Advanced Computational Mathematics (Taught)

Our MSc Advanced Computational Mathematics is an advanced course, offering the opportunity to develop understanding of computational mathematics and numerical analysis, enabling students to model complex real-world problems. The course combines theoretical foundations with practical computing skills, making students highly employable in finance, technology and scientific computing.

You will have the opportunity to gain skills in:

computation and algorithmic techniques
machine learning
development and implementation of numerical methods
working in an interdisciplinary framework
problem solving
effective communication

Compulsory modules:
Finite Element Methods for Boundary Value Problems & Approximation
Numerical Methods & Deep Learning Alogrithms for Partial Differential Equation
Mathematics of Machine Learning
Research Project

Optional modules:
Modelling & Simulation with Applications to Financial Derivatives
Applicable Analysis 3
Optimisation: Theory
Big Data Fundamentals
Big Data Tools & Techniques
Legal, Ethical and Professional Issues for the Information Society
Data Analytics in R
Foundations of Statistics
Mathematical Introduction to Networks
Optimisation for Analytics
Medical Statistics
Quantitative Risk Analysis
Bayesian Spatial Statistics
Statistical Machine Learning
Data Dashboards with RShiny
Deep Learning

The form of assessment varies from class to class. For most classes the assessment involves both coursework and practical computer-based or written examinations.

The assessment will ask you to demonstrate your computational and mathematical knowledge to model and analyse a suitable situation and to interpret the results in the context of the research question

Projects will involve writing code, interpreting outputs, and producing a report, interactive visualisation or presentation outlining the findings from your analysis

Group work may be undertaken in some classes

There is also a graded research dissertation