UC Berkeley Master of Computational Social Science -

Bridging the Gap Between
Data and Social Understanding

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Empower Your Social Science Degree with Data Computation Skills — UC Berkeley MaCSS

MaCSS is a one year in-person degree program that provides a cutting-edge computational education to those with social science backgrounds. With an emphasis on real-world applicability, our curriculum integrates computing tools and techniques, statistical approaches to data analysis, and social science theories and findings.

Data about people and the social world doesn’t “speak for itself.” While we’ve become adept at collecting and processing data, the graduates of the MaCSS program go beyond simple statistics to truly understand the complexities of our modern society in the curriculum.

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What You’ll Gain

About the Program

Uncover Deeper Insights

You’ll go beyond basic statistical analysis to answer the complex questions about human behavior, social structures, and forces shaping our world.

Develop innovative solutions

Address a wide array of social concerns, from inequality and exclusion to healthcare access and climate change, with data-driven solutions informed by a deep understanding of human needs.

Prepare for impactful careers

MaCSS graduates are highly sought after for data analyst roles in business, government, and nonprofits, where they can use their unique skillset to make a real-world difference.

The Student Experience

Citlalli Mendez-Santeno

“MaCSS allows me to utilize my sociological background while also equipping me with computational tools, enabling me to address social issues from a different, data-driven perspective.”

Sangmin Lee

“The MaCSS program’s emphasis on practical application, paired with its sophisticated interdisciplinary curriculum, perfectly aligns with my professional goal of becoming a data analyst who can answer a wide range of social questions with innovative computational approaches.”

Eloise Qin

“I love how the MaCSS program provides career development courses to help students with interviewing, networking strategies, and resume workshops, which provide a step by step guideline to be successful in job searching and my future career.”

Data analytics requires much more than writing code to tell a computer what model to estimate. We need to use our social science knowledge to pose the right question, understand how the data were generated, choose the right model for the research question, correctly interpret the results, and think through how a solution to a problem will work in a given context.”

Professor David Harding

Professor and Chair, Department of Sociology