The Data 8 Pedagogy Guide#

Data 8 is a “The Foundations of Data Science” course taught to first-year students at UC Berkeley. It combines principles and skills from statistics and computer science, such as inference, modeling, hypothesis testing, visualization, and others. It provides a foundation in the many disciplines encompassed by “data science”, and gives students a practical introduction to the field.

Teaching Data Science requires a shift in the way we traditionally teach each of the individual concepts. What were once introductory classes in statistics, computer science, and ethics (among others) are now combined into a single introductory course.

This book covers many of the pedagogical decisions that were made in Data 8 and should be seen as a reference and background for it.

All of the tools that Data 8 uses are available for the community to use (either as broader community-run projects, or as Berkeley projects). Many of them are open source (see Types of content in Data 8 for more information). The course material can be accessed at the following online resources:

To explore the guide, select a section to the left!

Types of content in Data 8#

There are many kinds of content associated with Data 8, released under two different licenses. You can find more complete information at the Data 8 adoption website. Here is a quick breakdown:

  • The Data 8 textbook is the textbook used by Data 8, with material that complements each topic in the class. It is licensed CC-BY-ND-NC, you are welcome to use the textbook at, but you may not modify or distribute it yourself without permission from the textbook authors.

  • Data 8 course materials includes notebooks, exercises, and other course materials. It is licensed CC-BY-NC, and you are free to modify and distribute as you wish.

  • Private course materials, including exams and answers. These are kept private in order to protect the integrity of the Data 8 courses at Berkeley and being run elsewhere. If you’d like access to these materials, please fill out this Google form.

  • Course Calendar and Demonstation Platforms We have an example course calendar laying out the course week-to-week with appropriate notebooks linked to various rendering platforms.

Technology Guide#

If you are looking for a more technical overview of the infrastructure required to create a data science course at your institution, there is a new guide titled “The Data Science Educator’s Guide to Technical Infrastructure”.

Contacting Us#

If you woud like to learn more about any of the tools used in Data 8 or are interested in deploying your own data 8 course, please fill out our Data 8 Instructor Interest form or shoot us an email at