1. Prepare (soft due Tu 8/31, hard due M 9/13)
   1. Content below
   2. Sakai quizzes
2. Group Worksheet (soft due W 9/1, hard due M 9/13)
3. Practice (due M 9/13)
4. Perform (due M 9/27)

Content

2A.A – Numpy (1 hour)

1. Why Numpy (8 min.)
2. Numpy Array Basics (15 min.)
3. Numpy Universal Functions (20 min.)
4. Numpy Axis (14 min.)

2A.B – Pandas (45 min.)

1. Why Pandas (7 min.)
2. Pandas Series (19 min.)
3. Pandas Dataframe (21 min.)

Optional Supplements

• Numpy Beginner’s Tutorial
• Chapter 2: Introduction to Numpy from Python Data Science Handbook
• Numpy Documentation
• 10 Minute to Pandas Tutorial
• Pandas User Guide
• Chapter 3: Data Manipulation with Pandas from Python Data Science Handbook (just the first three subsections)

1. Prepare (soft due Th 8/26, hard due M 8/30)
   1. Content below
   2. See Sakai for quiz
   3. Install Anaconda
2. Group Worksheet (soft due F 8/27, hard due M 8/30)
3. Practice (due M 8/30) (Solution)
4. No Perform

Content

1.A – What is Data Science? (in class or see recording)

1.B – Python3 (12 min.)

1. Python vs. Java (3 min.)
2. Data Types (2 min.)
3. Iteration, Functions, Classes (7 min.)

1.C – Python for Data Science

1. Anaconda and Jupyter (10 min.)
2. Jupyter Notebook Demo (11 min.)

Optional Supplements

• Official Python tutorial
• Python documentation
• Jupyter Notebook Documentation