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Lecture

Section

Lab

Exam

Homework

Office Hour

Other

Holiday

January
Sunday	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday
03	04 14:30-15:20 Lecture online Course introduction Slides	05	06 14:30-15:20 Lecture online Turing Tests, State Spaces Slides	07	08 14:30-15:20 Lecture online Search Algorithms Slides	09
10	11 14:30-15:20 Lecture online Heuristic Search Slides	12	13 14:30-15:20 Lecture online Heuristic Search (cont.)	14	15 14:30-15:20 Lecture online Heuristic Search (cont.) 23:59 A1 (Python Warm-up and AI Intro) due	16
17	18 MLK Day	19 23:59 A2 (Part 1 Early-Bird Bonus) due	20 14:30-15:20 Lecture online Adversarial Search Slides 14:30-15:20 Quizella 1	21	22 14:30-15:20 Lecture online Adversarial Search (Alpha-Beta Pruning); Expectimax Search Alpha-Beta Slides   Expectimax Slides 23:59 A2 (Search Techniques, Parts 1 and 2) due	23
24	25 14:30-15:20 Lecture online Markov Decision Processes Slides	26	27 14:30-15:20 Lecture online Values, Q-Values, Policies Slides	28	29 14:30-15:20 Lecture online Value Iteration 14:30-15:20 Quizella 2	30
31	01 14:30-15:20 Lecture online Q-Learning Slides 23:59 A3 (Adversarial Search) due	02	03 14:30-15:20 Lecture online Q-Learning (continued)	04	05 14:30-15:20 Lecture online Feature-Based Q-Learning Slides	06

February
Sunday	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday
07	08 14:30-15:20 Lecture online Probabilities and Probabilistic Reasoning Slides	09	10 14:30-15:20 Lecture online Joint Distributions Slides	11 23:59 A4 (Written Exercises I) due	12 14:30-15:20 Lecture online Bayes Nets 14:30-15:20 Quizella 3	13
14	15 President's Day	16 23:59 A5 (Reinforcement Learning, Part A) Early Bird due date	17 14:30-15:20 Lecture online Bayes Nets (Cont.) Intro to Perceptrons Slides	18	19 14:30-15:20 Lecture online Multi-Class Perceptrons Slides	20 23:59 A5 (Reinforcement Learning) due
21	22 14:30-15:20 Lecture online Multiclass perceptrons (cont.)	23	24 14:30-15:20 Lecture online D-Separation in Bayes Nets Slides 23:59 A6 (Perceptrons, Part A) Early Bird due date	25	26 14:30-15:20 Lecture online Markov Models Slides 14:30-15:20 Quizella 4	27
28	01 14:30-15:20 Lecture online Hidden Markov Models: The Viterbi Algorithm Slides 23:59 A6 (Perceptrons) due	02	03 14:30-15:20 Lecture online Guest Lecture: Ethics in AI for Health (Emilia Gan) Slides	04	05 14:30-15:20 Lecture online NLP Using Probabilistic Context-Free Grammars Slides	06

March
Sunday	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday
07	08 14:30-15:20 Lecture online Document analysis using the Cosine similarity and Latent Semantic Analysis; The Asimov Laws of Robotics Slides	09	10 14:30-15:20 Lecture online The Future of AI: Opportunities and Challenges Slides 23:59 A7 (Written Exercises II) due	11	12 14:30-15:20 Lecture online AI Opportunities and Challenges 14:30-15:20 Quizella 5	13