資料科學與 Python 程式實務
Data Science and Python Programming
| 節 | 週二 |
|---|---|
2 09:00–09:50 | 資料科學與 Python 程式實務 CY202（光復） 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
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評分標準: 以學期授課內容的分析框架，透過一個公開 Dataset，分組專題報告 Midterm Project and Report (10/27 in 8th week): 50% Final Project and Report (12/22 in 16th week): 50%
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| 週次 | 主題 |
|---|---|
| 第 1 週 | A. Principles of Data Literacy 1. Introduction to Data Literacy 2. Thinking about Data 3. Visualizing Data 4. Analyzing Data |
| 第 2 週 | A. Principles of Data Literacy 1. Introduction to Data Literacy 2. Thinking about Data 3. Visualizing Data 4. Analyzing Data |
| 第 3 週 | A. Principles of Data Literacy 1. Introduction to Data Literacy 2. Thinking about Data 3. Visualizing Data 4. Analyzing Data |
| 第 4 週 | B. Python Fundamentals 1. Basic Python Syntax and Variable Types 2. Functions 3. Control Flows 4. Lists 5. Working with Lists 6. Loops 7. Strings 8. Working with Strings 9. Dictionaries 10. Working with Dictionaries 11. Files |
| 第 5 週 | B. Python Fundamentals 1. Basic Python Syntax and Variable Types 2. Functions 3. Control Flows 4. Lists 5. Working with Lists 6. Loops 7. Strings 8. Working with Strings 9. Dictionaries 10. Working with Dictionaries 11. Files |
| 第 6 週 | C. Python Pandas and Numpy 1. Introduction 2. Lambda Functions 3. Hands-on with Pandas 4. Modifying DataFrames 5. Aggregation in Pandas 6. Multiple DataFrames |
| 第 7 週 | C. Python Pandas and Numpy 1. Introduction 2. Lambda Functions 3. Hands-on with Pandas 4. Modifying DataFrames 5. Aggregation in Pandas 6. Multiple DataFrames |
| 第 8 週 | Group Midterm Project Report |
| 第 9 週 | D. Exploratory Data Analysis (EDA) 1. Introduction to EDA 2. Variable Types and Data Types 3. Inspect, Clean, and Validate a Dataset 4. Statistical Summaries for Single Feature 5. Relationship between Numerical and Categorical Variables 6. Relationship between Two Numerical Variables 7. Relationship between Two Categorical Variables |
| 第 10 週 | D. Exploratory Data Analysis (EDA) 1. Introduction to EDA 2. Variable Types and Data Types 3. Inspect, Clean, and Validate a Dataset 4. Statistical Summaries for Single Feature 5. Relationship between Numerical and Categorical Variables 6. Relationship between Two Numerical Variables 7. Relationship between Two Categorical Variables |
| 第 11 週 | D. Exploratory Data Analysis (EDA) 1. Introduction to EDA 2. Variable Types and Data Types 3. Inspect, Clean, and Validate a Dataset 4. Statistical Summaries for Single Feature 5. Relationship between Numerical and Categorical Variables 6. Relationship between Two Numerical Variables 7. Relationship between Two Categorical Variables |
| 第 12 週 | E. Probability & Statistics 1. Probability, Set Theory, and the Law of Large Numbers 2. Rules of Probability 3. Discrete Random Variables 4. Continuous Random Variables 5. Properties of Expectation and Variance 6. More Probability Functions 7. Probability and Statistics 8. Sampling Distribution |
| 第 13 週 | E. Probability & Statistics 1. Probability, Set Theory, and the Law of Large Numbers 2. Rules of Probability 3. Discrete Random Variables 4. Continuous Random Variables 5. Properties of Expectation and Variance 6. More Probability Functions 7. Probability and Statistics 8. Sampling Distribution |
| 第 14 週 | E. Probability & Statistics 1. Probability, Set Theory, and the Law of Large Numbers 2. Rules of Probability 3. Discrete Random Variables 4. Continuous Random Variables 5. Properties of Expectation and Variance 6. More Probability Functions 7. Probability and Statistics 8. Sampling Distribution |
| 第 15 週 | E. Probability & Statistics 1. Probability, Set Theory, and the Law of Large Numbers 2. Rules of Probability 3. Discrete Random Variables 4. Continuous Random Variables 5. Properties of Expectation and Variance 6. More Probability Functions 7. Probability and Statistics 8. Sampling Distribution |
| 第 16 週 | Group Final Project Report |
教科書: 老師線上筆記 https://hackmd.io/ 參考資料: 1. Python Basics: MIT 6.0001 Introduction to Computer Science and Programming in Python 2. 彭彭的Python，C語言入門教學 (http://feis.studio/c)
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