Sea change: What happens when Jupyter becomes pervasive at a university?

In 2018, UC Berkeley launched a new major in data science, anchored by two core courses that are the fastest-growing in the history of the university. Fernando Prez discusses the program and explains how the core courses, which now reach roughly 40% of the campus population, are extending data science into specific domains that cover virtually all disciplinary areas of the campus.

In 2018, UC Berkeley launched a new major in data science, anchored by two core courses—Foundations of Data Science and Principles and Techniques of Data Science—powered by Jupyter infrastructure: all materials are delivered as Jupyter notebooks, with cloud hosting provided by JupyterHub instances available to all (students and faculty) at Berkeley. These courses are the fastest-growing in the history of the university: the two core courses now reach roughly 40% of the campus population. The courses, which combine statistical inference and computation on real-world data, provide a backbone on which a large collection of other courses and modular pedagogical units have grown, extending these foundational ideas into specific domains that cover virtually all disciplinary areas of the campus. In addition to complex pedagogical and logistical challenges, this is opening up a fascinating process: the transition of an entire campus into a pervasive data-literate, computationally savvy environment, where most undergraduates use Jupyter and the open data ecosystem as naturally as they use email. We don’t know yet what this will produce in the next few years, but it’s a remarkable process. We’re delighted to be a part of this process with Jupyter, and we hope it will lead to a wide range of new developments in education, research, and technology.