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Massachusetts Institute of Technology via YouTube Video playlist

MIT 6.034 Artificial Intelligence, Fall 2010

Overview

View the complete course: http://ocw.mit.edu/6-034F10

Instructor: Patrick Winston

In these lectures, Prof. Patrick Winston introduces the 6.034 material from a conceptual, big-picture perspective. Topics include reasoning, search, constraints, learning, representations, architectures, and probabilistic inference.

License: Creative Commons BY-NC-SA

More information at http://ocw.mit.edu/terms

More courses at http://ocw.mit.edu

Videos in this playlist 30

  1. 1. Introduction and Scope
  2. 2. Reasoning: Goal Trees and Problem Solving
  3. 3. Reasoning: Goal Trees and Rule-Based Expert Systems
  4. 4. Search: Depth-First, Hill Climbing, Beam
  5. 5. Search: Optimal, Branch and Bound, A*
  6. 6. Search: Games, Minimax, and Alpha-Beta
  7. 7. Constraints: Interpreting Line Drawings
  8. 8. Constraints: Search, Domain Reduction
  9. 9. Constraints: Visual Object Recognition
  10. 10. Introduction to Learning, Nearest Neighbors
  11. 11. Learning: Identification Trees, Disorder
  12. 12a: Neural Nets
  13. 12b: Deep Neural Nets
  14. 13. Learning: Genetic Algorithms
  15. 14. Learning: Sparse Spaces, Phonology
  16. 15. Learning: Near Misses, Felicity Conditions
  17. 16. Learning: Support Vector Machines
  18. 17. Learning: Boosting
  19. 18. Representations: Classes, Trajectories, Transitions
  20. 19. Architectures: GPS, SOAR, Subsumption, Society of Mind
  21. 21. Probabilistic Inference I
  22. 22. Probabilistic Inference II
  23. 23. Model Merging, Cross-Modal Coupling, Course Summary
  24. Mega-R1. Rule-Based Systems
  25. Mega-R2. Basic Search, Optimal Search
  26. Mega-R3. Games, Minimax, Alpha-Beta
  27. Mega-R4. Neural Nets
  28. Mega-R5. Support Vector Machines
  29. Mega-R6. Boosting
  30. Mega-R7. Near Misses, Arch Learning

Advantages and disadvantages

Advantages

  • Free and complete: every lecture is in the playlist, in order.
  • Watch at 1.5x, skip what you know, rewatch what you don't.
  • Taught by Massachusetts Institute of Technology, one of the strongest names in its field.
  • 2,200,462 views, so help and notes are easy to find.
  • Completely free.
  • Self-paced: start any time.
  • A clear syllabus (30 videos) you can see before you start.
  • Start watching right away, no sign-up.

Disadvantages

  • No certificate, deadlines or graded work.
  • Quality and depth vary: check that the playlist is finished before you start.
  • No certificate.
  • No graded assignments or feedback.
  • Recorded in 2013: tools may have changed since.

Some points apply to every course of this kind; see how we rank.

Free

  • Free: Watch on YouTube, no account needed.
  • Certificate: None. Code or take notes along to make it stick.

Massachusetts Institute of Technology is in Tier 1: world-leading universities and India's top institutes of our institution ranking (98/100). OpenCourseWare is the gold standard for free university material.

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