The democratization of data science education
- 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
- 2017. The democratization of data science education. PeerJ Preprints 5:e3195v1 https://doi.org/10.7287/peerj.preprints.3195v1
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.