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 that contain correctly completed versions of each lesson/practice exercise.
See contributing instructions for creating, editing, & reviewing lessons.
- Intro to Computers & Data Science [Google Slides]
- Jupyter Setup
- Hello World
- Variables & Types
- Lists
- Indexing
- 2D lists
- 2D list indexing
- Logic
- Conditionals
- For loops I
- For loops II
- Functions & Methods
- Packages
- Pandas Intro
- Reading data with Pandas
- Subsetting data with Pandas I
- Subsetting data with Pandas II
- Writing your own functions
- Numpy Intro
- Basic Stats I (Averages)
- Basic Stats II (Percents)
- Basic Stats III (Correlation)
- Basic Stats IV (Significance)
- Plotting I
- Plotting II
- Plotting III
- ML Classification (SVM)
- ML Clustering (k-means)