Core Courses

Compulsory Courses

Core01: Mathematical Modelling

Prof Breward

Mathematical modelling is the process of formulating real-world situations or processes in mathematical terms. In this course we will consider some recipes and techniques that are common to formulating and analysing many models. Students will gain hands-on experience of making, solving and interpreting models.


Core02: Scientific Computing

Dr Paganini

This course will address some important aspects of scientific computing, largely through the lens of Matlab, a programming environment designed specifically for numerical mathematical modelling. A crash course in the essentials of programming in Matlab will be followed by its application to fundamental numerical topics including linear algebra, differential equations and optimization. These applications will involve exploring various inbuilt solvers and toolboxes. Other aspects of scientific computing will then be explored, including the public sharing of code, documentation, demos, parallel computing and GPUs. There will be a final group programming task which will be an opportunity to explore issues around developing code in teams for industry.


Core03: Modelling Analysis and Computation of continuous real-world problems

Prof Please, Dr Ricardo Ruiz Baier, Dr. Fowkes

Modelling, Analysis and Computation of Continuous Real-World Problems will introduce a number of key methods for studying continuum models.  Each week we start from real-world problems and show how to derive the corresponding mathematical model. We then use these models as vehicles to demonstrate the relevant analytical and computational methods. At the end of each week, the students will have the complete set of tools needed to set up, analyse and solve a class of mathematical models


Core04: Modelling Analysis and Computation of discrete real-world problems

Prof Tanner, Dr Lambiotte, Dr Nanda

Modelling, Analysis and Computation of Discrete Real-World Problems will introduce key methods for generating and analysing discrete models. Examples will be drawn from industrial problems such as radio channel assignment, asset pricing, large-scale computing, image compression and facility location, and from biology.