Course Information
Instructor
Dr. Tao Huang
Email
Office Hours
Monday 16:00-19:00
Class Time
Monday 12:55–15:40
Location
东上院 205
Language
English
Course Goals
- Understand what is AI and core AI principles.
- Master foundational ML and deep learning methods.
- Gain insight into modern AI paradigms: large models, generative models, RL, …
- Develop the ability to analyze, design, and evaluate AI systems.
Quick Links
Textbooks / References
- R&N Russell & Norvig, Artificial Intelligence: A Modern Approach
- DL Goodfellow et al., Deep Learning
- Papers Weekly reading links will be posted in schedule
Announcements
Welcome! This page will be updated weekly with slides, readings, and assignments.
Last updated:
Assessment & Coursework
Homework
40%
Project
40%
Presentation
10%
Participation
10%
Coursework
- Coursework 1: Route Planning with Search Algorithms (canvas) Due: 2026-03-16, 23:59 CST
Schedule (16 Weeks)
| Week | Date | Topics | Slides | Extra Materials | Coursework |
|---|---|---|---|---|---|
| 1 | 2026-03-02 |
Introduction to AI 1. What is AI? 2. History of AI 3. Modern AI Landscape 4. Weak AI vs. AGI |
L1 | — | — |
| 2 | 2026-03-09 |
Search Algorithms 1. Uninformed Search 2. Informed Search 3. Heuristic Search & A* |
L2 • L3 • L4 | — |
Coursework 1 Search Algorithms (canvas) Due: 2026-03-16, 23:59 CST |
| 3 | 2026-03-16 |
Beyond Basic Search 1. Local Search 2. Adversarial Search 3. Constraint Satisfaction |
L5 • L6 • L7 | — | — |