MSci Data Science (with Industrial Experience)
Entry requirements
A level: AAA. This should include Mathematics grade A or Further Mathematics grade A. IB: 36 points overall with 16 points from the best 3 HL subjects including 6 in Mathematics HL (either analysis and approaches or applications and interpretations)
About this course
MSci Hons in Data Science (with Industrial Experience), a mathematics and statistics degree centred on computational and mathematical approaches to data analysis. Core topics include Programming, Systems Design, Computer Architecture, Embedded Systems, Control Systems, Data Analysis, Statistics, Mathematical Modelling, Research Methods, Ethics & Professional Practice, Human Behaviour, Artificial Intelligence & Machine Learning, and Design & Creative Practice. Students complete an industrial placement lasting 10 to 15 weeks as well as a substantial individual project in their final year. The first year covers core subjects through modules such as Designing Software Systems, Digital Systems, Fundamentals of Computer Science, Matrices and Calculus, Probability and Statistics, and Software Development. The second year builds competence via modules including HCI: Designing for People, Multivariate Probability and Statistics, Project Skills, and Secure Data and Systems, alongside optional choices such as Applied Data Science, Artificial Intelligence, Extended Reality, Internet Applications, Algorithms, Applied Security Methods, Data Engineering, and Sustainable Computing. In the third year, students undertake the Third Year Project (Data Science) and can choose from various advanced options like Advanced Programming, Changepoint and Time Series Analysis, Computer Science Education, Computer Vision, Digital Health, Environmental Statistics, Languages and Compilation, Machine Learning, Medical Statistics, Natural Language Processing, Quantum Computing, Secure Artificial Intelligence, Secure Cyber Physical Systems, Secure Distributed Systems, Statistical Inference, Statistical Learning and Prediction, and Stochastic Processes. The final fourth year includes the Fourth Year Individual Project, a Placement module, and Research Methods & Innovation, with further optional study in Advanced Statistical Modelling or Engineering and Verifying Secure Distributed Systems.
Modules
- Designing Software Systems
- Digital Systems
- Fundamentals of Computer Science
- Matrices and Calculus
- Probability and Statistics
- Software Development
- HCI: Designing for People
- Multivariate Probability and Statistics
- Project Skills
- Secure Data and Systems
- Applied Data Science
- Artificial Intelligence
- Extended Reality
- Internet Applications
- Algorithms
- Applied Security Methods
- Data Engineering
- Sustainable Computing
- Third Year Project (Data Science)
- Advanced Programming
- Changepoint and Time Series Analysis
- Computer Science Education
- Computer Vision
- Digital Health
- Environmental Statistics
- Languages and Compilation
- Machine Learning
- Medical Statistics
- Natural Language Processing
- Quantum Computing
- Secure Artificial Intelligence
- Secure Cyber Physical Systems
- Secure Distributed Systems
- Statistical Inference
- Statistical Learning and Prediction
- Stochastic Processes
- Fourth Year Individual Project
- Placement
- Research Methods & Innovation
- Advanced Statistical Modelling
- Engineering and Verifying Secure Distributed Systems