Fall 2017 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 and Notes | Video | Assignment | Due |
| Th 8/24 | Introduction to AI | Ch. 1, Ch. 2 |
video | Math Self-Diagnostic P0: Tutorial |
(ungraded) Th 8/31 11:59pm |
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| Tu 8/29 | Agents and Search | Ch. 3.1-4 | video |
Tu 9/5 11:59pm |
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| Th 8/31 | A* Search and Heuristics | Ch. 3.5-6 |
lecture notes 1 (same as 8/29) |
video | P1: Search Contest 1: Search |
F 9/8 11:59pm Su 9/24 |
| Tu 9/5 | Constraint Satisfaction Problems | Ch. 6.1 | video |
M 9/11 11:59pm |
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| Th 9/7 | CSPs II | Ch. 6.2-5, Ch. 4.1 |
video | |||
| Tu 9/12 | Game Trees: Minimax | Ch. 5.1-3 | video |
W 9/20 11:59pm |
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| Th 9/14 | Game Trees: Expectimax; Utilities | Ch. 5.4-5 | video | P2: Multi-Agent Search |
F 9/22 11:59pm M 9/25 11:59pm |
|
| Tu 9/19 | Markov Decision Processes |
Ch. 16.1-3, |
video | (section 4 / exam-prep 3) | ||
| Th 9/21 | Markov Decision Processes II | Ch. 17.3 | video | HW4 | W 9/27 11:59pm | |
| Tu 9/26 | Reinforcement Learning | Ch. 21.1-3 | video | (section 5 / exam-prep 4) | ||
| Th 9/28 | Reinforcement Learning II | Ch. 21.4-5 | video |
W 10/4 11:59pm Tu 10/10 11:59pm |
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| Mo 10/2 |
Midterm logistics |
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| Th 10/5 | Probability |
Ch. 13.1-5 (2e: Ch. 13.1-6) | video | (section 6 / exam-prep 5) | ||
| Tu 10/10 | Markov Chains/Conditional Probability. | Ch. 14.1-2,4 | video |
Contest 2 (see Piazza and course) |
W 10/18 11:59pm T 10/24 11:59pm Sun 10/29 11:59pm |
|
| Th 10/12 | Bayes' Nets: Representation/Independence | Ch. 14.3, Jordan 2.1 | video | |||
| Tu 10/17 | Bayes' Nets: Independence/Inference | Ch. 14.4-5 | video | HW7 | F 10/27 11:59pm | |
| Th 10/19 | Bayes' Nets: Inference/Sampling | Ch. 15.1-3, 6 | 6up, handout, slides | video | ||
| Tu 10/24 | Bayes' Nets: Decision Networks | Ch. 15.2-5 | video | HW8 | F 11/03 11:59pm | |
| Th 10/26 | HMMs/Particle Filtering | Ch. 15.2,6 | video | |||
| Tu 10/31 | ML:Naive Bayes. | Ch. 15.2,6 |
exam prep 8 / solutionsdiscussion 10 / solutions |
P5: Ghostbusters | T 11/14 11:59pm | |
| Th 11/2 | ML: Perceptrons | Ch. 15.2,6 | video | HW9 | Th 11/30 11:59pm | |
| Tu 11/7 | ML: Deep Learning I | Ch. 15.2,6 | video | |||
| Th 11/9 | MIDTERM (xx-xx) | |||||
| Tu 11/14 | ML: Deep Learning II | video | F 12/1, 11:59pm | |||
| Th 11/16 | Guest Lecture: Robotics (Pieter Abbeel) | slides | video | P6: Machine Learning | see piazza | |
| Tu 11/21 |
Guest Lecture: Speech Recognition (Adam Janin) |
slides (pdf), pptx | video | |||
| Th 11/23 | Thanksgiving break (No lecture) | |||||
| Tu 11/28 | Guest Lecture: Computer Vision (Alyosha Efros) / Final Contest |
(section 13) |
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| Th 11/30 | A little theory, and done. | 6up, handout, slides | video | |||
| Wed 12/13 | FINAL EXAM (11:30am-2:30pm) | |||||