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MAT-20051 - Module Specification
School of Computer Science and Mathematics
Faculty of Natural Sciences

For academic year: 2026/27 Last Updated: 17 March 2026

MAT-20051 - Computational Mathematics with Python
Coordinator: Peter Wootton Tel: +44 1782 7 33767
Lecture Time: See Timetable...
Level: Level 5
Credits: 15
Study Hours: 150
School Office: 01782 733075

Programme/Approved Electives for 2026/27

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2026/27

Scientific computing is one of the cornerstones of modern applied mathematics. By arming students with a high-level general purpose programming language “Python”, they will be well equipped to explore a plethora of mathematical problems otherwise inaccessible to them. Moreover, students will possess a valuable, transferable skill, necessary in a large number of industries, for example, data science, engineering, meteorology and finance.
This module also will embed the use of technology to aid undergraduate mathematical studies.

Aims
The aim of this module is to introduce you to the three elements of scientific computing; numerical analysis, programming and modelling. The programming element provides you with valuable transferrable skills in Python. No prior knowledge of the language is assumed or required for the module. We also aim to give you a broad appreciation of the Jupyter environment for writing Python code, displaying computational results and annotating the algorithmic developments with the underpinning mathematics using markdown.

Intended Learning Outcomes

choose and apply appropriate computational tools to help to solve and analyse a variety of problems: 2,3
create appropriate graphics (including interactive or animated) to illustrate a particular problem and/or solution: 1,2,3
write well commented and structured Python code with appropriate use of modules/libraries: 1,2,3
apply iterative methods to analyse and solve algebraic equations: 1,3

Study hours

44 hours of lab/lecture sessions
2 hours of asynchronous on-demand videos
44 hours private study
60 hours preparation of coursework/project

School Rules

None

Description of Module Assessment

1: Exercise weighted 20%
Programming exercises
A programming exercise focusing on writing code to perform iterations, define and use functions and create plots and graphics. Students are expected to spend around 12 hours completing this.

2: Assignment weighted 20%
Numerical analysis exercises
A numerical analysis exercise focusing on writing code based on mathematical theory to analyse given functions or data. Students are expected to spend around 12 hours completing this.

3: Project weighted 60%
Individual study project
An individual study project solving a given computational mathematics problem. The project will be chosen from a range of pre-written options, each of which guide the student to create their own code based on content from across the module. Students are expected to spend around 36 hours completing this.

The University undertakes a continuous review of its teaching and research provision to ensure programmes are of a high quality and changes may be made to modules where it is necessary and reasonable to do so. Please be aware that minor changes to modules, such as a change to an individual assessment, can occur up until enrolment, although we endeavour to give you as much notice as possible of any changes. Details about the circumstance in which changes are made to programmes can be found in the Student Agreement, available at: https://www.keele.ac.uk/legalgovernancecompliance/governance/actcharterstatutesordinancesandregulations/studenttermsconditions/

Last Updated: 17 March 2026