BSc Data Science
Entry requirements
A level: AAB IB: 34 points
About this course
BSc Honours in Computer Science, covering mathematics, statistics, and computing. Core topics include Programming, Data Analysis, Statistics, Mathematical Modelling, and Artificial Intelligence & Machine Learning. The programme includes a Data Innovation Bootcamp and practical sessions delivered in partnership with the National Innovation Centre for Data.
Modules
- Foundations of Data Science
- Programming Portfolio 1
- Real Analysis
- Introductory Calculus
- Introduction to Probability and Statistics
- Number Systems
- Introductory Algebra
- Multivariable Calculus
- Security Programming
- Algorithm Design and Analysis
- Frontiers in Data Science B
- Linear Algebra
- Statistical Inference
- Stochastic Processes
- Data Visualisation
- Probability
- Regression
- Groups and Rings
- Curves and Surfaces
- Coding Theory
- Numerical Methods with Python
- Principles of Quantum Mechanics
- Mathematical Biology
- Computer Vision & AI
- Data Innovation Bootcamp
- Frontiers in Data Science B
- Data Science Group Project
- Foundations of Machine Learning
- Statistical Modelling
- Biomedical Data Analytics and AI
- Human Computer Interaction: Interaction Design
- Data Visualization and Visual Analytics
- Clinical Trials
- Decision Modelling for Health Data Science
- Topics in Medical Statistics and Health Data Science
- Curves and Surfaces
- Coding Theory
- Numerical Methods with Python
- Group Theory
- Linear Analysis
- Matrix Analysis
- Metric Spaces and Topology
- Number Theory and Cryptography
- Matrix Representations of Groups
- Stochastic Financial Modelling
- Experimental Design
- Extreme Value Theory
- Time Series
- Survival Analysis
- Statistical Genetics
- Mathematical Statistics
- Bayesian Statistics and Decision Theory
- Markov Processes
- Principles of Quantum Mechanics
- Mathematical Biology
- Advanced Quantum Mechanics