| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
1. 熟悉Python語法及其內建資料結構；
2. 熟悉Python物件之建立與應用；
3. 了解機器學習與深度學習；
4. 熟悉OpenCV, TensorFlow, Keras等套件。 |
|
|
|
| Assignment |
| Quiz |
| Internship |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Basic Concepts |
| Week 2 |
Input, process, output |
| Week 3 |
Decision Structures and Boolean Logic |
| Week 4 |
Repetition Structures |
| Week 5 |
Functions |
| Week 6 |
Files |
| Week 7 |
Basic Data Structure I |
| Week 8 |
Basic Data Structure II |
| Week 9 |
Classes |
| Week 10 |
Numerical Computing with Python |
| Week 11 |
Midterm Exam |
| Week 12 |
Symbolic Computing with Python |
| Week 13 |
Natural Language Processing |
| Week 14 |
Python for Machine Learning |
| Week 15 |
Tensorflow for Neural Networks |
| Week 16 |
Deep Learning for Text and Sequences
Anomal1y Detection
Final Exam |
self-directed
learning |
|
|
| Evaluation |
| Exams 60%, Projects 40% |
| Textbook & other References |
Starting Out with Python 4/e (Global Edition), Tony Gaddis, Pearson Education, 東華書局
|
| Teaching Aids & Teacher's Website |
| 140.120.7.149/~tcyen |
| Office Hours |
週二08:10~09:00
週四15:10~16:00
|
| Sustainable Development Goals, SDGs(Link URL) |
| include experience courses：N |
|