University of Sussex campus

Arts & Humanities

Human and Social Data Science MSc at University of Sussex

University of Sussex, United Kingdom

Programme overview

Discover how data can be used to understand human behaviour. Focus on digital media or innovation and policy, and also collaborate with industry. Data is everywhere and affects every aspect of our lives and our society – from fitness trackers to online shopping to social media. Data is used to understand human behaviour, and to inform policy, journalism and strategy.

Department: Department of Mathematics  |  Duration: 1 year full time  |  Study mode: full-time  |  Intake: September 2027  |  Location: Brighton, England, United Kingdom

What you will study

Core modules: All year, Dissertation (Human and Social Data Science), Algorithmic Approaches to Mathematics, Data Science Research Methods Autumn (L7), Systems for Information Management, Data Science Masters Research Proposal, Machine Learning, Wider Topics in Data Science (L7).

Official programme page

Application information

Entry requirements

Degree requirements: You should normally have an upper second-class (2.1) undergraduate honours degree or above. Subject-specific requirements: Your qualification should be in Psychology, Economics, Business, or another Social Science subject with a good level of numeracy. You may also be considered for the course if you have an undergraduate degree in a different subject area and can demonstrate that you have ability with data and a reasonable level of Maths (this can be demonstrated in your school leaving qualifications). English language: IELTS (Academic) Standard level (6.0 overall, including at least 5.5 in each component). Apply by 1 August 2027 (international), 1 September 2027 (UK).

Domestic applicants: GBP 11,600 a year. for full-time students Source

International applicants: GBP 24,200 a year. for full-time students Source

Intake: September 2027

Duration: 1 year full time

Apply through the official page: https://www.sussex.ac.uk/study/masters/apply

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