admin Programme Overview
This programme offers advanced study of the methods and judgement required to derive robust insight from complex data. The curriculum examines statistical modelling, machine learning, data engineering, visualisation and research design, linking conceptual study with current questions in evidence-based investigation and decision support.
You will work with data-intensive problems, examining how questions are framed, data is prepared and results are evaluated and communicated. You will work through guided activities, applied scenarios and peer discussion, developing a disciplined approach to evidence, communication and independent work.
The curriculum embeds reproducibility, privacy and fairness in analytical practice, helping you engage critically with both findings and their limitations. Learning is organised for online participation, with clear milestones, tutor feedback and space to connect ideas across the programme. Throughout, opportunities to compare perspectives and receive formative feedback help consolidate your understanding, refine your judgement and prepare you to engage confidently with unfamiliar professional challenges. The final stage invites you to bring your learning together in a sustained piece of work.
What You’ll Learn
- Design rigorous data science investigations
- Apply advanced statistical and machine learning methods
- Evaluate data pipelines and analytical reproducibility
- Communicate complex data findings effectively
- Assess ethical, legal and governance implications
- Complete an independent data science project
Programme Structure
Core Modules
- Statistical Modelling for Data Science
- Machine Learning Applications
- Data Engineering and Pipelines
- Advanced Data Visualisation
- Data Governance and Ethics
Research and Applied Practice
- Research Design for Data Science
Final Project
- MSc Data Science Dissertation or Applied Capstone
Entry Requirements
Applicants are normally expected to hold a relevant undergraduate degree or demonstrate equivalent professional experience. Applications from adjacent disciplines may be considered where applicants can show appropriate technical knowledge and readiness for advanced study.
Applicants should be able to demonstrate English-language proficiency appropriate for degree-level study. Equivalent evidence of English proficiency may be considered as part of the application.
Assessment
Assessment may include technical investigations, applied coursework, reports, prototypes, critical analyses, presentations, portfolio evidence and a substantial capstone project or dissertation. Examination-style assessments may be used where appropriate to assess core concepts.
Career Opportunities
- Data Scientist
- Senior Data Analyst
- Machine Learning Analyst
- Analytics Consultant
- Data Engineer
- Research Data Specialist
Further Study
Graduates may consider doctoral study where entry requirements are met or pursue specialist development in analytics engineering, machine learning, statistics or data governance.