Data Science the Fun Way

Materials for CS 418: Intro to Data Science at UIC. I'm building this out during Summer 2026, in preparation for the Fall 2026 semester. I'm aiming to develop an adventurous, practice-based approach to data science, with lots of exercises to do "by hand" (I was inspired by Tom Yeh's "AI by Hand" series).

Sources consulted

• Core data science texts
  • Learning Data Science by Sam Lau, Joseph Gonzalez, and Deborah Nolan (UC Berkeley)
  • Doing Data Science by Rachel Schutt and Cathy O'Neil (O'Reilly)
  • Python Data Science Handbook by Jake VanderPlas (O'Reilly)
  • Computational and Inferential Thinking by Ani Adhikari and John DeNero (UC Berkeley)
• Statistics and machine learning
  • Intro to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani (Stanford)
  • A Course in Machine Learning by Hal Daume III (UMD)
  • Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, and Jeffrey Ullman (Cambridge/Stanford)
• Visualization and ethics
  • Fundamentals of Data Visualization by Claus O. Wilke (UT Austin)
  • Data Feminism by Catherine D'Ignazio and Lauren F. Klein (MIT Press)
  • Data Feminism for Data Visualization by Lauren F. Klein and Catherine D'Ignazio (Open Visualization Academy)
  • Practical Data Ethics by Rachel Thomas (fast.ai)
  • Open Visualization Academy (Alberto Cairo)

Materials in progress

• HTML syllabus
• Slide decks
  • Week 0 demo deck: HTML | PDF
• Frequently asked questions
• Ethics in Data Science Mini-book

Worksheets

• Worksheet template

Schedule

Schedule is a draft/ work-in-progress.