01MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/01. Localization Steps-4SiMoSTf4rQ.mp44.06MB

Part 06-Module 01-Lesson 03_The Search Problem/17. Uniform Cost Search 4-yO_uxVtEjq8.mp44.07MB

Part 06-Module 01-Lesson 03_The Search Problem/12. Breath First Search 5-eyN4162UjH8.mp44.07MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/14. Separated Gaussians-QAqsIWVVX0Y.mp44.09MB

Part 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements-gDO4sF8gR9k.mp44.1MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/05. L1 04 B V2-jR7_6Zqq228.mp44.13MB

Part 03-Module 01-Lesson 01_Section Overview/01. Introduction to Matrices-Ugx3mldc0lE.mp44.15MB

Part 03-Module 01-Lesson 05_Implement Matrix Class/01. Nd113P2 C2 L5 01 L Implement Matrix-0Ie9IxW9VDw.mp44.24MB

Part 02-Module 01-Lesson 08_Probability Distributions/21. Check Density-dyqgMA5zRko.mp44.26MB

Part 05-Module 01-Lesson 01_C++ Intro to Optimization/03. 02 L Intro To Comp HW V1 RENDER V1-WDMGkq9mkB8.mp44.26MB

Part 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2-WYA5Zbf8HC4.mp44.26MB

Part 04-Module 01-Lesson 04_C++ Object Oriented Programming/01. Introduction-4xHI5LFX-cQ.mp44.28MB

Part 02-Module 01-Lesson 11_Robot Localization/14. Normalized Sense Function-UX3W8TUKbJ0.mp44.29MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/03. Gaussian Intro-oFpvcWEllBs.mp44.29MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/07. L1 06 B V2-GRaIUM6s6B4.mp44.3MB

Part 06-Module 01-Lesson 01_How to Solve Problems/25. Making Progress Is Good-cUFZPid3yVw.mp44.3MB

Part 06-Module 01-Lesson 03_The Search Problem/19. Search Comparison-RMt_NiyY4nU.mp44.32MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/13. Parameter Update 2-2BfisMbu86o.mp44.4MB

Part 02-Module 01-Lesson 06_Bayes' Rule/01. Reducing Uncertainty-zuFMhmKQ--o.mp44.4MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/14. Nd113 C6 L1 14 L A Typical Calculus Problem Part2 V2-0ww_q51P8uY.mp44.45MB

Part 05-Module 01-Lesson 01_C++ Intro to Optimization/12. C Opt 05 L V3-rTtZVyWxYG8.mp44.47MB

Part 06-Module 01-Lesson 01_How to Solve Problems/32. Real World Problem-lY0CYTfkLWo.mp44.49MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/04. Kalman Filter Prediciton-SK3cnmu8BYU.mp44.49MB

Part 02-Module 01-Lesson 10_Gaussian Distributions/01. Introduction to Gaussian distributions-VQetR_9lBZc.mp44.49MB

Part 02-Module 01-Lesson 03_Probability/11. Complementary Outcomes-YseJqD-1oUg.mp44.5MB

Part 02-Module 01-Lesson 04_Conditional Probability/20. Two Coins 2-tI0J14yQr1s.mp44.52MB

Part 06-Module 01-Lesson 01_How to Solve Problems/14. The Expected Output-tiAFliSz9CY.mp44.59MB

Part 06-Module 01-Lesson 03_The Search Problem/34. Problems With Search-5RmTKsNoG6M.mp44.61MB

Part 02-Module 01-Lesson 04_Conditional Probability/19. Two Coins 1-QIQBb4nLsHc.mp44.61MB

Part 02-Module 01-Lesson 03_Probability/06. Flipping Coins-lgUDXtUyLLg.mp44.62MB

Part 06-Module 01-Lesson 01_How to Solve Problems/19. Should We Implement It-osHXLCQ9TKE.mp44.66MB

Part 06-Module 01-Lesson 03_The Search Problem/18. 17 - Uniform Cost Search 5-oiJLwSnrEDA.mp44.67MB

Part 02-Module 01-Lesson 11_Robot Localization/36. Coin Flip Quiz-hzDsYZ61D5M.mp44.69MB

Part 02-Module 01-Lesson 04_Conditional Probability/22. Two Coins 4-cDub-OOrIRE.mp44.81MB

Part 02-Module 01-Lesson 03_Probability/12. Probability In Robotics-BKLwvL1D0yE.mp44.88MB

