Resources

Date Lectures and Exercises Additional Resources
Week 1
Jan 19, 21
Introduction, AI Ethics

Week 2
Jan 26, 28
Search

Week 3
Feb 2, 4
Constraint Satisfaction Problems and Local Search

Week 4
Feb 9, 11
Adversarial Search, Utilities

Week 5
Feb 23, 25
Markov Decision Processes

Week 6
March 2, 4
Reinforcement Learning

Week 7
March 9, 11
Bayes Nets: Representation and Inference

Week 8
March 23, 25
Midterm

  • The Berkeley course's past exams (with solutions)
Week 9
March 30, April 1
(Hidden) Markov Models, Particle Filters, and VPI

Week 10
April 6, 8
Naive Bayes and Perceptrons

Week 11
April 13, 15
Deep Learning

Week 12
April 20, 22
SVMs, Kernels, and Clustering

Week 13
April 27, 29
Classical Planning

Week 14
May 4, 6
Philosophical Foundations

Final Exam
Wed May 12, 2-5pm
Final Exam