admin Programme Overview
This programme develops a practical and critical understanding of how data can be collected, analysed and communicated responsibly. The curriculum examines statistics, programming, databases, visualisation, modelling and data governance, linking conceptual study with current questions in complex questions in organisations and society.
Hands-on activities support the full analytical process, from framing a question and preparing data through to presenting a defensible interpretation. You will work through guided activities, applied scenarios and peer discussion, developing a disciplined approach to evidence, communication and independent work.
The programme gives equal weight to technical method and critical judgement, including data quality, privacy, bias and reproducibility. 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
- Acquire, prepare and manage data for analysis
- Apply statistical methods and programming techniques
- Create informative visualisations and narratives
- Build and evaluate introductory predictive models
- Assess data quality, ethics and privacy concerns
- Present analytical conclusions with appropriate caveats
Programme Structure
Level 4
- Programming Fundamentals
- Mathematics for Data Science
- Introduction to Data Science
- Database Concepts
- Academic Practice for Computing
Level 5
- Statistical Inference
- Data Wrangling and Visualisation
- Data Structures and Algorithms
- Machine Learning Fundamentals
- Research Methods for Data
Level 6
- Predictive Modelling
- Big Data Concepts
- Data Governance and Ethics
- Applied Analytics
- Data Science Project
Entry Requirements
Applicants are normally expected to have completed secondary education or an equivalent qualification. A basic grounding in mathematics or computing is helpful for this programme. Relevant work experience and prior learning may also be considered.
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 exercises, practical coursework, reports, designs, demonstrations, portfolio work, presentations and a substantial final project. Examination-style assessments may be used where they provide a suitable way to assess underlying concepts and analytical reasoning.
Career Opportunities
- Junior Data Analyst
- Business Intelligence Analyst
- Data Quality Analyst
- Research Data Assistant
- Reporting Analyst
- Analytics Consultant Assistant
Further Study
Graduates may progress to master’s study in data science, analytics, artificial intelligence, business intelligence, statistics or a related computational discipline.