Course Schedule and Lecture Slides

Date Topic Resources
Jan 07 Course Introduction, History and Foundations of AI Lecture 1
Jan 10 Search I Lecture 2
Jan 14 Search II Lecture 3
Jan 17 Constraint Satisfaction Problems Lecture 4
Jan 21 Logic Lecture 5
Jan 24 Game Trees I Lecture 6
Jan 28 Game Trees II Lecture 7
Jan 31 Markov Decision Processes Intro (short guest lecture) Lecture 8
Feb 04 Markov Decision Processes I - contd Lecture 9
Feb 07 Markov Decision Processes II Lecture 10
Feb 11 Reinforcement Learning I Lecture 11
Feb 14 Reinforcement Learning II Lecture 12
Feb 18 No class (Monday Schedule)
Feb 21 Recap for Exam 1 Lecture 13
Feb 25 In-class Exam 1
Feb 28 Introduction to Probability Lecture 14
Mar 04 No Class (Spring Break)
Mar 06 No Class (Spring Break)
Mar 11 Bayes Nets I Lecture 15
Mar 14 Bayes Nets II Lecture 16
Mar 18 Bayes Nets III Lecture 17
Mar 21 Recap for Exam 2 Lecture 18
Mar 25 In-class Exam 2
Mar 28 Decision Networks and Value of Information Lecture 19
Apr 01 Hidden Markov Models Lecture 20
Apr 04 Machine Learning I Lecture 21
Apr 08 Machine Learning II Lecture 22 and MIRA
Apr 11 Machine Learning III Lecture 23
Apr 15 AI applications, AI Ethics, Safety, and Security Lecture 24
Apr 18 Recap for Exam 3
Apr 22 In-class Exam 3