DSC 80 – The Practice and Application of Data Science

📚 Resources

Past exams with detailed solutions can be found at practice.dsc80.com. We're constantly working to add more exams and solutions to the site.

Principles and Techniques of Data Science, the textbook for Berkeley's Data 100 course. Most of our supplemental readings will come from here.
notes.dsc80.com. These notes were originally written for DSC 80 but have not been updated in a few years. Some of our supplemental readings will come from here.
Wes McKinney. "Python for Data Analysis".
DSC 10 Course Notes – great refresher on babypandas.
Computational and Inferential Thinking, the textbook for Berkeley's Data 8 course.

Views and Copies in pandas – a great read if you'd like to learn more about the infamous SettingWithCopyWarning.
jwilber.me/permutationtest, a great visual explanation of permutation testing.
A Visual Introduction to Machine Learning and Model Tuning and the Bias-Variance Tradeoff, excellent visual descriptions of the last few weeks of the course (some terminology is different, but the ideas are the same).
New: MLU Explain, a collection of interactive articles (prepared by Jared Wilber) that explain core machine learning ideas, like cross-validation, random forests, and precision and recall.