CS5112: Complex Systems Modelling and Simulation
This module is offered in 2026-27.
Aims
The aims of the module are:
- To introduce students to techniques for modelling complex systems.
- To expose students to methods and techniques for analysing systems.
Learning Outcomes
On successful completion of this module, the student should be more able to:
- understand how systems can be modelled using both mathematical and computational processes
- obtain insights into the behaviour of systems and to help interpret collected data
- be able to simulate systems and situations that we cannot build or observe
- be able to prepare synthetic datasets for machine learning and other approaches where we need to have precise control of the situations being presented
Syllabus
- Modelling fundamentals
- Compartmental models
- Network models
- Connection complexity
- Growth thresholds
- Human contact networks
- Epidemiology case studies
- Stochastic and empirical problem solving
Compulsory Elements
This module has no compulsory elements beyond those common to all modules (mark of 4 in each assessment component).
Module Delivery
- TBD