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Data Science at Kingston University - UCAS

Course options

2024 - 20252025 - 2026
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There are other course options available which may have a different vacancy status or entry requirements – view the full list of options

Course summary

Reasons to choose Kingston

  • This course aligns with a thriving area of applied machine learning research, giving opportunities for exposure to plenty of cutting-edge examples and exercises.
  • This course has flexible entry points and has been designed for a variety of disciplines and backgrounds.
  • 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.
About this course Data Science is one of the most rapidly expanding areas of employment globally, due to rapid and ongoing developments in computer systems and data gathering. Large data sets are widespread in business, science and government. This course builds on the established strengths of the Mathematics and Computer Science programmes at Kingston and develops a multidisciplinary approach to the computational analysis of data. 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. You will get the opportunity to develop your skills in a way which will prepare you for careers in this fast- growing and exciting area. Example modules
  • Machine Learning and Artificial Intelligence
  • Applied Data Programming
  • Data Analytics and Visualisation
For a full list of modules please visit the Kingston University course webpage. Career opportunities This course offers an excellent foundation aimed at careers contained within the more generic ‘Data Science’ umbrella, including data engineer, data analyst and machine learning engineer.

Modules

Example modules: Machine Learning and Artificial Intelligence, Applied Data Programming; Data Analytics and Visualisation. For a full list of modules please visit the Kingston University course webpage.

Assessment method

Assessment typically comprises in-class tests, practical (e.g. presentations, demonstrations) and coursework (e.g. essays, reports, self-assessment, portfolios, dissertation). The approximate percentage for how you will be assessed on this course is as follows: 94% coursework 3% exams and tests 3% practical (repeat for each year, if part time)

Entry requirements

A 2.1 or above honours degree in a subject with relevant computing science and mathematics/statistics content. Typical appropriate first degree subjects would include: computer science (including software engineering or cyber security), mathematics, statistics, and some engineering courses.

Fees and funding

Tuition fees

England £10900 Year 1
Northern Ireland £10900 Year 1
Scotland £10900 Year 1
Wales £10900 Year 1
EU £18500 Year 1
International £18500 Year 1

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

Please visit the provider course webpage for further information regarding additional course costs
Data Science at Kingston University - UCAS