物理學和AI
AI for Physicists
| 節 | 週二 |
|---|---|
7 15:30–16:20 | 物理學和AI SC159 2 節連堂 |
8 16:30–17:20 |
* 根據陽明交大上課時間表所列
Machine learning and AI are quickly transforming society and are revolutionising how we do science. Throughout their development, physicists have been early adopters, expert users, and researchers who have contributed to many of the most important aspects of how these methods work and are used today. In this course, we will present and practice machine learning methods and concepts, with an eye toward both broad theoretical understanding and practical applications. Through lectures, practice sessions, and homework problems, we will learn the theory and methods of machine learning and develop basic skills in applying this technology to solve physics problems. Topics of the course will include: - Data science basics - Supervised and unsupervised machine learning - Deep neural networks - Generative AI - Quantum machine learning - Applications in astrophysics - Applications in high-energy physics
50% exam and 50% computational projects. (To be confirmed in class)
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction and course format. |
| 第 2 週 | Supervised Machine Learning |
| 第 3 週 | Unsupervised Machine Learning |
| 第 4 週 | Deep Neural Networks |
| 第 5 週 | Backpropagation |
| 第 6 週 | Convolutional Neural Networks |
| 第 7 週 | Autoencoders |
| 第 8 週 | Generative AI |
| 第 9 週 | Generative AI |
| 第 10 週 | AI in high performance computing |
| 第 11 週 | Quantum Machine Learning |
| 第 12 週 | Applications in Astroparticle Physics |
| 第 13 週 | Applications in Astroparticle Physics |
| 第 14 週 | Applications in High-Energy Physics |
| 第 15 週 | Applications in High-Energy Physics |
| 第 16 週 | Applications outside of Physics |
- 地點
- SC457, SC406
- 時間
- T10
- 聯絡方式
- afrancis@nycu.edu.tw, sitam@nycu.edu.tw