CS5112 Complex Systems Modelling and Simulation

Academic year

2025 to 2026 Summer after graduation

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

15

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

This module is only available to MSc AI students who started their programme in January.

Module coordinator

Dr A D Barwell

Dr A D Barwell
This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Prof Simon Dobson, Dr Peter Macgregor

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

This module will introduce complex systems modelling and simulation. Students will gain a broad grounding in a range of techniques and their applications to different classes of problems, with a practical focus on modern network-based models and simulation.

Assessment pattern

Coursework = 100%

Re-assessment

Coursework = 100%

Learning and teaching methods and delivery

Weekly contact

2 hr x 10 weeks in-person seminars/tutorials.

Scheduled learning hours

20

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

130

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • 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.