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Note: Dates and topics are subject to change as the course progresses.
| March | ||||
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| Monday | Tuesday | Wednesday | Thursday | Friday |
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14:30-15:20 Lecture
CSE2 G01 Introduction |
14:30-15:20 Lecture
CSE2 G01 Math, Data Structures, Algorithms, Python, AI Coding Background |
14:30-15:20 Lecture
CSE2 G01 State-Space Search I: States, Operators, Moves, Spaces, Formulation |
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| April | ||||
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| Monday | Tuesday | Wednesday | Thursday | Friday |
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14:30-15:20 Lecture
CSE2 G01 Basic Algorithms, Iterative Deepening, Combinatorial Explosion |
14:30-15:20 Lecture
CSE2 G01 SSS III: Searching Weighted Graphs, Uniform-Cost Search, A* Algorithm Intro.
23:59 A1 (Python Warm-up) due
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14:30-15:20 Lecture
CSE2 G01 A* Algorithm Details |
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14:30-15:20 Lecture
CSE2 G01 Comparing and Designing Heuristics
23:59 A2 Part A (Blind Search) due
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14:30-15:20 Lecture
CSE2 G01 Adversarial Search I: Static Evaluation, Minimax Search |
14:30-15:20 Lecture
CSE2 G01 Adversarial Search II: Alpha-Beta Pruning
23:59 A2 Parts B and C (Heuristic Search) due
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14:30-15:20 Lecture
CSE2 G01 Adversarial Search III: Zobrist Hashing |
14:30-15:20 Lecture
CSE2 G01 Expectimax Search and Probability
23:59 A3 (Exercises I) due
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14:30-15:20 Lecture
CSE2 G01 Markov Decision Processes (e.g., for Robot World Modeling) |
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14:30-15:20 Midterm 1 exam
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14:30-15:20 Lecture
CSE2 G01 MDP Values, Bellman Equations and Value Iteration |
14:30-15:20 Lecture
CSE2 G01 Value Iteration (continued), Q-Learning |
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| May | ||||
|---|---|---|---|---|
| Monday | Tuesday | Wednesday | Thursday | Friday |
|
14:30-15:20 Lecture
CSE2 G01 Q-Learning (continued)
23:59 A4 (Game-Playing Agents) due
|
14:30-15:20 Lecture
CSE2 G01 Joint Probability Distributions |
14:30-15:20 Lecture
CSE2 G01 Bayes Nets |
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14:30-15:20 Lecture
CSE2 G01 Introducing a Markov Decision Process for Towers of Hanoi
23:59 A5 (Exercises II) due
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14:30-15:20 Lecture
CSE2 G01 D-Separation (Reasoning about Factored Prob. Distributions) |
14:30-15:20 Lecture
CSE2 G01 Markov Models (a Special Factoring Structure for BNs) |
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14:30-15:20 Midterm 2 exam
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14:30-15:20 Lecture
CSE2 G01 Hidden Markov Models and the Viterbi Algorithm |
14:30-15:20 Lecture
CSE2 G01 Perceptrons
23:59 A6 (Implementing Reinf. Learning) due
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Memorial Day
|
14:30-15:20 Lecture
CSE2 G01 Multiclass Perceptrons; Ethics I: The Asimov Laws, Trolley Problems |
14:30-15:20 Lecture
CSE2 G01 NN Architectures, Backpropagation, Word Embeddings |
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| June | ||||
|---|---|---|---|---|
| Monday | Tuesday | Wednesday | Thursday | Friday |
|
14:30-15:20 Lecture
CSE2 G01 Large Language Models, Self-Attention, Transformers.
23:59 A7 (Exercises III) due
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14:30-15:20 Lecture
CSE2 G01 Agent Presentations. |
14:30-15:20 Lecture
CSE2 G01 The Future of AI: Opportunities and Challenges; Course Wrap-up and Comments on the Final Exam |
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14:30-16:20 Final exam
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