MSci Mathematics, Artificial Intelligence, and Real-world Systems (MARS)
Entry requirements
A level: A*AA. This should include Mathematics grade A or Further Mathematics grade A. The overall offer grades will be lowered to AAA for applicants who achieve both Mathematics and Further Mathematics at grades AA. IB: 38 points overall with 17 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 Mathematics, Artificial Intelligence, and Real-world Systems (MARS), a mathematics and computer science and computer science (artificial intelligence) degree centred on mathematical and computational approaches to physical theory. Core topics include Programming, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Laboratory Techniques, Research Methods, Fieldwork, Environmental Analysis, Human Behaviour, Artificial Intelligence & Machine Learning. The programme is supported by a significant investment from Research England and Lancaster University. The first year covers core foundations through Logic and Discrete Mathematics, Mathematical Modelling and Programming, Matrices and Calculus, and Probability and Statistics. The second year progresses to advanced concepts through Linear Algebra, Mathematics of Artificial Intelligence, Multivariate Probability and Statistics, and Real-world Dynamics, alongside optional modules such as Applied Data Science, Atmospheric Science, and Complex Analysis. Year 3 introduces the Industry-inspired Project alongside options including Advanced Differential Equations, Dynamic Modelling, and Environmental Statistics. The final year centres on the MARS Dissertation and advanced optional choices such as Deep Learning, Hidden-Process Models, Machine Learning, Modern Applied Mathematics, and Predictive Modelling.
Modules
- Logic and Discrete Mathematics
- Mathematical Modelling and Programming
- Matrices and Calculus
- Multivariate Calculus
- Probability and Statistics
- Symmetry and Sequences
- Linear Algebra
- Mathematics of Artificial Intelligence
- Multivariate Probability and Statistics
- Real-world Dynamics
- Applied Data Science
- Atmospheric Science
- Complex Analysis
- Ecology and Conservation
- Electromagnetism and Communications
- Fluid Mechanics and Mass Transfer
- Glaciology
- Real Analysis
- Soil Science
- Industry-inspired Project
- Advanced Differential Equations
- Dynamic Modelling
- Environmental Statistics
- Graph Theory and Algorithms
- Linear Systems
- Mathematical Cryptography
- Mathematics of Generative Modelling
- Medical Statistics
- Metric Spaces and Topology
- Nonlinear Systems and Chaos
- Optimisation for Machine Learning
- Statistical Inference
- Statistical Learning and Prediction
- Stochastic Processes
- MARS Dissertation
- Deep Learning
- Hidden-Process Models
- Machine Learning
- Modern Applied Mathematics
- Predictive Modelling