Data Science Conversion Kingston University London
| Award | Attendance | Study | Duration | Start | Domestic fees | International fees |
|---|---|---|---|---|---|---|
| MSc | On-Campus | Full-time | 1 - 2 years | September | £12900.00 year per | £20000.00 year per |
| MSc | On-Campus | Part-time | 2 years | September | £7095.00 year per | £11000.00 year per |
2025/26 Fees
Home (UK students)
Full Time £12,400
Part Time £6,820
International
Full Time £19,300
Part Time £10,615
Course overview
Large data sets are widespread in business, science and government. Consequently, there is an increasing demand for data-savvy professionals, both in industry and in research, who are able to make sense of complex datasets, build models and apply them to the solution of relevant problems.
This conversion course is part of the government's response to the shortage of data science and artificial intelligence specialists in the UK. It aims to help students without strong backgrounds in programming or statistics to acquire a level of skill in these areas and learn to apply them.
Like many MSc courses in the School of Computer Science and Mathematics, Data Science benefits from a diverse community of learners. You will study in week-long blocks that can fit around different work/study patterns. You will also get to take advantage of opportunities for exposure to cutting-edge examples and exercises.
Please note that this course will begin earlier than other Kingston courses, to allow us to deliver a two-week ‘boot camp' of intensive pre-sessional teaching, to equip you with the technical skills needed to complete the course.
Entry requirements
The typical offer for this course is a 2:2 or above honours degree in any discipline.
Please note: each application for this course is assessed on an individual basis and may be subject to additional requirements, such as undertaking short course(s), work experience and/or English language qualification(s). Meeting particular minimum entry requirements does not automatically guarantee a place.
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