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) |
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Feb 21 |
Recap for Exam 1 |
Lecture 13 |
Feb 25 |
In-class Exam 1 |
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Feb 28 |
Introduction to Probability |
Lecture 14 |
Mar 04 |
No Class (Spring Break) |
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Mar 06 |
No Class (Spring Break) |
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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 |
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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 |
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Apr 22 |
In-class Exam 3 |
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