| Topic | Week | Meeting Time |
| Introduction and Overview | (Week 1) | 7-11 |
| Bayesian Network Fundamentals | (Week 1) |
| Template Models | (Week 1) |
| ML-class Octave Tutorial | (Week 1, Optional) |
| Structured CPDs | (Week 2) | |
| Markov Network Fundamentals | (Week 2) | |
| Representation Wrapup: Knowledge Engineering | (Week 3) | |
| Inference: Belief Propagation, Part 1 | (Week 3) | |
| Inference: Belief Propagation, Part 2 | (Week 4) | |
| Inference: MAP Estimation, Part 1 | (Week 4) | |
| Inference: MAP Estimation, Part 2 | (Week 5) | |
| Inference: Sampling Methods | (Week 5) | |
| Inference: Temporal Models and Wrap-up | (Week 6) | |
| Decision Theory | (Week 6) | |
| ML-class Revision | (Week 6, Optional) | |
| Learning: Overview | (Week 6) | |
| Learning: Parameter Estimation in BNs | (Week 7) | |
| Learning: Parameter Estimation in MNs | (Week 7) | |
| Structure Learning | (Week 8) | |
| Learning With Incomplete Data | (Week 9) | |
| Learning: Wrapup | (Week 9) | |
| Summary | (Week 9) | |