The Open UniversitySkip to content

Designing and Delivering a Curriculum for Data Science Education across Europe

Mikroyannidis, Alexander; Domingue, John; Phethean, Christopher; Beeston, Gareth and Simperl, Elena (2018). Designing and Delivering a Curriculum for Data Science Education across Europe. In: Teaching and Learning in a Digital World: Proceedings of the 20th International Conference on Interactive Collaborative Learning – Volume 2 (Auer, Michael E.; Guralnick, David and Simonics, Istvan eds.), Springer, Cham, 716 pp. 540–550.

Full text available as:
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


Data is currently being produced at an incredible rate globally, fuelled by the increasing ubiquity of the Web, and stoked by social media, sensors, and mobile devices. However, as the amount of available data continues to increase, so does the demand for professionals who have the necessary skills to manage and manipulate this data. This paper presents the European Data Science Academy (EDSA), an initiative for bridging the data science skills gap across Europe and training a new generation of world-leading data scientists. The EDSA project has established a rigorous process and a set of best practices for the production and delivery of curricula for data science. Additionally, the project’s efforts are dedicated to linking the demand for data science skills with the supply of learning resources that offer these skills.

Item Type: Conference or Workshop Item
Copyright Holders: 2018 Springer International Publishing AG
ISBN: 3-319-73204-8, 978-3-319-73204-6
Keywords: data science; curricula; courseware; demand analysis; personalised learning pathways
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 51762
Depositing User: Kay Dave
Date Deposited: 30 Oct 2017 09:52
Last Modified: 11 Jun 2020 20:29
Share this page:


Altmetrics from Altmetric

Citations from Dimensions

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU