Data Science Curriculums Around the World: An Empirical Study

doi:10.11925/infotech.2096-3467.2017.06.02

Data Analysis and Knowledge Discovery

2017, Vol. 1

Issue (6): 12-21 DOI: 10.11925/infotech.2096-3467.2017.06.02

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Data Science Curriculums Around the World: An Empirical Study

Chao Lemen^1,²(

), Yang Canjun², Wang Shengjie², Zhao Junpeng², Xu Mengtian²

¹Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China), Beijing 100872, China
²School of Information Resource Management, Renmin University of China, Beijing 100872, China

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Abstract

[Objective] This paper identifies the common features of existing Data Science curriculums around the world. It also addresses the main challenges facing these courses as well as possible solutions. [Methods] We conducted an empirical study with the help of text analysis techniques to examine the data science curriculums from China and abroad. [Results] We found common features of the retrieved curriculums and the differences between them and other related courses. [Limitations] Our study focused on the curriculum issues, therefore, more research is needed to discuss data science as a discipline. [Conclusions] This paper addresses the top ten key challenges facing data science curriculum and then proposes some solutions.

Key words： Data Science Big Data Curriculum Design

Received: 12 June 2017 Published: 25 August 2017

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	Lemen Chao
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Cite this article:

Chao Lemen,Yang Canjun,Wang Shengjie,Zhao Junpeng,Xu Mengtian. Data Science Curriculums Around the World: An Empirical Study. Data Analysis and Knowledge Discovery, 2017, 1(6): 12-21.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.06.02 OR https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I6/12

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