Part 02-Module 01-Lesson 08_Probability Distributions/22. Calculate Density-0gcTEExMH3k.mp44.97MB

Part 06-Module 01-Lesson 01_How to Solve Problems/11. What Are the Outputs-4jNzxstbCy0.mp44.98MB

Part 02-Module 01-Lesson 08_Probability Distributions/19. Changing Density-tpsUlBbz5Jo.mp45MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/07. Quantifying State-9zMbwSqTZAc.mp45.01MB

Part 06-Module 01-Lesson 01_How to Solve Problems/27. Define daysBetweenDates-oM3oyyQKQFU.mp45.01MB

Part 06-Module 01-Lesson 01_How to Solve Problems/19. Should We Implement It-M62yGhjmJoA.mp45.05MB

Part 06-Module 01-Lesson 01_How to Solve Problems/26. What Should We Do Next-ZETmw5tFcFU.mp45.06MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/11. Car Object-SnfhGZ76h7Y.mp45.12MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/22. State Vector-st26ov_TVwM.mp45.12MB

Part 04-Module 01-Lesson 01_C++ Getting Started/10. Doubles Are Bigger-uhwTWgmM2iY.mp45.13MB

Part 06-Module 01-Lesson 03_The Search Problem/06. Tree Search Continued-8yID2dTeBSM.mp45.15MB

Part 06-Module 01-Lesson 02_Data Structures/19. Nd113 C5 L2 17 L Conclusion V1-a3Q8QSjpVHQ.mp45.16MB

Part 02-Module 01-Lesson 06_Bayes' Rule/27. Robot Sensing 1--TBAfU1cjRU.mp45.17MB

Part 06-Module 01-Lesson 01_How to Solve Problems/40. Conclusion-JmP5wzHFchc.mp45.18MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/05. Preferred Gaussian--9AVZ-N_gbM.mp45.19MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/14. Nd113 C2 L3 17 L Car Class File V2-OOskkXm0mNc.mp45.2MB

Part 01-Module 01-Lesson 01_Introduction/02. Intro to Self-Driving Cars Welcome From Sebastian-qZt87xwkHro.mp45.2MB

Part 02-Module 01-Lesson 06_Bayes' Rule/04. Using Sensor Data-vhl-SADfti8.mp45.21MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/11. Predicting the Peak-PsyqM704q2Y.mp45.26MB

Part 06-Module 01-Lesson 01_How to Solve Problems/29. Step Two Helper Function-lpprz4op11k.mp45.29MB

Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/06. 07 L The Integral Area Under A Curve H1 V2-QNvgwoIrsIE.mp45.34MB

Part 02-Module 01-Lesson 04_Conditional Probability/21. Two Coins 3-GO6kbL3QRBE.mp45.36MB

Part 02-Module 01-Lesson 11_Robot Localization/17. Exact Motion-1mL6CtD3rAM.mp45.37MB

Part 05-Module 01-Lesson 01_C++ Intro to Optimization/07. 03 L Binary V1 RENDER V1-K6CpHxnhc2s.mp45.37MB

Part 06-Module 01-Lesson 02_Data Structures/02. Tracking Tickets RENDER 1 V1-6sbn7ECEOys.mp45.37MB

Part 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-6tV5NY1HoNA.mp45.43MB

Part 06-Module 01-Lesson 02_Data Structures/03. Nd113 C5 L2 03 L Design Tradeoffs V1-8IpVosy86Fo.mp45.45MB

Part 02-Module 01-Lesson 03_Probability/22. One Of Three 2-gGgqTGZ9TKg.mp45.49MB

Part 02-Module 01-Lesson 03_Probability/05. Probability-arJxFjaMsBM.mp45.49MB

Part 02-Module 01-Lesson 08_Probability Distributions/12. Stops Nowhere-BlC2BwoDxL8.mp45.54MB

Part 02-Module 01-Lesson 06_Bayes' Rule/29. Robot Sensing 3-m1LSU9SPZ2k.mp45.55MB

Part 06-Module 01-Lesson 01_How to Solve Problems/15. Take the Next Step-L4vB8eu6Wo8.mp45.56MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/11. Predicting the Peak-zc_GQiISQ3E.mp45.58MB

Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/06. Nd113 C6 07 L The Integral Area Under A Curve H1 V2-Nhpvh2dolcE.mp45.69MB

