| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
| 矩陣計算是研讀AI、數據科學的基本工具︒本課程是研讀矩陣計算的入門，除了數據模擬的基本概念外，本課程能提供學生實用性的知識，當與實務數據結合使用時，可以解決實際的問題︒ |
| 3.Professional Knowledge in Data Science |
| 4.Mathematical and Statistical Software Skills |
|
|
| topic Discussion / Production |
| Exercises |
| Discussion |
| Lecturing |
|
| Written Presentation |
| Attendance |
| Assignment |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
矩陣理論分析 |
| Week 2 |
矩陣理論分析 |
| Week 3 |
SVD處理影像作壓縮 |
| Week 4 |
矩陣正交性應用：最佳化計算 |
| Week 5 |
矩陣正交性應用：最佳化計算 |
| Week 6 |
矩陣正交性應用：最佳化計算 |
| Week 7 |
Tensor Decomposition |
| Week 8 |
Tensor Decomposition |
| Week 9 |
期中作業報告 |
| Week 10 |
Clustering and NMF |
| Week 11 |
Clustering and NMF |
| Week 12 |
Classification of Handwritten Digits |
| Week 13 |
Classification of Handwritten Digits |
| Week 14 |
PCA & MDS |
| Week 15 |
PCA & MDS |
| Week 16 |
期末報告與複習
|
self-directed
learning |
01.Participation in professional forums, lectures, and corporate sharing sessions related to industry-government-academia-research exchange activities.
02.Viewing multimedia materials related to industry and academia.
03.Preparing presentations or reports related to industry and academia.
06.Participation in field trips and outdoor instructional activities at other NCHU campuses or branches, including experimental forests or test sites.
|
|
| Evaluation |
期中報告(50%)
期末報告(50%) |
| Textbook & other References |
1. Lars Elden, Matrix Methods in Data Mining and Pattern Recognition, SIAM 2007.
2. Golub & Von Loan, Matrix Computations, 3rd Ed. , John Hopkins University, 1996.
3. Yuan Yao, A Mathematical Introduction to Data Science, Bejing University, 2014 |
| Teaching Aids & Teacher's Website |
|
| Office Hours |
| 再另行公告 |
| Sustainable Development Goals, SDGs(Link URL) |
| 07.Affordable and Clean Energy 08.Decent Work and Economic Growth 09.Industry, Innovation and Infrastructure | include experience courses：Y |
|