Abstract

As data-powered systems are present in every aspect of our lives, universities have a responsibility to prepare students to partake in the data workforce, to be informed on privacy and ethics of data, and to be inspired to reinvent the future of data. The University of California at Berkeley has been a pioneer in establishing data science offerings for all its undergraduates. In addition, this has initiated important transformations to the campus culture, both in terms of getting established faculty in all disciplines more involved with data science and giving students opportunities to gain sophisticated competencies in data science. The article “ Interleaving Computational and Inferential Thinking: Data Science for Undergraduates at Berkeley” by Adhikari et al (2021, this issue), describes the approach to data science education taken at Berkeley, and the growth of its successful undergraduate data science program in the five years since inception. In this article, I will discuss the pillars of the approach that shore up these exemplary programs. I will also argue for possible improvements to the approach that could broaden access for more students to careers in data science.

Date

June 7, 2021

Authors

Yolanda Gil

Journal

Harvard Data Science Review

Volume

3

Issue

2

Publisher

The MIT Press