Part 02-Module 01-Lesson 02_Joy Ride/01. Project Overview-Ij45-DpGejE.mp45.69MB

Part 02-Module 01-Lesson 03_Probability/23. Even Roll-DrnAR4SqlEE.mp45.7MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/15. Conclusion-gMbDqd4ItiU.mp45.72MB

Part 06-Module 01-Lesson 01_How to Solve Problems/23. What Should We Write First-YCQWVwsCZCk.mp45.79MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/03. L1 02 B V2-AFuQ1i3eUN8.mp45.84MB

Part 02-Module 01-Lesson 03_Probability/07. Fair Coin-9LrlrexpW_o.mp45.84MB

Part 04-Module 01-Lesson 01_C++ Getting Started/02. Nd113 C3 L1 04 L Lesson Overview 2 V1-DjT2E23xhj8.mp45.85MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/24. Color Spaces and Transforms-qd49BIci-yw.mp45.87MB

Part 06-Module 01-Lesson 01_How to Solve Problems/33. Best Strategy-2T1JONL0WyE.mp45.93MB

Part 06-Module 01-Lesson 03_The Search Problem/02. Welcome to Search!-pHySYq-wghU.mp45.96MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/12. Solving Trig Problems Part1-qI4i845d7Qg.mp45.97MB

Part 06-Module 01-Lesson 02_Data Structures/01. Nd113 C5 L2 01 L Lesson Overview V1-LLrp9jq381k.mp46.03MB

Part 04-Module 01-Lesson 01_C++ Getting Started/01. Introduction-ahoiVrq4qAk.mp46.03MB

Part 06-Module 01-Lesson 01_How to Solve Problems/11. What Are the Outputs-5vjhu_cssNQ.mp46.05MB

Part 03-Module 01-Lesson 03_State and Object-Oriented Programming/17. Nd113 C2 L3 20 L Adding Color V2-iltQBIpbCSw.mp46.06MB

Part 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-2PZHPjyYnMg.mp46.09MB

Part 04-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-0ZF649G58l4.mp46.09MB

Part 02-Module 01-Lesson 08_Probability Distributions/20. Changing Density 2-v30w4s2djfc.mp46.18MB

Part 06-Module 01-Lesson 01_How to Solve Problems/07. Understanding a Problem-hkspB2e0S9A.mp46.2MB

Part 01-Module 02-Lesson 02_Get Ready/03. Intro to Self-Driving Cars Intro To Jupyter Notebooks-0-5VG9FsdQ0.mp46.2MB

Part 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.mp46.21MB

Part 02-Module 01-Lesson 08_Probability Distributions/18. Birth Time Density-EhLR8l5XAiQ.mp46.24MB

Part 06-Module 01-Lesson 01_How to Solve Problems/03. Como Resolver Problemas-E6t0oGRXXh8.mp46.25MB

Part 02-Module 01-Lesson 06_Bayes' Rule/35. Generalizing-SdMk3aROgSc.mp46.27MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/16. New Mean and Variance-SwxRWZaC1FM.mp46.31MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/45. Nd113 C7 45 L Classification V1-LWD1M2vqXXo.mp46.54MB

Part 06-Module 01-Lesson 01_How to Solve Problems/20. Different Approach-czjMsAXjWVg.mp46.55MB

Part 06-Module 01-Lesson 03_The Search Problem/03. What Is A Problem-gepUYmWERZA.mp46.59MB

Part 02-Module 01-Lesson 04_Conditional Probability/12. Medical Example 3-Iz4ViIg9ZlQ.mp46.61MB

Part 06-Module 01-Lesson 03_The Search Problem/35. A Note On Implementation-P3mkDcB-nqY.mp46.64MB

Part 02-Module 01-Lesson 06_Bayes' Rule/17. Probability Given Test-omC0zbJyzUY.mp46.72MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/01. L3 01 V2-a_eHxfy5tnI.mp46.79MB

Part 06-Module 01-Lesson 01_How to Solve Problems/10. How Are Inputs Represented-kG94A6xHqZk.mp46.79MB

Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/10. Rate Gyros-TmnecSf80b0.mp46.82MB

