The course
- Instructor:
Ke Tang (唐珂) - TA:
Yao Zhao (赵耀) - Semester:
2024 Fall - Textbook:
Artificial Intelligence: A Modern Approach
| Week | Theory | Lab | Content |
|---|---|---|---|
| #1 | Intro & Search Algorithm | Lab1 & Practice1 | Numpy tutorial |
| #2 | Simulated Annealing & Evolutionary Algorithm | Practice2 | A* Search |
| #3 | Alpha-Beta Search | Project1 tutorial | Heuristic Search |
| #4 | Machine Learning Intro | Practice3 | Simulated Annealing |
| #5 | Supervised Learning | Practice4 | CSP |
| #6 | Performance Evaluation | Practice5 | Adversairal Search |
| #7 | Unsupervised Learning | Lab6 & Practice6 | Credit Card Fraud Detection |
| #8 | Recommender System | Practice7 | SVM |
| #9 | Automated Machine Learning | Lab9 & Practice8 | Quiz |
| #10 | Logic Agents | Lab10 & Practice9 | K-Means |
| #11 | Logic Agents cont. | Practice10 | LLE vesus PCA |
| #12 | First-Order Logic | Practice11 | Matrix Factorization |
| #13 | First-Order Logic cont. | Project3 tutorial | KGRS |
| #14 | Representing and Inference with Uncertainty | Review | |
| #15 | Knowledge graph | Review |
Three subprojects in total, evaluated by OJ, which are basically
- Project 1 solves NP search problems
- Project 2 introduces machine learning in practice, i.e., model training and tuning
- Project 3 tunes parameters for nerual networks