Below is the class schedule. A few notes:
- All instruction is in English.
- All meetings are in Room BC02 of the EPFL. 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, July 8 (location and time TBA) 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
- Time TBA
- Lesson 0: Configuring your computer (location TBA)
Monday, July 9
- 8 am - 11:45 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
- 11:45 - 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: Suliana Manley
- 4:15 - 6 pm
- Exercise 1
Tuesday, July 10
- 8 am - 11:45 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: File I/O
- 11:45 - 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: Py.test and TDD practice
- 3 - 4 pm
- Faculty lecture: Maartje Bastings
- 4:15 - 6 pm
- Exercise 2
Wednesday, July 11
- 8 am - 11:45
- 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]
- 11:45 - 12:45 pm
- Lunch
- 12:45 - 3 pm
- Lesson session 6
- Lesson 22: High-level plotting
- Lesson 23: Plotting with Altair
- Lesson 24: Practice with Pandas and Altair [solution]
- 3 - 4 pm
- Faculty lecture: Andy Oates
- 4:15 - 6 pm
- Exercise 3
Thursday, July 12
- 8 am - 11:45 pm
- Lesson session 7
- Lesson 25: Review of exercise 3
- Lesson 26: Introduction to Numpy and Scipy
- Lesson 27: Plotting time series, generated data, and ECDFs
- Lesson 28: Random number generation
- Lesson 29: Practice with Numpy [solution]
- 11:45 - 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
- Faculty Lecture: Sophie Martin
- 4:15 - 6 pm
- Exercise 4
Friday, July 13
- 8 am - 11 am
- Lesson session 9
- Lesson 33: Review of exercise 4
- Lesson 34: Introduction to image processing
- Lesson 35: Basic image quantification
- Lesson 36: Practice image processing [solution]
- 11 am - 12 pm
- Faculty lecture: Bart Deplancke
- 12 - 1 pm
- Lunch
- 1 - 5 pm
- Exercise 5
- 5 pm - 6 pm
- Lesson session 10
- Lesson 37: Review of exercise 5
- Lesson 38: Bootcamp recap