Part 02-Module 01-Lesson 08_Probability Distributions/03. Intro To Probability Distribution 2-PglBg4eb_5M.mp46.85MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/11. Defining The Derivative-043a3JRE1hU.mp46.86MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/09. Nd113 C2 L3 08 L Look At Where We Are V2-5EjWMSV-0wo.mp46.93MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/20. Kalman Prediction-tSfmiuB9s2c.mp46.95MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/02. Kalman Prediction-tSfmiuB9s2c.mp46.95MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/09. Nd113 C6 L1 09 L Interpreting Position Vs Time Graphs V3-NAEasXHN_PU.mp46.95MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/08. Measurement and Motion 1-Y7Mr_5Hfe24.mp47.03MB

Part 02-Module 01-Lesson 06_Bayes' Rule/25. Disease Test 6-OdVAt79eQak.mp47.08MB

Part 02-Module 01-Lesson 08_Probability Distributions/10. Landing Probability-PNiaE1fy-7k.mp47.15MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/15. Separated Gaussians 2-edcfMK_bKXw.mp47.18MB

Part 06-Module 01-Lesson 03_The Search Problem/24. A Search-HNdOFYCtfu4.mp47.25MB

Part 02-Module 01-Lesson 11_Robot Localization/10. Normalize Distribution-SW_wvez0izo.mp47.33MB

Part 02-Module 01-Lesson 06_Bayes' Rule/15. Equivalent Diagram-aUFWZ2uJuBE.mp47.38MB

Part 02-Module 01-Lesson 11_Robot Localization/13. Sense Function-Y5iFxWRTw1c.mp47.39MB

Part 04-Module 01-Lesson 01_C++ Getting Started/02. Lesson Overview C++-lR3PH3bL-9U.mp47.4MB

Part 02-Module 01-Lesson 11_Robot Localization/22. Inexact Move Function-QCnPJcNprEU.mp47.42MB

Part 06-Module 01-Lesson 03_The Search Problem/31. Sliding Blocks Puzzle-Dzah_49isp8.mp47.44MB

Part 02-Module 01-Lesson 01_Introduction/02. Course Overview-QTFIJNBXx9w.mp47.45MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/10. Nd113 C2 L3 08 L The Kalman Filter Equations V2-X9UUpk5URuw.mp47.49MB

Part 02-Module 01-Lesson 11_Robot Localization/15. Test Sense Function-Lf2DYUCsUH4.mp47.5MB

Part 01-Module 01-Lesson 01_Introduction/09. Intro to Self-Driving Cars Expectations for this Nanodegree-TTOhBB7QaUg.mp47.65MB

Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/12. Working with Real Data-WvEcWtAz-OQ.mp47.66MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/20. Nd113 C7 19 L Color Masking-4U5fYTbSDg0.mp47.7MB

Part 02-Module 01-Lesson 06_Bayes' Rule/36. Sebastian At Home-TtmQ7YCw_1Y.mp47.74MB

Part 05-Module 01-Lesson 01_C++ Intro to Optimization/02. C Opt 01 L V2-Kdx1_BI5ddc.mp47.76MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/13. Parameter Update 2-_AAkw_fynwc.mp47.86MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/39. Nd113 C7 36 L Filters And Finding Edges V1-f3H2EtiZLOQ.mp47.91MB

Part 04-Module 01-Lesson 03_Practical C++/01. Introduction To Compilation-dyzGEB8YDGg.mp47.96MB

Part 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/07. Power of Trigonometry-yLMTfBq_I3k.mp47.98MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/05. Nd113 C7 03 L Vision And SelfDriving Cars V1-dezDkQ47NaY.mp48.09MB

Part 04-Module 01-Lesson 01_C++ Getting Started/17. Function Signatures 2-Sx4AWTmXl2U.mp48.1MB

Part 06-Module 01-Lesson 03_The Search Problem/04. Example Route Finding-5lrkPKQwOFE.mp48.12MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/03. Welcome To Computer Vision-qAGnachIrxs.mp48.13MB

Part 02-Module 01-Lesson 04_Conditional Probability/22. Two Coins 4-9R44IyZ-aQI.mp48.19MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/04. Variance Comparison-rczAG7meAY4.mp48.19MB

Part 06-Module 01-Lesson 01_How to Solve Problems/22. Don't Optimize Prematurely-uQDk8euwyDI.mp48.2MB

Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/01. L2 01 V2-GRgbA3XBy6w.mp48.32MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/10. What Is Machine Learning-3mzV7uQhEos.mp48.33MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/07. Maximize Gaussian-fRYtUP0P4Lg.mp48.34MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/18. Pre-processing--h1GS0SEyzY.mp48.47MB

