The democratization of data science education

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1 Department of Biostatistics, The Johns Hopkins University, Baltimore, MD, United States
2 Center for Teaching and Learning, The Johns Hopkins University, Baltimore, MD, United States
DOI
10.7287/peerj.preprints.3195v1
Published
Accepted
Subject Areas
Science and Medical Education, Statistics, Human-Computer Interaction, Computational Science
Keywords
data science, education, online learning
Copyright
© 2017 Kross et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Kross S, Peng RD, Caffo BS, Gooding I, Leek JT. 2017. The democratization of data science education. PeerJ Preprints 5:e3195v1

Abstract

Over the last three decades data has become ubiquitous and cheap. This transition has accelerated over the last five years and training in statistics, machine learning, and data analysis have struggled to keep up. In April 2014 we launched a program of nine courses, the Johns Hopkins Data Science Specialization, which has now had more than 4 million enrollments over the past three years. Here the program is described and compared to both standard and more recently developed data science curricula. We show that novel pedagogical and administrative decisions introduced in our program are now standard in online data science programs. The impact of the Data Science Specialization on data science education in the US is also discussed. Finally we conclude with some thoughts about the future of data science education in a data democratized world.

Author Comment

The first version of our submission to The American Statistician.