| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
| 培養具備人工智慧專業知識與應用能力兼備之數據分析人才。 |
|
|
| topic Discussion / Production |
| Networking / Distance Education |
| Exercises |
| Discussion |
| Other |
| Lecturing |
|
| Written Presentation |
| Attendance |
| Oral Presentation |
| Assignment |
| Quiz |
| Internship |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Python language and data science introduction
|
| Week 2 |
Regression introduction
|
| Week 3 |
Simple linear regression |
| Week 4 |
Model adequacy checking |
| Week 5 |
Transformations and weighting to correct model inadequacies Diagnostics for leverage and influence |
| Week 6 |
Transformations and weighting to correct model inadequacies Diagnostics for leverage and influence |
| Week 7 |
Polynomial regression models |
| Week 8 |
Polynomial regression models |
| Week 9 |
Indicator variables |
| Week 10 |
Indicator variables |
| Week 11 |
Multicollinearity
|
| Week 12 |
Multicollinearity
|
| Week 13 |
Variable selection and model building |
| Week 14 |
Variable selection and model building |
| Week 15 |
Validation of regression models |
| Week 16 |
Final exam or report |
self-directed
learning |
03.Preparing presentations or reports related to industry and academia.
|
|
| Evaluation |
Midterm Examination 20%
Final examination (or presentation) 20%
Class participation, Quizzes, homework, and others 60%
|
| Textbook & other References |
「Introduction to Linear Regression Analysis, 5th Edition」，by Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining
「Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow 2/e」，by Aurélien Géron, 2019
|
| Teaching Aids & Teacher's Website |
| https://www.youtube.com/channel/UCSivAooQ-OTLATS1dTT3DZw |
| Office Hours |
| Appointment |
| Sustainable Development Goals, SDGs(Link URL) |
| include experience courses：N |
|