Part 02-Module 01-Lesson 01_Introduction/01. The Wonderland of Probability and Bayes' Rule-gfFWpMehzpk.mp48.49MB

Part 01-Module 01-Lesson 01_Introduction/03. Meet The Team-U7OiT5kWlnQ.mp48.56MB

Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/07. Approximating The Integral-9C05AHzI_I8.mp48.57MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/02. Tracking Intro-lDykH1UHq38.mp48.67MB

Part 02-Module 01-Lesson 11_Robot Localization/18. Move Function-wfjE0mVADIk.mp48.7MB

Part 09-Module 01-Lesson 01_Congratulations! You've finished!/01. Congratulations on completing Intro to Self-Driving Cars!-w640r8wujPw.mp48.74MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/31. Feature Extraction-DkmLO7PKhy8.mp48.88MB

Part 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-kfPWiMsnWFI.mp48.9MB

Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/15. L2 18 V2-nCJQl2kH8bY.mp48.98MB

Part 02-Module 01-Lesson 03_Probability/21. One Of Three 1-bDCXSxkochE.mp49.02MB

Part 02-Module 01-Lesson 03_Probability/25. Summary-hIEDvyCETEw.mp49.06MB

Part 02-Module 01-Lesson 06_Bayes' Rule/19. Normalizing Probability-yYqN9Mf4jqw.mp49.25MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/51. Ends and Beginnings-lCUkFi4fwLY.mp49.3MB

Part 02-Module 01-Lesson 11_Robot Localization/36. Coin Flip Quiz-ASUXN9Ay35M.mp49.32MB

Part 06-Module 01-Lesson 01_How to Solve Problems/21. Simple Mechanical Algorithm-gPfkboHV3QA.mp49.44MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/16. New Mean and Variance-yo8jf0U4hlc.mp49.46MB

Part 02-Module 01-Lesson 11_Robot Localization/20. Inexact Motion 2-jR7FERpsqe4.mp49.54MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/15. Color Images--XbXiiGQ9gw.mp49.6MB

Part 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-1s2dRczcu1A.mp49.74MB

Part 06-Module 01-Lesson 01_How to Solve Problems/06. First Step-N8dKtrrCZ7U.mp49.78MB

Part 02-Module 01-Lesson 04_Conditional Probability/08. Dependent Things-NDL-rxSYJWo.mp49.81MB

Part 06-Module 01-Lesson 03_The Search Problem/23. More Uniform Cost-8xH-3WtswDs.mp49.82MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/50. Nd113 C7 47 L Outro-YbWjhAVvdKc.mp49.84MB

Part 02-Module 01-Lesson 06_Bayes' Rule/30. Robot Sensing 4-vasdN2Gol0M.mp49.87MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/32. Nd113 C7 29 L Features-HshygbfQylA.mp410.05MB

Part 02-Module 01-Lesson 11_Robot Localization/34. Cancer Test-SZ6Jg1wS604.mp410.06MB

Part 02-Module 01-Lesson 11_Robot Localization/28. Localization Summary-MVbo4OAgQCc.mp410.12MB

Part 06-Module 01-Lesson 01_How to Solve Problems/16. Try an Example-X29RjzKHsWU.mp410.19MB

Part 06-Module 01-Lesson 01_How to Solve Problems/14. The Expected Output-trokjJravhc.mp410.3MB

Part 06-Module 01-Lesson 03_The Search Problem/05. Tree Search-lCuwrHKxNlU.mp410.32MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/10. L1 09 V2-b-zB9Bs8zKQ.mp410.42MB

Part 04-Module 01-Lesson 01_C++ Getting Started/06. Static Vs Dynamic Typing-D7v6iIAORkE.mp410.49MB

Part 06-Module 01-Lesson 01_How to Solve Problems/37. Solution Step II-SGC8UAz12Q4.mp410.56MB

Part 06-Module 01-Lesson 01_How to Solve Problems/28. Step One Pseudocode-hJzpU5qC3hs.mp410.57MB

Part 04-Module 01-Lesson 04_C++ Object Oriented Programming/03. Why Use Object Oriented Programming-G2KzZfNu9Ak.mp410.64MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/01. Introduction-XZL934YQ-FQ.mp410.68MB

Part 06-Module 01-Lesson 03_The Search Problem/33. Sliding Blocks Puzzle 2-7vExAvX3LbI.mp410.85MB

