The School of Information is UC Berkeley’s newest professional school. Located in the center of campus, the I School is a graduate research and education community committed to expanding access to information and to improving its usability, reliability, and credibility while preserving security and privacy.
The Master of Information and Data Science (MIDS) is an online degree preparing data science professionals to solve real-world problems. The 5th Year MIDS program is a streamlined path to a MIDS degree for Cal undergraduates.
The School of Information's courses bridge the disciplines of information and computer science, design, social sciences, management, law, and policy. We welcome interest in our graduate-level Information classes from current UC Berkeley graduate and undergraduate students and community members. More information about signing up for classes.
I School graduate students and alumni have expertise in data science, user experience design & research, product management, engineering, information policy, cybersecurity, and more — learn more about hiring I School students and alumni.
In 1918, UC Berkeley began a full-time program in library science. Join us to celebrate the 105th birthday and history of the I School, SIMS, SLIS, and School of Librarianship.
Cybersecurity Futures 2030 is a foresight-focused scenario-planning exercise considering how cybersecurity is set to transform over the next five to seven years.
Graduating MICS students present their cybersecurity projects. A panel of judges will select an outstanding project for the Lily L. Chang MICS Capstone Award.
Graduating MIDS students present their data science projects. A panel of judges will select an outstanding project for the Hal R. Varian MIDS Capstone Award.
Women in Data Science is a one-day technical conference bringing together data scientists and professionals from around the globe to discuss the latest research and applications of data science.
A 2009 report was highly critical of many forensic practices. This is the first thorough analysis of the purportedly distinct patterns on the seams of denim pants.
Bin Yu is Chancellor’s Distinguished Professor of statistics and EECS. Her research focuses on practice, algorithm, and theory of statistical machine learning and causal inference.