University of Reading

What you'll study

The programme combines core training in statistics, programming and machine learning with applied modules and a substantial individual research or industry-linked project. You will build practical skills in data acquisition, cleaning and storage; exploratory and inferential statistics; supervised and unsupervised learning; deep learning methods; and tools for communicating results such as data visualisation.

• Core topics typically include: statistical inference and modelling, machine learning, programming for data science (commonly Python and relevant libraries), databases and big-data technologies, and principles of data visualisation.
• Applied modules: data mining and feature engineering, applied machine learning in domains such as finance or environmental science, scalable analytics, and ethical, legal and practical issues in data use.
• Project / dissertation: an individual research or industry project supervised by academic staff, allowing you to apply methods to a real dataset and demonstrate independent technical and communicative skills.
• Teaching and assessment: a mix of lectures, practical laboratory sessions, programming workshops and seminar-style modules; assessment typically through coursework, project reports, presentations and a final dissertation or project deliverable.

Entry requirements

Applicants are normally expected to hold an upper second-class (2:1) UK honours degree, or an international equivalent, in a numerate discipline such as computer science, mathematics, statistics, engineering, physics, or a related subject with substantial quantitative content. Applicants with a lower second-class degree plus relevant professional experience or evidence of strong quantitative and programming ability may also be considered.

All applicants whose first language is not English must demonstrate competence in English through an accepted qualification (for example an IELTS, TOEFL or equivalent); details of acceptable scores and exemptions are provided by the university. Applicants should be prepared to show evidence of programming ability or complete preparatory material if required.

Career prospects

Graduates are prepared for roles that require strong data skills and quantitative judgement. Typical job titles include data scientist, data analyst, machine learning engineer, data engineer, business intelligence analyst and quantitative modeller. Alumni work across sectors such as finance and banking, technology and software, healthcare and pharmaceuticals, energy and environment, retail and consumer analytics, and public sector analytics.

The programme also provides a foundation for further research or doctoral study for those interested in academic careers.

Why study at University of Reading

University of Reading offers a research-active environment with academic staff working on applied and methodological problems across statistics, computer science and data analytics. The programme emphasises hands-on skills through laboratory sessions and a substantial project supervised by academics with expertise in relevant application areas.

Reading's location gives good access to employers in the Thames Valley and London, and the university provides careers support, workshops and employer engagement activities to help students develop professional skills and make industry contacts. Teaching is delivered in well-equipped computing facilities and draws on interdisciplinary collaboration across the university.