Artificial Intelligence with Patrick Winston

Course Description

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.

Artificial Intelligence with Patrick Winston
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Video Lectures & Study Materials

Visit the official course website for more study materials:

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


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