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Activity Number: 651 - Expanding the Tent: Undergraduate Majors in Data Science
Type: Invited
Date/Time: Thursday, August 2, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract #326729 Presentation
Title: Dismantling Math, Stats, and CS Silos: PCMI Guidelines for Undergraduate Majors in Data Science
Author(s): Albert Y. Kim*
Companies: Smith College
Keywords: data science; education; curriculum; PCMI; undergraduate

In the last five years there has been a feverish desire on the part of academic institutions to increase their data science offerings. However, it can be argued that consensus on what form these offerings should take has yet to coalesce. It was in this backdrop that Prof. Richard DeVeaux of Williams College led a 2016 Park City Mathematics Institute Undergraduate Faculty Program tasked with forming an early set of guidelines for undergraduate majors in data science. While the PCMI initiative was not the first of its kind, it was among the first to have broad interdisciplinary representation from mathematics, statistics, and computer science simultaneously. In this talk, we present the details of the resulting guidelines and the relevant discussions behind their design, in particular those surrounding a rhetorical question posed by Prof. Ben Baumer of Smith College: "What if we blew up statistics, computer science, mathematics, and their legacies and started over? What would would this field be?"

Authors who are presenting talks have a * after their name.

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