Schedule overview

The bootcamp runs August 18–21, 2025, 9:00–16:00. We meet in the K. B. Weissman Auditorium in Weissman Building, which houses part of the Faculty of Physics.

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Daily schedule

• Pre-bootcamp

  • Lesson 0: Configuring your computer for the bootcamp

• Day 1: Monday, August 18

  • 9:00 - Lesson 1: Welcome and Introduction to JupyterLab

  • 9:45 - Lesson 3: Variables, operators, and types

  • 10:35 - Lesson 4: More operators and conditionals

  • 11:20 - Lesson 5: Lists and tuples

  • 12:00 - Lunch break

  • 13:00 - Lesson 6: Iteration

  • 13:45 - Lesson 7: Introduction to functions

  • 14:35 - Lesson 8: String methods

  • 15:20 - Exercise 1

• Day 2: Tuesday, August 19

  • 9:00 - Review of Exercise 1

  • 9:45 - Lesson 9: Dictionaries

  • 10:35 - Lesson 10: Packages and modules

  • 11:20 - Lesson 11: File I/O

  • 12:00 - Lunch break

  • 13:00 - Lesson 12: Version control with Git

  • 13:45 - Lesson 13: Errors and exception handling

  • 14:35 - Lesson 14: Style

  • 15:20 - Exercise 2

• Day 3: Wednesday, August 20

  • 9:00 - Review of Exercise 2

  • 9:45 - Lesson 15: Comprehensions

  • 10:35 - Lesson 16: Introduction to data frames and Polars

  • 11:20 - Lesson 17: Tidy data and split-apply-combine

  • noon - Lunch break

  • 13:00 - Lesson 18: Making plots

  • 14:00 - Lesson 19: High level plotting with iqplot

  • 15:00 - Exercise 3

• Day 4: Thursday, August 21

  • 9:00 - Review of Exercise 3

  • 9:45 - Lesson 20: Styling Bokeh plots

  • 10:35 - Lesson 21: Introduction to Numpy and Scipy

  • 11:20 - Lesson 22: Plotting time series and generated data

  • noon - Lunch break

  • 13:00 - Exercise 4

  • 15:15 - Lesson 23: Survey of other packages and languages

  • 15:45 - Lesson 24: Bootcamp recap

• Auxiliary lessons

  • Lesson 2: Basic command line skills

  • Lesson 25: Random number generation

  • Lesson 26: Hacker stats I

  • Lesson 27: Hacker stats II

  • Lesson 28: Dashboards

  • Lesson 29: JavaScript for stand-alone Bokeh apps

  • Lesson 30: Control of external devices

  • Lesson 31. Apps for controlling external devices

  • Lesson 32: Control panels

  • Lesson 33: More about the command line

  • Lesson 34: Regular expressions

  • Lesson 35: Introduction to scripting

  • Lesson 36: Introduction to object-oriented programming

  • Lesson 37: Algorithmic complexity

  • Lesson 38: Testing and test-driven development

  • Lesson 39: Examples of TDD

  • Lesson 40: High level plotting with HoloViews

  • Lesson 41: High level plotting with Vega-Altair

  • Lesson 42: More plotting with Vega-Altair

  • Lesson 43: Dealing with overplotting

  • Lesson 44: Introduction to image processing with scikit-image

  • Lesson 45: Basic image quantification

  • Lesson 46: Plotting with Matplotlib and Seaborn

• Auxiliary exercise

  • Exercise 5