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| DESCRIPTION | This course provides guidance to undergraduate students of the AI major for their academic path and future. This course is mostly introductory and aims to inspire UG students for their academic path development and growth of maturity during their UG study. Activities may include seminars, workshops, advising and sharing sessions, interaction with faculty and teaching staff, and discussion with student peers or alumni. Graded P or F. |
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| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6363) | 01-SEP-2025 - 05-SEP-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | DAI, Enyan | 155 | 150 | 5 | 0 | The class will be delivered by the following instructors as below. W1-Enyan Dai W2-Bingzhuo Zhong W3-Xin Wang W4-Sihong Xie W5-Menglin Yang W6-Yingcong Chen W7-Junwei Liang W8-Changhao Chen W9-Zeke Xie W10-Yutao Yue W11-Li LIU W12-Xuming Hu W13-Apostolos Rikos |
| 08-SEP-2025 - 12-SEP-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | ZHONG, Bingzhuo | ||||||
| 15-SEP-2025 - 19-SEP-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | WANG, Xin | ||||||
| 22-SEP-2025 - 26-SEP-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | XIE, Sihong | ||||||
| 29-SEP-2025 - 11-OCT-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | YANG, Menglin | ||||||
| 13-OCT-2025 - 17-OCT-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | CHEN, Yingcong | ||||||
| 20-OCT-2025 - 24-OCT-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | LIANG, Junwei | ||||||
| 27-OCT-2025 - 31-OCT-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | CHEN, Changhao | ||||||
| 03-NOV-2025 - 07-NOV-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | XIE, Zeke | ||||||
| 10-NOV-2025 - 14-NOV-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | YUE, Yutao | ||||||
| 17-NOV-2025 - 21-NOV-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | LIU, Li | ||||||
| 24-NOV-2025 - 28-NOV-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | HU, Xuming | ||||||
| 01-DEC-2025 - 05-DEC-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | RIKOS, APOSTOLOS |
| DESCRIPTION | This introductory course surveys the explosive area of AI ethics and illuminates relevant AI concepts with no prior background needed. Key topics include Fake News Bots; AI Driven Social Media Displacing Traditional Journalism; drone Warfare; Elimination of Traditional Jobs; Privacy-violating Advertising; Monopolistic Network Effects; Biased AI Decision/Recognition Algorithms; Deepfakes; Autonomous Vehicles; Automated Hedge Fund Trading, etc. Through the course, students will be able to understand how human civilization will survive amid the rise of AI, what are the new rules in the new era, how to preserve ethics when facing the threats of extinction and what are engineers’ and entrepreneurs’ ethical responsibilities. |
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| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6366) | Fr 09:00AM - 11:50AM | Rm 149, E1 | HU, Xuming | 50 | 49 | 1 | 0 | |
| L02 (6367) | Fr 01:30PM - 04:20PM | Rm 149, E1 | HU, Xuming | 50 | 50 | 0 | 0 |
| VECTOR | [3-0-0:3] |
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| DESCRIPTION | This course offers an in-depth exploration of Natural Language Processing (NLP), emphasizing transformative neural network architectures like RNNs and transformers. Students will engage with core NLP tasks such as language modeling and machine translation, and examine the impacts of recent innovations like Large Language Models. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6006) | Th 01:30PM - 04:20PM | Rm 202, W4 | HU, Xuming | 40 | 40 | 0 | 0 |