| Course Title | Course Information |
|
Applying large language models in cybersecurity systems Course Difficulty: ★★★★★★ |
1.University & Instructor: National Taiwan University of Science and Technology, Prof. Jyun-Ruei Lin (TMU assisting teacher: Prof. Yung-Chun, Chang) |
| 2.Credits: 3 | |
| 3.Course type: Mirror course, Prof. Jyun-Ruei Lin is in charge of all assessments and evaluation | |
| 4.Course level: Graduate | |
| 5.Langauge of instruction: English | |
| 6. Course capacity: 100 students | |
| 7. Online class time: Monday 9:20–12:20. The first hour is for online self-study; 10:20–12:20 is the live practice session. Students from partner universities may attend asynchronously: first complete the one-hour online self-study on their own, and then participate in a two-hour online practice session during one of the fixed TA time slots (to be announced later, available Monday to Friday). This practice session is a required component, and all students must participate. |
|
| 8. Asynchronous learning: Accepted | |
| 9.Corresponding prorgram: Applied Artificial Intelligence Exploration Program(Applied AI Course) | |
|
Deep Learning Course Difficulty: ★★★★★★★★★★ |
1.University & Instructor: National Yang Ming Chiao Tung University, Prof. Wen-Hsiao Peng,Yong-Sheng Chen,Ping-Chun Hsieh (TMU assisting teacher: Prof. Tzu-Hao, Chang & Prof. Yu-Wei, Wu) |
| 2.Credits: 3 | |
| 3.Course type: Mirror course, Prof. Wen-Hsiao Peng,Yong-Sheng Chen, and Ping-Chun Hsieh are in charge of all assessments and evaluation | |
| 4.Course level: Graduate (Open to student in senior) | |
| 5.Langauge of instruction: English | |
| 6. Course capacity: 10 students | |
| 7.Online Class Time: Thursday 12:20-15:10, with synchronous final exam on June 4th, 12:20-15:10 in Computer and Language Classroom, Xing-Chun Building, Xinyi Campus | |
| 8. Asynchronous learning: Accepted | |
| 9. Course Requirements: You must have access to GPU equipped with at least 6GB of memory. | |
| 10.Corresponding prorgram: Artificial Intelligence for Computer Vision and Imaging Technology Program(Deep learning) |