Week Date Topics Slides
1 3/17(Tue)  Lecture 1. Introduction
3/19(Thu)  Lecture 2. Intelligent Agents
2 3/24(Tue)  Lecture 3. Problem Solving and Search
3/26(Thu)  Lecture 4. Beyond Classical Search
3 3/31(Tue)  Lecture 5. Adversarial Search
4/2(Thu) Lecture 6. Logical Agents
4 4/7(Tue)  Lecture 7. First-Order Logic
4/9(Thu)  Lecture 8. Inference in First-Order Logic
5 4/14(Tue) Lecture 9. Probabilistic Reasoning
4/16(Thu)  -
6 4/23(Tue)  Lecture 10. Bayesian Networks
4/23(Thu)   Practice Session 1: Bayesian Networks
7 4/28(Tue)  Midterm
4/16(Thu)  Review and Discussion
8 4/21(Tue)  Mid term
4/23(Thu)  Practice Session 3 (Hidden Markov Models)
 Project 2 Announcement
9 4/28(Tue)  Temporal Reasoning 1
 (Ch. 15. Probabilistic Reasoning over Time, HMM)

4/30(Thu)  Holiday
10 5/4(Mon)  Temporal Reasoning 2
 (Ch. 15. Kalman Filters, DBN, Particle Filters))
5/5(Tue)  Holiday
5/7(Thu)  Temporal Reasoning 3 (Ch. 15. Dynamic Bayesian Networks)
11 5/12(Tue)  Learning Probabilistic Models 1
 (Ch 20. Learning Probabilistic Models 1)

5/14(Thu)  Neural Networks
 (Ch 18.7. Artificial Neural Networks))

12 5/19(Tue)  Practice Session 4
5/21(Thu)  Neural Networks
 (Ch 18.7. Artificial Neural Networks))
13 5/26(Tue)   Natural Language (Ch 22-23. Natural Language Processing)
5/28(Thu)  Vision (Ch 24. Perception)
14 6/2(Tue)  Robotics (Ch. 25. Robotics)
6/4(Thu)  Final Exam
15 6/9(Tue)  Project 2 Poster Presentation
6/11(Thu)  Future of AI (Discussion)