MSc Data Science and Artificial Intelligence
This MSc is for people who want to develop advanced skills in data science and artificial intelligence. It combines statistical analysis, programming, machine learning and data engineering with practical work on data-driven applications. It may suit graduates from any subject who meet the entry requirements, including those looking to move into data or AI-focused work.
About this course
This MSc combines data science, artificial intelligence and software engineering for graduates looking to develop practical and analytical skills in working with data-driven systems.
You will build a grounding in statistics, data inference, programming and machine learning before moving into areas such as data engineering, distributed processing, data mining, visualisation, deep learning and natural language processing. The course also considers responsible practice, including GDPR, the EU AI Act and algorithmic fairness.
Study is available full-time, part-time or flexibly. A two-year full-time route with academic and professional practice is also available.
What you will study
Core areas include Programming and AI Orchestration; Foundations of Statistics and Data Inference; Machine Learning Principles; and Ethics, Law, and Society.
You will also study Distributed Processing and Data Engineering, including Apache Spark, Docker, Kubernetes and MLOps; Data Mining, Visualisation, and Actionable Intelligence; and Deep Learning and Natural Language Processing. Topics include exploratory data analysis, association rule mining, network analysis, data storytelling, Transformers and large language models.
Further study covers Applied Data Architecture and Integration, software engineering, research methods and an MSc Project in Computer Science. Professional Development, Consultancy Projects and a Computing Work Placement are included in the relevant study routes.
Modules
Semester 1
- Programming and AI Orchestration (core)
- Foundations of Statistics and Data Inference (core)
- Machine Learning Principles (core)
- Ethics, Law, and Society (core)
Semester 2
- Distributed Processing and Data Engineering (core)
- Data Mining, Visualisation, and Actionable Intelligence (core)
- Deep Learning and Natural Language Processing (core)
- Applied Data Architecture and Integration (core)
Semesters 1-3
- MSc Project in Computer Science (core)
- Professional Development (core)
Academic and Professional Practice Year
- Computing Work Placement (optional)
- Consultancy Projects (optional)
Assessment
Assessment includes portfolios, coursework reports and presentations.
Entry requirements
Applicants need an undergraduate degree in any subject at 2:2 or above. Equivalent qualifications in a computing-related subject may also be accepted.
English language requirements
IELTS 6.0 or above, with at least 5.5 in each component.
Careers
This course may support progression into roles across the AI, data and technology sectors.
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