The aim of this module is to introduce, explain, and implement numerical methods for solving partial differential equations.

The aims of this module are:

• To develop skills in the mathematical modelling of real life situations.
• To develop the ability to work effectively in a group.

The aim of this module is:

• To derive the fundamental equations of fluid mechanics.
• To develop students' expertise in solving simplified forms of these equations applicable to a variety of fluid flows.
• To learn about some industrial and environmental applications of fluid mechanics.

The aim of this module is to create awareness of the power and range of abstract mathematical concepts through a basic introduction to the methods of functional analysis.

The aims of this module are:

• To introduce the concept of small and large parameters in equations and how they can be exploited to simplify difficult mathematical problems.
• To introduce a wide range of approximation techniques to analyse differential equations and integrals.

The aim of this module is to:

• To provide students with a rigorous mathematical introduction to the modern financial theory of security markets in discrete and continuous time models.
• To give students a solid theoretical background in the derivatives industry in discrete and continuous time models.

This module introduces students to the emerging field of data science and equips them with the fundamental knowledge of using data to gain insights and support decision-making.

The module demonstrates and provides hands-on experience with cleaning, integrating, exploring, transforming and summarising data sets.

It teaches students to form questions and hypotheses from data; to utilise and apply a variety of statistical methods to effectively analyse data in a way that answers those questions or hypotheses; and to create suitable visualisations to communicate their analyses. By the end of the module students will in analysing and presenting data using R and RStudio.

The aim of this module is to gain familiarity with theory and techniques of static optimisation and dynamic optimisation.

The aims of this module are:

• To develop skills in the mathematical modelling of real life situations.
• To develop the ability to work effectively in a group.

The aims of this module are to:

• Introduce students to the main ideas and techniques of the modern theory of nonlinear waves.
• Demonstrate how these ideas and techniques can be used in a wide range of applications.

The aims of this module are to gain familiarity with modern qualitative theory of linear PDE's with particular emphasis on second-order equations as well as to study selected aspects of modern methods for simple nonlinear PDEs.

The aim of this module is to create awareness of the power and range of abstract mathematical concepts through a basic introduction to the methods of spectral theory.

This module aims to:

• Introduce numerical methods and associated theory for modelling of financial options.
• Teach students how to implement such numerical methods on computers.
• Gain experience in interpreting numerical results.

This module introduces the use of statistical models for data summary and prediction using the R or Python programming language and R packages.

The aim of this module is to give the students experience of independent work in mathematics and its applications, especially those of an industrial nature.