The Berkeley School of Information is a global bellwether in a world awash in information and data, boldly leading the way with education and fundamental research that translates into new knowledge, practices, policies, and solutions.
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.
Open data infrastructures promise transparency, collaboration, and democratized access to scientific knowledge. But what happens when these same principles enable challenges to scientific consensus?
While multimodal large language models (LLMs) excel at dialogue, whether they can adequately parse the structure of conversation — conversational roles and threading — remains underexplored.
Taylor Arnold uses large-scale computational methods to analyze how television production practices and narrative strategies intersect with industry changes and cultural contexts.
Ongoing work on benchmarking vision-language models and using them and object detection for art historical research into canonicity and national romanticism styles in Northern Europe.
David Bamman’s research focuses on natural language processing and cultural analytics, applying NLP and AI to empirical questions in the humanities and social sciences.
Large language models can make writing mind-numbingly efficient — but the point of writing with AI should be to write what we couldn’t have written alone (without generating bland, derivative “slop”).
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.
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.
Wednesday, December 9, 2026, 4:00 pm
- 6:30 pm PST
Graduating MICS students present their cybersecurity projects. A panel of judges will select an outstanding project for the Lily L. Chang MICS Capstone Award.
Thursday, December 17, 2026, 5:00 pm
- 7:30 pm PST
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.
Zackary Okun Dunivin’s work examines cultural phenomena at scale, including political discourse, mythmaking, information systems, and organizational communication.
Online misinformation is a growing concern. Dr. Madeline Jalbert identifies the underlying psychological processes, the role that feelings play, and the criteria people use to assess truth.
Sayash Kapoor is coauthor of AI Snake Oil and author of the newsletter AI as Normal Technology. He explains the stakes of misplaced optimism about AI in science, medicine, and more.
Thursday, December 18, 2025, 5:00 pm
- 7:30 pm PST
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.
Wednesday, December 10, 2025, 4:00 pm
- 6:30 pm PST
Graduating MICS students present their cybersecurity projects. A panel of judges will select an outstanding project for the Lily L. Chang MICS Capstone Award.
Exploring novel methods for deepfake detection, technical methods for biometric system evaluation, and the complexity of data privacy and consent in high-stakes situations