Below is the class schedule. A few notes:
- All meetings are on the 9th floor of Millikan library, except where noted otherwise on the schedule below.
- There will be a special pre-bootcamp session on Sunday, June 16, 5-6:30 pm in 328 Sherman Fairchild Library for students who are unable to complete Lesson 0.
- There may be modifications to the schedule and the lessons leading up to the bootcamp.
Before bootcamp
- 5-6:30 pm
- Lesson 0: Configuring your computer (328 SFL)
Monday, June 17
- 8 - 11:45 am
- Lesson session 1
- Lesson 1: Welcome and intro to JupyterLab
- Lesson 2: Basic command line skills
- Lesson 3: Variables, operators, and types
- Lesson 4: More operators and conditionals
- Lesson 5: Lists and tuples
- 11:45 am - 12:45 pm
- Lunch
- 12:45 - 3 pm
- Lesson session 2
- Lesson 6: Iteration
- Lesson 7: Introduction to functions
- Lesson 8: String methods
- 3 - 4:15 pm
- Faculty lecture: Lulu Qian
- 4:15 - 6 pm
- Exercise 1
Tuesday, June 18
- 8 - 11:45 am
- Lesson session 3
- Lesson 9: Review of exercise 1
- Lesson 10: Dictionaries
- Lesson 11: Packages and modules
- Lesson 12: Version control with Git
- Lesson 13: File I/O
- 11:45 am - 12:45 pm
- Lunch
- 12:45 - 3 pm
- Lesson session 4
- Lesson 14: Exceptions and error handling
- Lesson 15: Testing and test-driven development
- Lesson 16: Examples of TDD
- 3 - 4 pm
- Faculty lecture: Yisong Yue
- 4:15 - 6 pm
- Exercise 2
Wednesday, June 19
- 8 - 11:45 am
- Lesson session 5
- Lesson 17: Review of exercise 2
- Lesson 18: Python style (PEP 8)
- Lesson 19: Introduction to Pandas
- Lesson 20: Tidy data and split-apply-combine
- Lesson 21: Practice with Pandas [solution]
- 11:45 am - 12:45 pm
- Lunch
- 12:45 - 3 pm
- Lesson session 6
- Lesson 22: Making plots
- Lesson 23: High level plotting
- Lesson 24: Practice with Pandas and Bokeh [solution]
- 3 - 4 pm
- Guest lecture: Tom Morrell
- 4:15 - 6 pm
- Exercise 3
Thursday, June 20
- 8 - 11:45 am
- Lesson session 7
- Lesson 25: Review of exercise 3
- Lesson 26: Introduction to Numpy and Scipy
- Lesson 27: Plotting time series and generated data
- Lesson 28: Random number generation
- Lesson 29: Practice with Numpy [solution]
- 11:45 am - 12:45 pm
- Lunch
- 12:45 - 3 pm
- Lesson session 8
- Lesson 30: Hacker statistics
- Lessons 31 and 32: Practice with hacker stats [solution]
- 3 - 4 pm
- Guest Lecture: Davi Ortega
- 4:15 - 6 pm
- Exercise 4
Friday, June 21
- 8 - 11:45 am
- Lesson session 9
- Lesson 33: Review of exercise 4
- Lesson 34: High level plotting with Holoviews and Datashader
- Lesson 35: Introduction to image processing
- Lesson 36: Basic image quantification
- Lesson 37: Practice image processing [solution]
- 11:45 am - 12:45 pm
- Lunch
- 12:45 - 1:45 pm
- Guest Lecture: Simon Byrne
- 1:45 - 5 pm
- Exercise 5
- 5 pm - 6 pm
- Lesson session 10
- Lesson 38: Review of exercise 5
- Lesson 39: Bootcamp recap