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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
Lemen Chao1,2(),Canjun Yang2,Shengjie Wang2,Junpeng Zhao2,Mengtian Xu2
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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[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 wordsData Science      Big Data      Curriculum Design     
Received: 12 June 2017      Published: 25 August 2017

Cite this article:

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

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