Resources
| Date | Lectures and Exercises | Additional Resources |
|---|---|---|
| Week 1 Jan 18, 20 |
Introduction, AI Ethics |
|
| Week 2 Jan 25, 27 |
Search |
|
| Week 3 Feb 1, 8 |
Constraint Satisfaction Problems and Local Search |
|
| Week 4 Feb 10, 15 |
Adversarial Search, Utilities |
|
| Week 5 Feb 17 |
Markov Decision Processes |
|
| Week 6 Feb 22, 24 |
Reinforcement Learning |
|
| Week 7 March 1, 3 |
Probability and Bayes Nets: Representation |
|
| Week 8 March 8, 10 |
Bayes Nets: Independence, Midterm |
|
| Week 9 March 22, 24 |
Bayes Nets: Inference and Sampling |
|
| Week 10 March 29, 31 |
(Hidden) Markov Models, Particle Filters |
|
| Week 11 April 5, 7 |
Decision Networks and Naive Bayes |
|
| Week 12 April 12, 14 |
Perceptrons, Kernels, Clustering |
|
| Week 13 April 19, 21 |
Deep Learning |
|
| Week 13 April 19, 21 |
Advanced Topics: Robotics
|
|
| Week 15 May 3, 5 |
AI Advances and Conclusion |
|
| Final Exam May 13, 2-5 pm |
Final ExamLocation: CAL 100 |