Subscribe to this calendar (Google, iCal, etc.)
Note: Dates and topics are subject to change as the course progresses.

March
Monday	Tuesday	Wednesday	Thursday	Friday
30 14:30-15:20 Lecture CSE2 G01 Introduction slides	31	01 14:30-15:20 Lecture CSE2 G01 Math, Data Structures, Algorithms, Python, AI Coding Background slides	02	03 14:30-15:20 Lecture CSE2 G01 State-Space Search I: States, Operators, Moves, Spaces, Formulation slides

April
Monday	Tuesday	Wednesday	Thursday	Friday
06 14:30-15:20 Lecture CSE2 G01 Basic Algorithms, Iterative Deepening, Combinatorial Explosion slides	07	08 14:30-15:20 Lecture CSE2 G01 SSS III: Searching Weighted Graphs, Uniform-Cost Search, A* Algorithm Intro. slides 23:59 A1 (Python Warm-up) due	09	10 14:30-15:20 Lecture CSE2 G01 A* Algorithm Details slides
13 14:30-15:20 Lecture CSE2 G01 Comparing and Designing Heuristics slides 23:59 A2 Part A (Blind Search) due	14	15 14:30-15:20 Lecture CSE2 G01 Adversarial Search I: Static Evaluation, Minimax Search slides	16	17 14:30-15:20 Lecture CSE2 G01 Adversarial Search II: Alpha-Beta Pruning slides 23:59 A2 Parts B and C (Heuristic Search) due
20 14:30-15:20 Lecture CSE2 G01 Adversarial Search III: Zobrist Hashing slides	21	22 14:30-15:20 Lecture CSE2 G01 Expectimax Search and Probability 23:59 A3 (Exercises I) due	23	24 14:30-15:20 Lecture CSE2 G01 Markov Decision Processes (e.g., for Robot World Modeling)
27 14:30-15:20 Midterm 1 exam	28	29 14:30-15:20 Lecture CSE2 G01 MDP Values, Bellman Equations and Value Iteration	30	01 14:30-15:20 Lecture CSE2 G01 Value Iteration (continued), Q-Learning

May
Monday	Tuesday	Wednesday	Thursday	Friday
04 14:30-15:20 Lecture CSE2 G01 Q-Learning (continued) 23:59 A4 (Game-Playing Agents) due	05	06 14:30-15:20 Lecture CSE2 G01 Joint Probability Distributions	07	08 14:30-15:20 Lecture CSE2 G01 Bayes Nets
11 14:30-15:20 Lecture CSE2 G01 Introducing a Markov Decision Process for Towers of Hanoi 23:59 A5 (Exercises II) due	12	13 14:30-15:20 Lecture CSE2 G01 D-Separation (Reasoning about Factored Prob. Distributions)	14	15 14:30-15:20 Lecture CSE2 G01 Markov Models (a Special Factoring Structure for BNs)
18 14:30-15:20 Midterm 2 exam	19	20 14:30-15:20 Lecture CSE2 G01 Hidden Markov Models and the Viterbi Algorithm	21	22 14:30-15:20 Lecture CSE2 G01 Perceptrons 23:59 A6 (Implementing Reinf. Learning) due
25 Memorial Day	26	27 14:30-15:20 Lecture CSE2 G01 Multiclass Perceptrons; Ethics I: The Asimov Laws, Trolley Problems	28	29 14:30-15:20 Lecture CSE2 G01 NN Architectures, Backpropagation, Word Embeddings

June
Monday	Tuesday	Wednesday	Thursday	Friday
01 14:30-15:20 Lecture CSE2 G01 Large Language Models, Self-Attention, Transformers. 23:59 A7 (Exercises III) due	02	03 14:30-15:20 Lecture CSE2 G01 Agent Presentations.	04	05 14:30-15:20 Lecture CSE2 G01 The Future of AI: Opportunities and Challenges; Course Wrap-up and Comments on the Final Exam
08	09 14:30-16:20 Final exam	10	11	12