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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 (6277) | 02-SEP-2024 - 06-DEC-2024 Fr 03:00PM - 03:50PM | Rm 101, W1 | CHEN, Lei CHEN, Yingcong DAI, Enyan HU, Xuming LIANG, Junwei LIU, Li RIKOS, APOSTOLOS SUN, Ying WANG, Hao WANG, Xin XIE, Sihong XIONG, Hui YUE, Yutao ZHONG, Bingzhuo | 136 | 85 | 51 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course will explore the basic knowledge and the latest advances of Deep Learning based methods in the medical field, with special attention to challenges and opportunities for Medical AI. This course will provide students the opportunity to learn skills to train/learn/develop Deep Learning models from medical data with several case studies. It covers knowledge on Digital Medical Imaging, supervised learning, semi-supervised learning, and unsupervised learning related with Medical AI research. Importantly, some hot topics on "AI for Medical" will be introduced. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6096) | 02-SEP-2024 - 06-DEC-2024 Fr 09:00AM - 11:50AM | Rm 222, W1 | LIU, Li | 40 | 40 | 0 | 0 |