Interleaving Computational and Inferential Thinking: Data Science for Undergraduates at Berkeley

• URL: http://arxiv.org/abs/2102.09391v3
• Date: Wed, 17 Mar 2021 04:05:45 GMT
• Title: Interleaving Computational and Inferential Thinking: Data Science for Undergraduates at Berkeley
• Authors: Ani Adhikari, John DeNero, Michael I. Jordan
• Abstract summary: The undergraduate data science curriculum at the University of California, Berkeley is anchored in five new courses. These courses emphasize computational thinking, inferential thinking, and working on real-world problems. These courses have become some of the most popular on campus and have led to a surging interest in a new undergraduate major and minor program in data science.
• Score: 81.01051375191828
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The undergraduate data science curriculum at the University of California, Berkeley is anchored in five new courses that emphasize computational thinking, inferential thinking, and working on real-world problems. We believe that interleaving these elements within our core courses is essential to preparing students to engage in data-driven inquiry at the scale that contemporary scientific and industrial applications demand. This new curriculum is already reshaping the undergraduate experience at Berkeley, where these courses have become some of the most popular on campus and have led to a surging interest in a new undergraduate major and minor program in data science.

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