Conversation at UC Berkeley workshop shares perspectives on AI and humanity
A recent discussion at the National Workshop on Data Science Education illustrated the value of open conversation about the impact of AI on humanity.
Safiya Noble, an internet studies scholar, social scientist and UCLA professor, joined Jennifer Chayes, dean of the UC Berkeley College of Computing, Data Science, and Society (CDSS), during a June 24 afternoon session on the Berkeley campus. Their wide-ranging conversation considered the importance of critical thinking and interdisciplinary education, and the need for open systems to expand access to, and participation in, the development and use of AI technologies.
UC Berkeley alumni share insights on data science career paths at National Workshop
In a week filled with panels on pedagogy, curriculum design and emerging technologies in the classroom, the 2025 National Workshop on Data Science Education paused to ask a critical question: What comes next for the students we teach?
A panel of UC Berkeley alumni offered their perspectives, reflecting on how their undergraduate experience shaped their careers, what they wish they'd known earlier and how educators can better prepare students for a changing workforce.
Data Science Undergraduate Studies and Puente partner to inspire underrepresented students in STEM
This summer, we partnered with the Puente MaS program to introduce CA community college students underrepresented in STEM to the field of data science. Through student narratives, a career professional's advice, and information from our Data Science Undergraduate Studies team, the students discovered pathways into a major many had never heard of.
UC Berkeley convenes, connects California data science education pioneers
Dozens of California public educators walked into a sunlight streaked, first floor-room at the edge of UC Berkeley in late June. Hugging each other and snagging coffee or water, they navigated blue and gold star-shaped balloons to settle at tables facing a projector screen.
These scholars are part of a state effort to make California the nation’s leader in excellent, equitable and accessible undergraduate data science education. For the next two days, the assembled attendees would share how they’re building programming, community or pathways to do just that...
About our educational partnerships
UC Berkeley's Data Science Undergraduate Studies is dedicated to making high-quality data science education accessible beyond Berkeley. Through partnerships with other institutions, we strive to broaden access and impact.
Our approach to data science education:
- Empowers student discovery. Through our approachable foundations course and by developing curricula add-ons for other disciplines, we seed opportunities for students to discover this burgeoning field.
- Bridges disciplines. We view data science as an interdisciplinary field with applications spanning from the sciences to the humanities and we promote connections across these diverse areas.
- Integrates human contexts and ethics. Our curricula incorporates human contexts and ethical considerations, equipping students to make responsible and impactful decisions in their careers.
Bring Data Science Education to Your School
Resources for adopting classes and building curricula
Our Current Educational Partnerships
Learn more about our current partnership projects
Community
Events and opportunities to learn from other educators
Join our Mailing List for Educational Partners
Stay informed about resources, community, and news for our educational partners.
Media
Building Data Science Pathways at a Community College
Today, we speak with Rachel Saidi, Professor in the Math, Statistics, and Data Science Department and Data Science Program Director at Montgomery College, a two-year college outside Washington, DC. Rachel shares her path from teaching math to statistics to data science, and what it’s like to scale a data science program in the community college setting, with the goal of catering to students of all ages and experiences. She tackles holistic data science education, combining curriculum, experiential learning, speaker series, and more, while also acknowledging difficulties with constraints like faculty capacity and transfer articulation with four-year universities. Finally, she reflects on how professional organizations can help educators find community and stay on top of best practices, and offers advice to educators and learners on how to tackle data science teaching and learning today.
Listen on Spotify or Apple Podcasts
Scaling Earth System Science: Open Data and CryoCloud
In this week’s episode, we speak with Tasha Marie Snow, a cryosphere researcher who works at the intersection of Earth system science, data science, cloud computing, and open science. Snow is a Co-Founder and Lead Scientist for the CryoCloud cloud-computing community and platform, and works at both NASA and the University of Maryland. She touches on how her work with NASA satellite data, such as ICESat-2 data, focuses on making large, complex datasets more accessible and usable for researchers. She also discusses her role in supporting geoscience researchers to transition their workflows to the cloud via CryoCloud within JupyterHub, as well as the educational benefits of shared computing environments.
Listen on Spotify or Apple Podcasts
Scaling Data Science Education with JupyterHub
To kick off Season 11, we interviewed Min Ragan-Kelley, Senior Open Infrastructure Architect at Berkeley Institute for Data Science (BIDS) and a founding member of JupyterHub. Min discusses the origin story of JupyterHub and how it evolved into the scalable platform that students and researchers alike utilize daily, reflecting on key design decisions that have shaped the platform into what it is today. He describes the importance of the platform to “get out of the way” of students in order to best aid in learning how to operate within a computing environment. Finally, Min touches on his passion for open source projects and what he hopes to come of it in relation to data science education.
Listen on Spotify or Apple Podcasts