Schedule overview

The bootcamp runs Monday through Friday June 15-June 26, 2020 from 1-5:30 pm PDT via Zoom. Enrollees have a private Zoom link emailed to them. Each lesson is approximately 40 minutes and is followed with a break. The lessons are given live via Zoom, but are recorded for future reference. Enrollees will also have private video links emailed to them.

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Daily schedule

• Pre-bootcamp

  • Lesson 0: Configuring your computer

• Day 1: Monday, June 15

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

  • 1:45 - Lesson 2: Basic command line skills

  • 2:30 - Lesson 3: Variables, operators, and types

  • 3:20 - Lesson 4: More operators and conditionals

  • 4:05 - Lesson 5: Lists and tuples

  • 4:50 - Exercise 1

• Day 2: Tuesday, June 16

  • 1:00 - Review of Exercise 1

  • 1:30 - Lesson 6: Iteration

  • 2:45 - Lesson 7: Introduction to functions

  • 3:15 - Lesson 8: String methods

  • 4:05 - Exercise 2

• Day 3: Wednesday, June 17

  • 1:00 - Review of Exercise 2

  • 1:45 - Lesson 9: Dictionaries

  • 2:35 - Lesson 10: Packages and modules

  • 3:20 - Lesson 11: File I/O

  • 4:10 - Exercise 3

• Day 4: Thursday, June 18

  • 1:00 - Review of Exercise 3

  • 1:45 - Lesson 12: Version control with Git

  • 2:35 - Lesson 13: Errors and Exception handling

  • 3:20 - Lesson 14: Testing and test-driven development

  • 4:10 - Lesson 15: Examples of TDD

  • 4:45 - Exercise 4

• Day 5: Friday, June 19

  • 1:00 - Review of Exercise 4

  • 1:45 - Lesson 16: Style

  • 2:35 - Lesson 17: Introduction to Pandas

  • 3:20 - Lesson 18: Tidy data and split-apply-combine

  • 4:10 - Exercise 5

• Day 6: Monday, June 22

  • 1:00 - Review of Exercise 5

  • 1:45 - Lesson 19: Making plots

  • 2:35 - Lesson 20: High level plotting

  • 3:30 - Exercise 6

• Day 7: Tuesday, June 23

  • 1:00 - Review of Exercise 6

  • 1:45 - Lesson 21: Introduction to Numpy and Scipy

  • 2:35 - Lesson 22: Plotting time series and generated data

  • 3:20 - Lesson 23: Random number generation

  • 4:10 - Exercise 7

• Day 8: Wednesday, June 24

  • 1:00 - Review of Exercise 7

  • 1:45 - Lesson 24: Comprehensions

  • 2:35 - Lesson 25: Hacker stats I

  • 3:20 - Lesson 26: Hacker stats II

  • 4:10 - Exercise 8

• Day 9: Thursday, June 25

  • 1:00 - Review of Exercise 8

  • 1:45 - Lesson 27: High level plotting with HoloViews

  • 2:35 - Lesson 28: Dealing with overplotting

  • 3:20 - Lesson 29: Dashboards

  • 4:10 - Exercise 9

• Day 10: Friday, June 26

  • 1:00 - Review of Exercise 9

  • 1:45 - Guest lecture from Griffin Chure: Using version control in research workflows

  • 2:35 - Guest lecture from Griffin Chure: Constructing the paper of the future

  • 3:20 - Lesson 30: Survey of other packages and languages

  • 4:05 - Lesson 31: Bootcamp recap

• Auxiliary lessons

  • Lesson 32: Introduction to object-oriented programming

  • Lesson 33: Algorithmic complexity

  • Lesson 34: More about the command line

  • Lesson 35: Regular expressions

  • Lesson 36: Introduction to scripting

  • Lesson 37: Introduction to image processing with scikit-image

  • Lesson 38: Basic image quantification

  • Lesson 39: Control of external devices

  • Lesson 40: Apps for controlling external devices

• Auxiliary exercise

  • Exercise 10