Instructor:
- 
											
											Prof. Qi DOUDept. of Computer Science & Engineering 
 Email: qidou@cuhk.edu.hk
 Office: Room 911, 9/F, SHB, CUHK
 Consultation hours: Monday 3pm-5pm
- 
											
											Mr. Kejian Shi (Coordinator)Dept. of Computer Science & Engineering 
 Email: kjshi@cse.cuhk.edu.hk
 Office: Room 121, 10/F, SHB, CUHK
 Consultation hours: Wednesday 2pm-4pm
- 
											
											Ms. Yiyao MaDept. of Computer Science & Engineering 
 Email: yyma23@cse.cuhk.edu.hk
 Office: Room 121, 1/F, SHB, CUHK
 Consultation hours: Wednesday 2pm-4pm
- 
											
											Mr. Jiawei FuDept. of Computer Science & Engineering 
 Email: jwfu@cse.cuhk.edu.hk
 Office: Room 115, 1/F, SHB, CUHK
 Consultation hours: Monday 2pm-4pm
- 
											
											Mr. Qianhan FengDept. of Computer Science & Engineering 
 Email: qhfeng25@cse.cuhk.edu.hk
 Office: Pentecostal Mission Hall Complex Hall Block, IMIXR, CUHK
 Consultation hours: Wednesday 2pm-4pm
- 
											
											Mr. Zelong Tan (ESTR 3108)Dept. of Computer Science & Engineering 
 Email: zltan25@cse.cuhk.edu.hk
 Office: Room 121, 1/F, SHB, CUHK
 Consultation hours: Monday 2pm-4pm
TAs:
Useful links
News
- Welcome to CSCI3230 2025-2026 (Term 1)!
- First lecture will start on 2 Sep 14:30 - 16:15 Science Centre L1!
Course information
 This course aims to widely introduce the basic knowledge, classic algorithms, neural networks, searching, cutting-edge technical concepts and models in artificial intelligence. Topics to be covered include introduction to artificial intelligence, basics of key concepts, linear regression, logistic regression, clustering, SVM, neural network basics and deep learning, advanced AI models for big data, and latest applications of AI in multiple domains. On the theoretical side, students are expected to learn the relevant knowledge and mathematics in artificial intelligence from lectures and tutorials. On the practical side, students are given written assignments and programming assignments to get hands-on experience to apply the learned knowledge to solve problems. The field of artificial intelligence is advancing rapidly. Through this course, students will not only learn solid fundamentals of AI, but also know the latest news about AI on the globe.
									
									
									
Class time
Lectures:
										Tuesday                                 	14:30pm - 16:15pm          Science Centre L1
										Thursday (ESTR 3108)         	11:30am - 12:15pm            YIA LT3 
										Thursday                                	12:30pm - 1:15pm                YIA LT3 
									
Tutorials:
								   		(T01) Wednesday                 	13:30pm - 14:15pm          Science Centre L5 
										(T02) Wednesday                 	17:30pm - 18:15pm          Science Centre L5 
										(T03) Thursday                     	9:30am - 10:15am           ERB 803 
										(T04) Thursday                     	10:30am - 11:15am         Science Centre L3 
								    
Piazza
For discussions and questions: go to here
Assessments:
 CSCI3230: 
										Assignments: 
										               	
										60% 
										Final examination:        
										35% 
										Class participation:
										        
										5%
                                    
 ESTR3108: 
                                    	Assignments: 
										               	
										40% 
										Article reading:               
										20% 
										Final examination:        
										35% 
										Class participation:
										        
										5%
									
									
Tentative class schedule
| Week | Time | Topic | Instructor |     TA | ||||
|---|---|---|---|---|---|---|---|---|
| 1 | Sep 2,4 | Introduction | Prof. Dou | - | ||||
| 2 | Sep 9,11 | Linear Regression | Prof. Dou | Zelong Tan | ||||
| 3 | Sep 16,18 | Logistic Regression | Prof. Dou | Zelong Tan | ||||
| 4 | Sep 23,25 | Support Vector Machine | Prof. Dou | Yiyao Ma | ||||
| 5 | Sep 30, Oct 2 | Clustering Algorithms | Prof. Dou | Yiyao Ma | ||||
| 6 | Oct 9 | Neural Network Basics | Prof. Dou | Yiyao Ma | ||||
| 7 | Oct 14,16 | Convolutional Neural Networks | Prof. Dou | Qianhan Feng | ||||
| 8 | Oct 21,23 | Transformers | Prof. Dou | Qianhan Feng | ||||
| 9 | Oct 28,30 | Uninformed Search | Prof. Dou | Jiawei Fu | ||||
| 10 | Nov 4,6 | Informed Search | Prof. Dou | Jiawei Fu | ||||
| 11 | Nov 11, 13 | AI Applications in Healthcare | Prof. Dou | Kejian Shi | ||||
| 12 | Nov 18,20 | AI Applications in HCI | Prof. Dou | Kejian Shi | ||||
| 13 | Nov 25,27 | AI Applications in Robotics | Prof. Dou | Kejian Shi | ||||
Useful materials and links
 
										-  The Elements of Statistical Learning  by Trevor Hastie, Robert Tibshirani, Jerome Friedman 
										
										-  Deep learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville. 
										-  Artificial Intelligence: A Modern Approach, 4th Global ed.  by Stuart Russell, Peter Norvig 
										
										
										
										-  Google AI Blog  
										-  MIT Technology Review, Artificial Intelligence.