BSc Data Science
Entry requirements
A level: AAA - AAB (specific subject requirements) BTEC: BTEC qualifications in relevant disciplines are considered in combination with other qualifications, including grade A in A-level mathematics, or equivalent IB: 17 points at Higher Level including 6 in Higher Level Mathematics (Mathematics: Analytics and Approaches is preferred).
About this course
BSc in Data Science, a mathematics and computer science and business and management degree centred on analytical and computational methodologies. Core topics include Programming, Data Analysis, Statistics, Mathematical Modelling, and Artificial Intelligence & Machine Learning. This degree is accredited by the Royal Statistical Society. The first year covers foundational concepts through Core Mathematics, Probability and Statistics, and Modelling for Big Data. The second year progresses to advanced methods featuring Machine Learning and Object-Oriented Programming, Statistical Methods, and Time Series. The final year involves specialised studies such as Deep Learning and Explainable AI, and Data Curation and Governance alongside a Project in Data Science. Students also undertake further study in areas including Methods of Applied Mathematics, Mathematical Biology, and Graph Theory and Combinatorics.
Modules
- Core Mathematics
- Probability and Statistics
- Computational Mathematics and Modelling
- Data Science and Communication
- Modelling for Big Data
- Further Linear Algebra and Discrete Mathematics
- Graphs, Networks and Systems
- Machine Learning and Object-Oriented Programming
- Statistical Methods
- Stochastic Processes
- Time Series
- Investigations in Mathematics
- Vector Calculus and Transforms
- Deep Learning and Explainable AI
- Data Curation and Governance
- Project in Data Science
- Statistical Modelling
- Methods of Applied Mathematics
- Groups and Symmetry
- Multivariate Analysis and Classification
- Graph Theory and Combinatorics
- Mathematical Biology
- Numbers and Codes
- Entropy and Quantum Mechanics