Part 06-Module 01-Lesson 01_How to Solve Problems/04. Days Between Dates-VLrJ01wEajw.mp410.86MB

Part 02-Module 01-Lesson 04_Conditional Probability/20. Two Coins 2-hoVOT8qcQ7c.mp410.92MB

Part 02-Module 01-Lesson 11_Robot Localization/18. Move Function-TnFq6hufsYs.mp410.96MB

Part 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-_AhoOd8YUK0.mp411.03MB

Part 02-Module 01-Lesson 06_Bayes' Rule/36. Sebastian At Home-R4zq6mPPMxs.mp411.04MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/27. Nd113 C7 25 L Day And Night Classification NEEDS ANM V1-bsra6mwtw7U.mp411.13MB

Part 02-Module 01-Lesson 03_Probability/22. One Of Three 2-27Ed1GI4j84.mp411.22MB

Part 02-Module 01-Lesson 03_Probability/24. Doubles-fkUyTJNbdzU.mp411.26MB

Part 02-Module 01-Lesson 03_Probability/06. Flipping Coins-OpNufHYgJCg.mp411.32MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/22. Nd113 C7 20 L Green Screen Car V2-_YEdV_mRKXQ.mp411.37MB

Part 02-Module 01-Lesson 06_Bayes' Rule/27. Robot Sensing 1-_DjfTytro6I.mp411.42MB

Part 02-Module 01-Lesson 04_Conditional Probability/18. Total Probability-YSYpzFR4k1I.mp411.54MB

Part 04-Module 01-Lesson 01_C++ Getting Started/16. Function Signatures 1-T6kQ_4w98IQ.mp411.65MB

Part 02-Module 01-Lesson 11_Robot Localization/21. Inexact Motion 3-7T1Rr7KLgdM.mp411.85MB

Part 06-Module 01-Lesson 01_How to Solve Problems/23. What Should We Write First-HRepefDqkDM.mp411.93MB

Part 04-Module 01-Lesson 01_C++ Getting Started/04. Why C++-_t4ZvwfnuCA.mp411.98MB

Part 06-Module 01-Lesson 01_How to Solve Problems/24. Define Simple nextDay-Qttkfhh3I5s.mp412.01MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/20. Kalman Prediction-doyrdLJ6rJ4.mp412.36MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/02. Kalman Prediction-doyrdLJ6rJ4.mp412.36MB

Part 02-Module 01-Lesson 06_Bayes' Rule/14. Bayes Rule Diagram-b8M9CWxRyQ4.mp412.52MB

Part 05-Module 01-Lesson 02_C++ Optimization Practice/16. Nd113 Story 1 V1-lIe2zso8A-w.mp412.76MB

Part 02-Module 01-Lesson 04_Conditional Probability/21. Two Coins 3-JIWv5fU3GLA.mp412.85MB

Part 02-Module 01-Lesson 11_Robot Localization/13. Sense Function-eIjyrQpDogg.mp412.91MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/02. Nd113 C6 L1 01 Inertial Navigation V1 (1)-vWgG0d2HOVE.mp412.92MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/02. Computer Vision and Sebastian-pil3PeZzCIY.mp413.05MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/43. Nd113 C7 40 L Convolution In Self-Driving Cars-nz7rOTZ99X4.mp413.07MB

Part 04-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-9SgmzOfBmRU.mp413.16MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/19. Kalman Filter Code-3xBycKfnCOQ.mp413.28MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/25. Nd113 C7 23 L HSV Conversion-GbrJi0U8T20.mp413.31MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/09. Learning To Classify Images-_mE0nkLPSw0.mp413.65MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/04. Nd113 C7 02 L Introducing Tarin V2-us2b__pBR8Y.mp413.97MB

Part 02-Module 01-Lesson 11_Robot Localization/08. Probability After Sense-UFcTLCttNRI.mp414.05MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/04. Kalman Filter Prediciton-HTL5-0DDqE4.mp414.2MB

Part 06-Module 01-Lesson 01_How to Solve Problems/30. Step Three daysBetweenDates-DOkkOsraobw.mp414.55MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/10. Shifting the Mean-8c479K2UCZo.mp414.6MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/29. Labeled Data and Accuracy-FN96OM_JGyM.mp414.66MB

Part 02-Module 01-Lesson 06_Bayes' Rule/09. Prior And Posterior-o2Tpws5C2Eg.mp414.97MB

