| 課程大綱 Syllabus |
學生學習目標
Learning Objectives |
單元學習活動
Learning Activities |
學習成效評量
Evaluation |
備註
Notes |
序
No. | 單元主題
Unit topic |
內容綱要
Content summary |
| 1 | Python Programming (1) |
1. Background
2. Variables, expressions, and statements
3. Conditional execution
4. Anaconda, Jupyter Notebook, google colab |
1. Programming background
2. Variables, expressions, and statements
3. Conditional execution
4. Anaconda, Jupyter Notebook, google colab |
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| 2 | Python Programming (2) |
1. Functions
2. Iteration
3. Strings |
1. Functions
2. Iteration
3. Strings |
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| 3 | Python Programming (3) |
1. Files
2. Lists
3. Dictionaries |
1. Files
2. Lists
3. Dictionaries |
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| 4 | Python Programming (4) |
1. Tuples
2. Regular Expressions |
1. Tuples
2. Regular Expressions |
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| 5 | NumPy |
1. NumPy |
1. NumPy |
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| 6 | NumPy, Pandas |
1. Numpy
2. Pandas |
1. Numpy
2. Pandas |
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| 7 | Pandas, Matplotlib |
1. Pandas
2. Matplotlib |
1. Pandas
2. Matplotlib |
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| 8 | Building A Logistic Regression in Python (1) |
1. Introduction to Logistic Regression
2. Problem Description and Datasets
3. Data exploration
4. Visualizations |
Building A Logistic Regression in Python
1. Introduction to Logistic Regression
2. Problem Description and Datasets
3. Data exploration
4. Visualizations |
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| 9 | 期中考週 |
期中考試 |
期中考試 |
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| 10 | Building A Logistic Regression in Python (2) |
5. Create dummy variables
6. Over-sampling using SMOTE
7. Recursive Feature Elimination
8. Implementing the model |
5. Create dummy variables
6. Over-sampling using SMOTE
7. Recursive Feature Elimination
8. Implementing the model |
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