 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | BSBE 6000B |
| DESCRIPTION | This course covers the basic knowledge of nervous system, and the clinical manifestation, anatomy, physiology, pathophysiology, diagnosis, and treatment of common nervous system diseases, with focus on the underlying molecular mechanism of the diseases and treatments. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6130) | We 01:30PM - 04:20PM | Rm 202, E4 | XIA, Jun | 15 | 0 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | In this course, theories, models, algorithms of deep learning and their application to data science will be introduced. The basics of machine learning will be reviewed at first, then some classical deep learning models will be discussed, including AlexNet, LeNet, CNN, RNN, LSTM, and Bert. In addition, some advanced deep learning techniques will also be studied, such as reinforcement learning, transfer learning and graph neural networks. Finally, end-to-end solutions to apply these techniques in data science applications will be discussed, including data preparation, data enhancement, data sampling and optimizing training and inference processes. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6234) | Tu 12:00PM - 02:50PM | Rm 102, E4 | XIA, Jun | 120 Quota/Enrol/Avail For PhD (DSA) students only: 50/0/50 | 0 | 120 | 0 |