Keele University

What you'll study

This programme combines modules in statistics, machine learning, data management and business strategy, culminating in an extended applied project or dissertation. Teaching balances theory and hands-on practice using industry-standard tools and programming languages to prepare you for real-world analytics work.

• Core analytics and methods: statistical inference, regression and multivariate methods, time series and forecasting, and business decision modelling.
• Computing and tools: practical training in data preparation, scripting (commonly Python and/or R), SQL and use of visualisation and business intelligence platforms.
• Machine learning and big data: supervised and unsupervised learning techniques, model evaluation, and approaches for handling larger or unstructured datasets.
• Business context and strategy: modules that focus on translating analytics into organisational value, including change, ethics and governance of data-driven projects.
• Research methods and project: methods for applied analytics and a substantial independent project or dissertation, which can be industry-linked, allowing you to apply techniques to a real organisational problem.

Entry requirements

Applicants are normally expected to hold a good honours degree in a numerate subject (for example business, economics, computing, mathematics, engineering or a social science with quantitative content) or a degree in another subject combined with relevant work experience. Candidates with appropriate professional experience or evidence of quantitative ability may be considered on a case-by-case basis. International applicants must demonstrate competence in English via an approved test or recognised qualification.

Career prospects

Graduates go on to roles such as data analyst, business analyst, analytics consultant, operations or supply chain analyst, business intelligence developer and, with further experience or training, data scientist. Employers span private firms (finance, retail, technology, consultancy), healthcare organisations, and public sector bodies. The course also provides a foundation for further research or professional qualifications in analytics and data science.

Why study at Keele University

Keele combines a collegiate campus environment with focused small-group teaching from staff with applied research and industry experience. The programme emphasises practical skills, using computing labs and software commonly used by employers, and offers opportunities for industry-linked projects through the School. Students benefit from interdisciplinary links across computing, business and health faculties, and from support services for careers and enterprise that help convert analytical training into employment outcomes.