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 2 | Introduction: Course Overview | no labs this week |
1 | Thu, Sep 4 | Search: Graph Search | P&M §3.1–3.4 no labs this week |
2 | Tue, Sep 9 | Search: Uninformed Search | P&M §3.5 |
2 | Thu, Sep 11 | Search: Heuristic Search 1 | P&M §3.6 Assignment 1 released Add/drop deadline: Sep 15 |
3 | Tue, Sep 16 | Search: Heuristic Search 2 | P&M §3.7–3.8 |
3 | Thu, Sep 18 | Uncertainty: Probability Theory | P&M §8.1 |
4 | Tue, Sep 23 | Uncertainty: Conditional Independence | P&M §8.2 |
4 | Thu, Sep 25 | Uncertainty: Belief Networks | P&M §8.3 Assignment 1 due |
5 | Tue, Sep 30 | National Day for Truth and Reconciliation, no class | |
5 | Thu, Oct 2 | Uncertainty: Inference in Belief Networks | P&M §8.4 Assignment 2 released |
6 | Tue, Oct 7 | Supervised Learning: Introduction & Framework | P&M §7.1–7.2 |
6 | Thu, Oct 9 | Supervised Learning: Calculus Refresher | P §B.3–B.3.4, §B.5 |
7 | Tue, Oct 14 | Supervised Learning: Linear Models | P&M §7.3 |
7 | Thu, Oct 16 | Supervised Learning: Overfitting | P&M §7.4 |
8 | Tue, Oct 21 | Supervised Learning: Bayesian Inference | P&M §10.4, §8.6 Assignment 2 due |
8 | Thu, Oct 23 | MIDTERM | |
9 | Tue, Oct 28 | Deep Learning: Neural Networks | P §3.1–3.6 |
9 | Thu, Oct 30 | Deep Learning: Training Neural Networks | P §7.1–7.4.1 Assignment 3 released |
10 | Tue, Nov 4 | Deep Learning: Image Data | P §10.1–10.4.1, §10.5 |
10 | Thu, Nov 6 | Deep Learning: Sequence Data | P §12.1–12.2, §12.4, §12.6 |
Tue, Nov 11 | reading week, no class | ||
Thu, Nov 13 | reading week, no class | ||
11 | Tue, Nov 18 | Reinforcement Learning: Markov Decision Processes | S&B §3.0–3.5 |
11 | Thu, Nov 20 | Reinforcement Learning: Optimality and Dynamic Programming | S&B §3.6, §4.0–4.4 Assignment 3 due Assignment 4 released |
12 | Tue, Nov 25 | Reinforcement Learning: Monte Carlo Prediction & Control | S&B §5.0–5.5, §5.7 |
12 | Thu, Nov 27 | Reinforcement Learning: TD-Learning Prediction & Control | S&B §6.0–6.5 |
13 | Tue, Dec 2 | Reinforcement Learning: Function Approximation & Policy Gradient Methods | S&B §9.0–9.5.4, §13.0–13.3 Withdrawal deadline: Dec 2 |
13 | Thu, Dec 4 | TBD | Assignment 4 due |
Tue, Dec 16 1:00pm |
FINAL EXAM (tentative date) |