1
6.034 Artificial Intelligence (Fall 2010, MIT OCW). Instructor: Professor Patrick Henry Winston.
FREE
This course includes
Hours of videos
583 years, 3 months
Units & Quizzes
21
Unlimited Lifetime access
Access on mobile app
Certificate of Completion
This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to concrete computational problems; understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering; and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective. (from ocw.mit.edu)
Course Currilcum
- Lecture 01 – Introduction and Scope Unlimited
- Lecture 02 – Reasoning: Goal Trees and Problem Solving Unlimited
- Lecture 03 – Reasoning: Goal Trees and Rule-Based Expert Systems Unlimited
- Lecture 04 – Search: Depth-First, Hill Climbing, Beam Unlimited
- Lecture 05 – Search: Optimal, Branch and Bound, A* Unlimited
- Lecture 06 – Search: Games, Minimax, and Alpha-Beta Unlimited
- Lecture 07 – Constraints: Interpreting Line Drawings Unlimited
- Lecture 09 – Constraints: Visual Object Recognition Unlimited
- Lecture 10 – Introduction to Learning, Nearest Neighbors Unlimited
- Lecture 11 – Learning: Identification Trees, Disorder Unlimited
- Lecture 12 – Learning: Neural Nets, Back Propagation Unlimited
- Lecture 13 – Learning: Genetic Algorithms Unlimited
- Lecture 14 – Learning: Sparse Spaces, Phonology Unlimited
- Lecture 15 – Learning: Near Misses, Felicity Conditions Unlimited
- Lecture 16 – Learning: Support Vector Machines Unlimited
- Lecture 17 – Learning: Boosting Unlimited
- Lecture 18 – Representations: Classes, Trajectories, Transitions Unlimited
- Lecture 19 – Architectures: GPS, SOAR, Subsumption, Society of Mind Unlimited
- Lecture 21 – Probabilistic Inference I Unlimited
- Lecture 22 – Probabilistic Inference II Unlimited
- Lecture 23 – Model Merging, Cross-Modal Coupling, Course Summary Unlimited
