The project aim
Southampton Data Science Academy (SDSA) was born out of the Web Institute at the University of Southampton. They run tutor-led, online courses helping professionals bridge the gap in skills and demand in a data-driven society. The aim of Fundamentals of Data Science (Non-Technical) is to develop students’ knowledge and practical skills needed to work more effectively with data. There are many courses for highly technical people, but not many for non technical people.
My colleague David Tarrant and I created Fundamentals of Data Science (Non-Technical) and delivered the first instance before licensing it to SDSA.
The design
The course is taught entirely online, with some synchronous and asynchronous elements.
The course came out of an EU research project, exploring how to use problem based learning models to create open data curricula. The ODI’s role was to create a curriculum based on demand analysis done by other EU partners, and to develop a vocational and educational training course for the private and public sector.
We explored problem based learning models and decided on an approach where students attend a webinar that teaches some of the key points, supported by asynchronous online materials. Students then have one problem to solve that combines two weeks of topics to put their skills into practice.
The methodology and outcome is available to read in this deliverable: Open Data VET course for private and public sector employees. (Note this is published under my maiden name Emily Vacher.)
My role
Dave and I collaborated on this project together. I was responsible for weeks 1-3 and he for weeks 4-6, but we worked together to research the literature, build the curriculum, design the course and the assessment, create the resources, manage the platform, deliver the first instance of the course and mark the assessments and write the paper.
What students say
The assignments, the fact that they were real, it was real data and the fact that it was quite emotive topics, actually, was really well-designed, really well-selected assignments, I would say, in hindsight, probably why I was so motivated during it.
The Fundamentals of Data Science (Non-Technical ) course taught me how to gather, clean, analyse and present data on a large scale. It introduced me to new tools and techniques that will help me work much more efficiently with large data sets in the future.