Part 02-Module 01-Lesson 11_Robot Localization/19. Inexact Motion 1-C3f-T9_GTpw.mp415.07MB

Part 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-K8g3Hss8Q1A.mp415.44MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/07. Image Classification Pipeline-jfu6aqvU1vQ.mp415.61MB

Part 02-Module 01-Lesson 04_Conditional Probability/23. Summary-yepMH9VswI8.mp415.78MB

Part 06-Module 01-Lesson 01_How to Solve Problems/09. What Are the Inputs-cAr-unfe-mg.mp415.82MB

Part 06-Module 01-Lesson 01_How to Solve Problems/18. Algorithm Pseudocode-Ei91QeYiG_E.mp416.14MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/40. High Pass Filters-JOa9ZtV_rB4.mp416.34MB

Part 02-Module 01-Lesson 06_Bayes' Rule/26. Bayes Rule Summary-RgXQ8GRsjfc.mp416.86MB

Part 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-SXSafquSoW8.mp417.04MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/03. Gaussian Intro-GHKKUR6tZE0.mp417.07MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/12. Parameter Update-d8UrbKKlGxI.mp417.31MB

Part 06-Module 01-Lesson 01_How to Solve Problems/36. Solution Step I-bIZgt0ttMeU.mp417.42MB

Part 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2-rmWL_3r8MKo.mp417.54MB

Part 02-Module 01-Lesson 11_Robot Localization/35. Theorem of Total Probability-byZ-BzbQA5M.mp417.79MB

Part 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.mp417.79MB

Part 02-Module 01-Lesson 06_Bayes' Rule/08. Cancer Test-CNpSrdnYvbo.mp418.01MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/35. Nd113 C7 32 L Average Brightness V2-oUlOS670uQg.mp421.19MB

Part 01-Module 01-Lesson 01_Introduction/01. Final Teaser ISDC-j7iB0p4dOj4.mp421.51MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/37. Nd113 C7 33 L Features And Classification-Ni3ocWoUDPk.mp421.67MB

Part 02-Module 01-Lesson 04_Conditional Probability/11. Medical Example 2-FV_hc3MzS_8.mp422.05MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/13. Images as Grids of Pixels-RVNiaZuv6Ss.mp422.58MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/03. Kalman Filter Land-LXJ5jrvDuEk.mp422.64MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/48. Nd113 C7 46 L Evaluation Metrics-fDN4D1QV674.mp423.75MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/17. Gaussian Motion-X7YggdDnLaw.mp424.56MB

Part 06-Module 01-Lesson 01_How to Solve Problems/33. Best Strategy-JsMwEH8cluU.mp424.6MB

Part 06-Module 01-Lesson 01_How to Solve Problems/38. Solution Step III-CRv1ogJYe8w.mp424.99MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/02. Tracking Intro-8O9GV4SUToA.mp425.53MB

Part 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/01. Meet Phantom Auto-D6-7L9nZMPY.mp426.49MB

Part 05-Module 01-Lesson 01_C++ Intro to Optimization/04. Nd113 Embedded Terminal V1-Bhl5JQ_N9V8.mp426.5MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/08. Kalman Filter Design-KYEr4BXhD_E.mp427.34MB

Part 02-Module 01-Lesson 11_Robot Localization/33. Bayes' Rule-sA5wv56qYc0.mp429MB

Part 02-Module 01-Lesson 11_Robot Localization/02. Introduction-Uqt_pRbR8rI.mp432MB

Part 03-Module 01-Lesson 02_Introduction to Kalman Filters/19. Kalman Filter Code-X7cixvcogl8.mp433.73MB

Part 03-Module 01-Lesson 04_Matrices and Transformation of State/06. More Kalman Filters-hUnTg5v4tDU.mp435.46MB

Part 02-Module 01-Lesson 11_Robot Localization/04. Total Probability-n1EacrqyCs8.mp440.4MB

Part 08-Module 01-Lesson 01_Computer Vision and Classification/01. Meet Danny Shapiro At Nvidia-tglLnJNHSI4.mp443.21MB

Part 05-Module 01-Lesson 03_Project Optimize Histogram Filter/02. Nd113 Running The Project V1--X1pB-HTdnQ.mp480.41MB

Part 01-Module 02-Lesson 02_Get Ready/05. The Great Robot Race-UFGu15hCtKg.mp4301.22MB