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Systematic Study of Big Data Science and Analytics Programs

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Conference

2017 ASEE Annual Conference & Exposition

Location

Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Curricular Issues in Computing

Tagged Division

Computing & Information Technology

Page Count

9

DOI

10.18260/1-2--28900

Permanent URL

https://peer.asee.org/28900

Download Count

252

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Paper Authors

biography

Huanmei Wu Indiana University-Purdue University, Indianapolis

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Chair of the Department of BioHealth Informatics. Research on data management and data analytics, applying to informaticcs, especially biomedical informatics and other interdisciplinary fields.

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Abstract

Rapid advances in information technologies have led to the generation of massive data sets, especially in life science and biomedical informatics. These data sets are valuable assets and in great needs to be analyzed. However, there is a shortage of workforce for big data analysis. Education innovations are required to empower students with the skills and technologies for large dataset analysis. Over the last few years, there is a high demand for new programs in data science and analytics (DSA). We has performed a systematic study of the existing DSA programs in the US by checking the detailed information about the degree programs, the program competencies, the curriculum designs, the expected learning outcomes, program sizes, professional careers, and other related information. There are more than 70 DSA programs offered in the US. This study provides guidance on DSA related program development and curriculum design. It also provides the potential trainees in DSA with the current market needs and the required knowledge for their future career.

Wu, H. (2017, June), Systematic Study of Big Data Science and Analytics Programs Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28900

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