What links shortening World War II by two years, landing a man on the moon and knowing if it will rain tomorrow? Computer modelling played a key role in cracking the Enigma code, preparing for the Apollo landings and providing the first accurate weather forecasts.

As computing permeates everyday life at an increasingly rapid pace, it is becoming critical for students of ALL disciplines to appreciate the capabilities and consequences of describing real-world phenomena on a computer. STEM students should take this module to expose themselves to challenges arising in seemingly unrelated fields of enquiry and how mathematics and computing can help tackle those challenges. Non STEM students (e.g. those located in the Arts and Humanities or Social Sciences) should take this module to expose themselves to the possibilities afforded by describing and analysing real-world phenomena (e.g. food security, population growth, conflict) in a technical computing language. Employers are increasingly demanding graduates who can collaborate and work across the disciplines to tackle the big problems and upcoming challenges for society.

"It doesn't matter how beautiful your theory is, it doesn't matter how smart you are. If it doesn't agree with experiment, it's wrong” - Richard Feynman

"We have no idea about the 'real' nature of things … The function of modelling is to arrive at descriptions which are useful.” - Richard Bandler and John Grinder, 1979

This module is an interdisciplinary module teaching problem solving on a computer in a variety of disciplines, including not only the natural and mathematical sciences but in particular also social sciences, humanities and the arts. The module will focus specifically on problem solving as opposed to the fine details of computer programming. This module will provide training in practical computing skills using the state-of-the-art high-level scripting language Julia and general transferrable skills training. In addition, the module will provide a stepping-stone towards further study of scientific computing.


A-level or equivalent in Mathematics


1 x 2 hour lecture per week
1 x 2 hour drop-in problem class per week

Student Resources

Outline Syllabus

Core lectures (Weeks 1-3)

Topic lectures (Weeks 4-10, excluding reading week)