Curriculum Overview

Berkeley’s Data Science education program aims at a comprehensive curriculum built from the entry level upward to meet students’ varied needs for data fluency. It includes a diverse constellation of connector courses that allow students to explore real-world issues related to their areas of interest and continues with intermediate and advanced courses that enable them to apply more complex concepts and approaches.

Foundations of Data Science (Data 8)

Foundations of Data Science, or Data 8, is Berkeley’s path-breaking lower-division course that teaches core computational and statistical concepts while enabling students to work hands-on with real data. It is designed to be accessible to undergraduates of any intended major and does not require prior experience in the field.


Connector courses enable students to apply core concepts from the Foundations course to explore real-world issues that relate to students’ areas of interest. Offered by faculty across many departments and fields of study, connectors are optional but highly encouraged and are designed to be taken at the same or after the Foundations course. They offer two or more units of course credit.

View all current courses at or visit a list of all connectors that have been offered.

If you are interested in teaching connector course or are currently running one, please visit the Connector Guide for more information.  

Courses with Data 8 as prerequisite 

These courses take Foundations of Data Science as a starting point for further work in data science. Three courses have been developed to date and are offered in some or all semesters. Please check the list of current courses for this semester's offerings. 

Data-enabled courses

These courses across Berkeley are taught in a way that permits students to build on top of Data 8. Please check the list of current courses for this semester's offerings. Students should review prerequisites. 

Advanced integrative opportunities

Advanced Integrative opportunities enable more advanced students to work hands-on with data in an interdisciplinary, project-based manner. For instance, Terrestrial Hydrology (Geog C136/ESPM C130) is a new course focused on the role that hydrology plays in malaria transmission in sub-Saharan Africa (pre requisites are Math 1A-1B and Physics 7A).

Data science modules in existing courses

Instructors are introducing data science modules into existing courses as a way to enable students to tap the power of data in a range of disciplines and fields. Modules use approaches and concepts familiar from the Foundations and connector courses. Learn more about modules>>

Other core courses for students who want to pursue data science

In addition to the courses listed above, a variety of courses are offered as part of existing programs. Here are just a few examples offered in regular rotation:

    • CS 186: Introduction to Database Systems

    • CS 189: Introduction to Machine Learning

    • STAT 133: Concepts in Computing with Data

    • STAT 154: Modern Statistical Prediction and Machine Learning

    • STAT 159: Reproducible and Collaborative Data Science

    • CS 61A, B, C provide additional background in computing

    • Math 1A & 1B, Math 10A & 10B, Math 54

Proposals for Data Science major and minor programs of study at Berkeley are under preparation for consideration by faculty and administrative review. This website will provide updated information as it becomes available.

Other institutions 

Faculty from other institutions who are interested in developing a data science program are invited to visit our implementation page.