Assignments by Lecture
Format: 8 weeks × 3 class meetings = 24 sessions. Each assignment includes exercises from the corresponding AIMA chapter.
| Session | Week | Lecture | Chapter | Title |
|---|---|---|---|---|
| 01 | 1 | 01 | 01 | Introduction |
| 02 | 1 | 02 | 02 | Intelligent Agents |
| 03 | 1 | 03 | 03 | Solving Problems by Searching |
| 04 | 2 | 04 | 04 | Search in Complex Environments |
| 05 | 2 | 05 | 05 | Adversarial Search and Games |
| 06 | 2 | 06 | 06 | Constraint Satisfaction Problems |
| 07 | 3 | 07 | 07 | Logical Agents |
| 08 | 3 | 08 | 08 | First-Order Logic |
| 09 | 3 | 09 | 09 | Inference in First-Order Logic |
| 10 | 4 | 10 | 10 | Knowledge Representation |
| 11 | 4 | 12 | 12 | Quantifying Uncertainty |
| 12 | 4 | 11 | 11 | Automated Planning |
| 13 | 5 | 13 | 13 | Probabilistic Reasoning |
| 14 | 5 | 14 | 14 | Probabilistic Reasoning over Time |
| 15 | 5 | 15 | 15 | Probabilistic Programming |
| 16 | 6 | 16 | 16 | Making Simple Decisions |
| 17 | 6 | 17 | 17 | Making Complex Decisions |
| 18 | 6 | 18 | 18 | Multiagent Decision Making |
| 19 | 7 | 19 | 19 | Learning from Examples |
| 20 | 7 | 20 | 20 | Learning Probabilistic Models |
| 21 | 7 | 21 | 21 | Deep Learning |
| 22 | 8 | 22 | 22 | Reinforcement Learning |
| 23 | 8 | 23 | 23 | Natural Language Processing |
| 24 | 8 | 27 | 27 | Philosophy, Ethics, and Safety of AI |