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, Jan 9 | Introduction: Course Overview | no labs this week |
| 1 | Thu, Jan 11 | Search: Graph Search | P&M §3.1–3.4 no labs this week |
| 2 | Tue, Jan 16 | Search: Uninformed Search | P&M §3.5 |
| 2 | Thu, Jan 18 | Search: Heuristic Search 1 | P&M §3.6 Assignment 1 released Add/drop deadline: Jan 19 |
| 3 | Tue, Jan 23 | Search: Heuristic Search 2 | P&M §3.7–3.8 |
| 3 | Thu, Jan 25 | Uncertainty: Probability Theory | P&M §8.1 |
| 4 | Tue, Jan 30 | Uncertainty: Conditional Independence | P&M §8.2 |
| 4 | Thu, Feb 1 | Uncertainty: Belief Networks | P&M §8.3 Assignment 1 due |
| 5 | Tue, Feb 6 | Uncertainty: Inference in Belief Networks | P&M §8.4 Assignment 2 released |
| 5 | Thu, Feb 8 | Supervised Learning: Introduction & Framework | P&M §7.1–7.2 |
| 6 | Tue, Feb 13 | Supervised Learning: Calculus Refresher | P §B.3–B.3.4, §B.5 |
| 6 | Thu, Feb 15 | Supervised Learning: Linear Models | P&M §7.3 |
| Tue, Feb 20 | reading week, no class | ||
| Thu, Feb 22 | reading week, no class | ||
| 7 | Tue, Feb 27 | Supervised Learning: Overfitting | P&M §7.4 |
| 7 | Thu, Feb 29 | Supervised Learning: Bayesian Inference | P&M §10.4, §8.6 Assignment 2 due |
| 8 | Tue, Mar 5 | MIDTERM | |
| 8 | Thu, Mar 7 | Deep Learning: Neural Networks | P §3.1–3.6 |
| 9 | Tue, Mar 12 | Deep Learning: Training Neural Networks | P §7.1–7.4.1 Assignment 3 released |
| 9 | Thu, Mar 14 | Deep Learning: Image Data | P §10.1–10.4.1, §10.5 |
| 10 | Tue, Mar 19 | Deep Learning: Sequence Data | P §12.1–12.2, §12.4, §12.6 |
| 10 | Thu, Mar 21 | Reinforcement Learning: Markov Decision Processes | S&B §3.0–3.5 |
| 11 | Tue, Mar 26 | Reinforcement Learning: Optimality and Dynamic Programming | S&B §3.6, §4.0–4.4 |
| 11 | Wed, Mar 27 | Wednesday, no class | Assignment 3 due |
| 11 | Thu, Mar 28 | Reinforcement Learning: Monte Carlo Prediction & Control | S&B §5.0–5.5, §5.7 Assignment 4 released |
| 12 | Tue, Apr 2 | Reinforcement Learning: TD-Learning Prediction & Control | S&B §6.0–6.5 |
| 12 | Thu, Apr 4 | Reinforcement Learning: Function Approximation & Policy Gradient Methods | S&B §9.0–9.5.4, §13.0–13.3 Withdrawal deadline: Apr 5 |
| 13 | Tue, Apr 9 | Guest lecture: Goal Recognition Design | |
| 13 | Thu, Apr 11 | Multiagent Systems: Game Theory for Single Interactions | S&LB §3.0–3.3.2 Assignment 4 due |
| Tue, Apr 23 9:00am |
FINAL EXAM | ED 2-115 (usual lecture hall) |