Skip to content

Latest commit

 

History

History
60 lines (49 loc) · 4.22 KB

README.md

File metadata and controls

60 lines (49 loc) · 4.22 KB

Club Curriculum

build check license

This repository contains the curriculum materials for our weekly club.

The Lessons directory contains live coding demos meant to introduce each topic in ~15 minute interactive mini-lessons. These lessons are delivered in Jupyter Notebooks in a "fill in the blanks" style. Instructors will guide students through each lesson and the students will follow along, filling in the blanks on their own documents as we go.

The Practices directory contains practice exercises for students to spend ~30 minutes to solidify skills taught in each mini-lesson. These practices are delivered in Jupyter Notebooks in a "fill in the blanks" style. Students will work with partners/groups to fill in blanks within the documents, using code from the corresponding lesson as a resource. Instructors will work closely with students to help them complete and understand each practice.

Both Lessons and Practices directories contain _Keys subdirectories with correctly completed versions of each exercise. Sometimes GitHub doesn't render Jupyter notebooks in a timely manner, so we use continuous integration to compile all notebook keys to PDFs. Take a look at the Lesson & Practice Key PDFs if you only want to view them quickly in your browser.

Links for facilitators

Links for students

Lessons

  1. Jupyter Setup
  2. Hello World
  3. Variables & Types
  4. Lists Intro
  5. Lists Indexing
  6. 2D Lists
  7. 2D List Indexing
  8. Logic
  9. Conditionals
  10. For Loops I
  11. For Loops II
  12. Functions & Methods
  13. Packages
  14. Pandas Intro
  15. Reading Data with Pandas
  16. Subsetting Data with Pandas I
  17. Subsetting Data with Pandas II
  18. Dictionaries
  19. Writing Functions
  20. Numpy Intro
  21. Basic Stats I - Averages
  22. Basic Stats II - Percents
  23. Basic Stats III - Correlation
  24. Basic Stats IV - Significance
  25. Plotting - Line Graphs
  26. Plotting - Scatterplots
  27. Plotting - Barplots & Histograms
  28. Machine Learning - Classification
  29. Machine Learning - Clustering