Further opportunities for study
We hope you’ve enjoyed this course!
Are you interested in learning more about Linked Data, SPARQL, or the Semantic Web? Here we discuss a number of study and training opportunities.
The material is based on the EUCLID project and we recommend the free iBook available from that website as a great source for further self-study. It is also available in ePUB and Kindle formats, as well as an HTML version available directly on the site.
For more content related to data, and in particular ‘data science’, the European Data Science Academy project, which is behind the creation of this course, is developing a range of courses on Big Data, Data Management, Machine Learning, Analytics, Visualisation and more.
Postgraduate opportunities for further study
There are various Postgraduate opportunities in Data Science and related subjects at the University of Southampton:
For further FutureLearn courses from the University of Southampton and from the EDSA this Spring/Summer:
25th April 2016 (2 weeks): The Power of Social Media, University of Southampton - Explore the impact of social media on the world and learn how to put it to good use in everyday life.
16th May 2016 (3 weeks): Contract Management: Building Relationships in Business, University of Southampton - Learn to build relationships and manage contracts successfully with this free online course backed by UK government and IACCM.
13th June 2016 (6 weeks): Archaeology of Portus: Exploring the Lost Harbour of Ancient Rome, University of Southampton - Learn how ancient artefacts, written evidence, excavation and digital technologies are transforming understanding of this harbour.
27th June 2016 (2 weeks): Web Science: How the Web is changing the world, University of Southampton - Explore how the web has changed our world and what the future might hold, with this free online course introducing Web Science.
11th July 2016 (4 weeks): Process Mining with ProM, Eindhoven University of Technology in association with EDSA - Use the free, open source process mining framework (ProM) to analyse, visualise, manage and improve a range of business processes.
© University of Southampton 2016