Schedule
This schedule is subject to change as the semester progresses, but it will be kept up to date. Slides are linked from the lecture title. They will be made available on the day of the lecture.
| wk | Date | Topic | Readings & Milestones |
|---|---|---|---|
| 1 | Tue, Sep 1 | Introduction: Course Overview | no labs this week |
| 1 | Thu, Sep 3 | Search: Graph Search | P&M §3.1–3.4 no labs this week |
| 2 | Thu, Sep 10 | Search: Heuristic Search 1 | P&M §3.6 Assignment 1 release |
| 3 | Tue, Sep 15 | Search: Heuristic Search 2 | P&M §3.7–3.8 Add/drop deadline |
| 3 | Thu, Sep 17 | Uncertainty: Probability Theory | P&M §8.1 |
| 4 | Tue, Sep 22 | Quiz 1 | |
| 4 | Thu, Sep 24 | Uncertainty: Conditional Independence | P&M §8.2 |
| 5 | Tue, Sep 29 | Uncertainty: Belief Networks | P&M §8.3 |
| 5 | Thu, Oct 1 | Uncertainty: Inference in Belief Networks | P&M §8.4 Assignment 2 released |
| 6 | Tue, Oct 6 | Supervised Learning: Introduction & Framework | P&M §7.1–7.2 |
| 6 | Thu, Oct 8 | Supervised Learning: Calculus Refresher | P §B.3–B.3.4, §B.5 |
| 7 | Tue, Oct 13 | Supervised Learning: Linear Models & Overfitting | P&M §7.3-7.4 |
| 7 | Thu, Oct 15 | Supervised Learning: Bayesian Inference | P&M §10.4, §8.6 |
| 8 | Tue, Oct 20 | Quiz 2 | |
| 8 | Thu, Oct 22 | Deep Learning: Neural Networks | P §3.1–3.6 |
| 9 | Tue, Oct 27 | Deep Learning: Training Neural Networks | P §7.1–7.4.1 |
| 9 | Thu, Oct 29 | Deep Learning: Image Data | P §10.1–10.4.1, §10.5 Assignment 3 released |
| 10 | Tue, Nov 3 | Deep Learning: Sequence Data | P §12.1–12.2, §12.4, §12.6 |
| 10 | Thu, Nov 5 | Reinforcement Learning: Markov Decision Processes | S&B §3.0–3.5 |
| Tue, Nov 10 | reading week, no class | ||
| Thu, Nov 12 | reading week, no class | ||
| 11 | Tue, Nov 17 | Quiz 3 | |
| 11 | Thu, Nov 19 | Reinforcement Learning: Optimality and Dynamic Programming | S&B §3.6, §4.0–4.4 Assignment 4 released |
| 12 | Tue, Nov 24 | Reinforcement Learning: Monte Carlo Prediction & Control | S&B §5.0–5.5, §5.7 |
| 12 | Thu, Nov 26 | Reinforcement Learning: TD-Learning Prediction & Control | S&B §6.0–6.5 |
| 13 | Tue, Dec 1 | Quiz 4 | Withdrawal deadline |
| 13 | Thu, Dec 3 | Reinforcement Learning: Function Approximation & Policy Gradient Methods | S&B §9.0–9.5.4, §13.0–13.3 |
| 14 | Tue, Dec 8 | Multiagent Systems: Game Theory for Single Interactions | S&LB §3.0–3.3.2 |
| TBA | Final exam |