Summer 2018 Syllabus
This syllabus is subject to change! Note that unreleased project out and due dates are just guesses and will likely change somewhat.
| Day | Topic | Optional Reading | Slides |
Notes* |
Assignment | Due |
| Mon 6/18 | Introduction to AI | Ch. 1, Ch. 2 |
Math Self-Diagnostic P0: Tutorial |
(ungraded) |
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| Tues 6/19 | Agents and Search | Ch. 3.1-4 | ||||
| Wed 6/20 | A* Search and Heuristics | Ch. 3.5-6 |
HW1 P1: Search |
Su 6/24 11:59pm T 6/26 11:59pm |
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| Thu 6/21 | Constraint Satisfaction Problems |
Ch. 6.1 Ch. 6.2-5, |
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| Mon 6/25 | Game Trees: Minimax | Ch. 5.1-3 | ||||
| Tues 6/26 | Game Trees: Expectimax; Utilities | Ch. 5.4-5 |
HW 2 + 3 HW4 P2: Multi-Agent Search |
Su 7/1 11:59PM Tu 7/3 11:59PM Th 7/5 11:59PM |
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| Wed 6/27 | Markov Decision Processes |
Ch. 16.1-3, |
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| Thurs 6/28 | Markov Decision Processes II | Ch. 17.3 | ||||
| Mon 7/2 |
Reinforcement Learning |
Ch. 21.1-3 |
HW5 P3: Reinforcement Learning |
Su 7/8 11:59pm Tu 7/10 11:59pm |
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| Tues 7/3 |
Reinforcement Learning II |
Ch. 21.4-5 | ||||
| Wed 7/4 | Holiday | |||||
| Thurs 7/5 | Holiday | |||||
| Mon 7/9 | RL/Probability/Bayes | Ch. 13.1-5 (2e: Ch. 13.1-6) | ||||
| Tues 7/10 | RL/Bayes Nets | Ch. 14.1-2,4 |
HW6 |
Su 7/15 11:59pm |
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| Wed 7/11 | Bayes' Nets: Representation/Independence | Ch. 14.3, Jordan 2.1 | ||||
| Thurs 7/12 | Bayes' Nets: Independence/Inference | Ch. 14.4-5 | ||||
| Mon 7/16 | Midterm (5-8pm) | P4: Bayes Nets | TBD | |||
| Tues 7/17 |
Bayes' Nets: Inference/Sampling |
Ch. 15.1-3, 6 |
Lecture Note 7 (draft) | |||
| Wed 7/18 |
Bayes' Nets: Sampling/Decision Networks |
Ch. 15.2-5 |
Lecture Note 8 (draft) Exam Prep Solutions |
HW7 | TBD | |
| Thurs 7/19 |
Decision Networks/VPI |
Ch. 15.2,6 | Lecture Note 9 (draft) | |||
| Mon 7/23 | Markov Models, HMMs |
HW8 P5: Ghostbusters |
TBD Sat 7/28 |
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| Tues 7/24 |
HMMs/Particle Filtering |
Ch. 15.2,6 |
slides continued from yesterday |
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| Wed 7/25 | ML:Naive Bayes. | Ch. 15.2,6 | ||||
| Thurs 7/26 |
ML: Perceptrons |
Ch. 15.2,6 | Lecture Note 10 (draft) | P6: Machine Learning | Mon 8/6 | |
| Mon 7/30 | ML: Deep Learning | Ch. 15.2,6 |
Exam Prep Solutions |
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| Tues 7/31 | ML: Deep Learning & AI Applications | |||||
| Wed 8/1 | Advanced Topics & Final Contest |
Exam Prep 10 Exam Prep Solutions |
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| Wed 8/8 | FINAL EXAM (5:00pm-8:00pm) | Practice final (submit by 11:59p 8/4 on Gradescope for 1 pt EC on the final) | ||||
* Note drafts may undergo changes in coverage (which sections are optional) and minor changes in content.