Berkeley's core data science classes all offer its students free access to an interactive online textbook. The books are created using a service from Project Jupyter in collaboration with the Berkeley Data Science Education Program (DSEP) known as a Jupyter Book. The most updated textbooks for these core classes are listed below.

The contents of all of these books are licensed for free consumption under the following license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

Data 8 Textbook: Inferential Thinking

Authors: Ani Adhikari and John Denero

Contributions: David Wagner and Henry Milner

This is the textbook for the Foundations of Data Science class at UC Berkeley(link is external)

Data 100 Textbook: Principles and Techniques of Data Science(link is external)

Authors: Sam Wu, Joseph Gonzalez, and Deb Nolan

Data 100 is the upper-division, semester-long data science course that follows Data 8, the Foundations of Data Science(link is external). The reader’s assumed background is detailed in the About This Book(link is external) page.

Prob 140 Textbook: Probability for Data Science(link is external)

Authors: Ani Adhikari and Jim Pitman

This is the textbook for the Probability for Data Science(link is external) class at UC Berkeley.

Jupyter Book Guide

A guide to creating an online Jupyter Book