Creating a Balanced Data Science Program

被引:7
|
作者
Adams, Joel C. [1 ]
机构
[1] Calvin Univ, Dept Comp Sci, Grand Rapids, MI 49546 USA
关键词
Computer science; data; data analytics; data science; statistics;
D O I
10.1145/3328778.3366800
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
As we consider the next fifty years of computing education, a phenomenon that shows no signs of abating is the data deluge, in which commercial companies, the natural sciences, the social sciences, professional sports teams, government agencies, and other institutions are generating ever-increasing quantities of data. To address the challenges posed by the data deluge, the discipline of data science has arisen, and an increasing number of universities are offering undergraduate data science programs. Many of these programs have their origins in a computer science or a statistics department, leading to a data science curriculum that is more heavily weighted toward computing or statistics. By contrast, the data science program described in this paper is a joint endeavor between computer science and statistics that seeks to provide balanced training in both areas. Its broad goals are to produce students who (a) are well-trained in both computer science and statistics, (b) are equipped with specialized data-related skills that are not normally taught in either of those disciplines, and (c) can apply their skills to a domain area. This paper reports on the author's experiences leading the effort to create this program, which has seen good growth, received positive feedback from students, and is successfully preparing students for internships. We offer this report in the hope that it may serve as a model for other institutions considering the addition of an undergraduate data science program.
引用
收藏
页码:185 / 191
页数:7
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