Below is the class schedule. A few notes:
- All meetings are in Annenberg 105. This includes the evening exercises, when students work together under the guidance of the course staff.
- There will be a special pre-bootcamp session on Sunday, June 17, 2:30 - 4:00 pm, in 326 Sherman Fairchild Library for students who are unable to complete Lesson 0.
Sunday, June 17
- 2:30 - 4 pm
- Lesson 0: Configuring your computer (in 326 SFL)
Monday, June 18
- 9 am - 12:45 pm
- 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
- 12:45 - 1:45 pm
- Lunch
- 1:45 - 4 pm
- Lesson session 2
- Lesson 6: Iteration
- Lesson 7: Introduction to functions
- Lesson 8: String methods
- 4:15 - 5:15 pm
- Faculty lecture: Niles Pierce, Engineering programmable molecular instruments
- 5:15 - 7 pm
- Dinner
- 7 - 10 pm
- Exercise 1
Tuesday, June 19
- 9 am - 12:45 pm
- 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: Exceptions and error handling
- 12:45 - 1:45 pm
- Lunch
- 1:45 - 4 pm
- Lesson session 4
- Lesson 14: Testing and test-driven development
- Lesson 15: Py.test and TDD practice
- Lesson 16: File I/O
- 4:15 - 5:15 pm
- Faculty lecture: Vanessa Jönsson, Computing cancer-immune set points to guide adaptive immunotherapy clinical trial design
- 5:15 - 7 pm
- Dinner
- 7 - 10 pm
- Exercise 2
Wednesday, June 20
- 9 am - 12:45
- 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]
- 12:45 - 1:45 pm
- Lunch
- 1:45 - 4 pm
- Lesson session 6
- Lesson 22: High-level plotting
- Lesson 23: Plotting with Altair
- Lesson 24: Practice with Pandas and Altair [solution]
- 4:15 - 5:15 pm
- Faculty lecture: Dave Van Valen, Deep learning for single-cell biology
- 5:15 - 7 pm
- Dinner
- 7 - 10 pm
- Exercise 3
Thursday, June 21
- 9 am - 12:45 pm
- Lesson session 7
- Lesson 25: Review of exercise 3
- Lesson 26: Introduction to Numpy and Scipy
- Lesson 27: Numpy arrays and operations with them
- Lesson 28: Plotting time series, generated data, and ECDFs
- Lesson 29: Practice with Numpy [solution]
- 12:45 - 1:45 pm
- Lunch
- 1:45 - 4 pm
- Lesson session 8
- Lesson 30: Random number generation
- Lesson 31: Hacker statistics
- Lesson 32: Practice with hacker stats [solution]
- 4:15 - 5:15 pm
- Lecture: Ann Kennedy (Anderson lab), Identifying neural correlates of social behavior in mice
- 5:15 - 7 pm
- Dinner
- 7-10 pm
- Exercise 4
Friday, June 22
- 9 am - 12:45 pm
- Lesson session 9
- Lesson 33: Review of exercise 4
- Lesson 34: Performing regressions
- Lesson 35: Pairs bootstrap
- Lesson 36: Lower-level plotting: Intro to Bokeh
- Lesson 37: Practice with pairs bootstrap and Bokeh [solution]
- 12:45 - 1:45 pm
- Lunch
- 1:45 - 4 pm
- Lesson session 10
- Lesson 38: Introduction to image processing
- Lesson 39: Basic image quantification
- Lesson 40: Practice image processing [solution]
- 4:15-5:15 pm
- Faculty lecture: Matt Thomson, Building low dimensional models from high dimensional data
- 5:15-7 pm
- Dinner
- 7-10 pm
- Exercise 5