Online Program Home
My Program

Abstract Details

Activity Number: 522
Type: Invited
Date/Time: Wednesday, August 3, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract #318086 View Presentation
Title: Data Science Education
Author(s): Constantine Gatsonis* and Alfred Hero* and John Lafferty* and Raghu Ramakrishnan*
Companies: Brown University and University of Michigan and The University of Chicago and Microsoft
Keywords: data science ; education ; big data ; training

The nation's ability to make use of big data depends heavily on the availability of a workforce that is properly trained and ready to tackle these high-need areas. However, this workforce is not presently available and it is unclear whether enough students are being trained to be fluent and ready to adapt to the changing demands of a world awash with big data. The Committee on Applied and Theoretical Statistics (CATS) of the National Academies of Sciences, Engineering, and Medicine is establishing a roundtable focusing on data science education and practice. This JSM invited panel will discuss some of these issues underlying the roundtable, including: What big data skills are most important for different career paths? What courses and training would provide a solid foundation for an undergraduate or graduate student interested in big data problems? What different types of preparation might be useful for different categories of data scientists? What is the role of on-the-job training and continuing education?

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

Back to the full JSM 2016 program

Copyright © American Statistical Association