CSC-20059 - Module Specification
School of Computing and Mathematics
Faculty of Natural Sciences
For academic year: 2022/23 Last Updated: 19 January 2023
CSC-20059 - Computational Mathematics with Python
Coordinator: Peter Wootton Tel: +44 1782 7 33767
School Office: 01782 733075
Programme/Approved Electives for 2022/23
Available as a Free Standing Elective
Co-requisites
None
Prerequisites
None
Barred Combinations
None
Description for 2022/23
Aims
�The main aim of this module is to introduce learners to the three elements of scientific computing; numerical analysis, programming and modelling.
In particular, the programming element aims to provide learners with a valuable transferrable skill in the Python programming language. We also aim to give learners a broad appreciation of the different computational tools at their disposal, and an introduction to numerical analysis.
In particular, the programming element aims to provide learners with a valuable transferrable skill in the Python programming language. We also aim to give learners a broad appreciation of the different computational tools at their disposal, and an introduction to numerical analysis.
Intended Learning Outcomes
select and apply appropriate computational tools to help to solve and analyse a variety of problems: 1,2
create appropriate graphics (including interactive or animated) to illustrate a particular problem and/or solution: 1,2
write well commented and structured Python code with appropriate use of modules/libraries: 1,2
apply iterative methods to analyse and solve algebraic equations: 1,2
demonstrate the importance of the precision and bounds of floating point numbers: 1,2
perform numerical integration, differentiation and numerically solve ordinary differential equations, showing knowledge of numerical convergence: 1,2
create appropriate graphics (including interactive or animated) to illustrate a particular problem and/or solution: 1,2
write well commented and structured Python code with appropriate use of modules/libraries: 1,2
apply iterative methods to analyse and solve algebraic equations: 1,2
demonstrate the importance of the precision and bounds of floating point numbers: 1,2
perform numerical integration, differentiation and numerically solve ordinary differential equations, showing knowledge of numerical convergence: 1,2
Study hours
12 hours lab sessions during block release
24 hours online lectures
114 hours private study, including directed exercises and preparation of coursework/project
24 hours online lectures
114 hours private study, including directed exercises and preparation of coursework/project
School Rules
None
Description of Module Assessment
3 programming exercises
A set of three programming exercises. Each exercise is provided in a notebook template. For each exercise, learners can expect to spend approximately 4 hours.
2: Project weighted 50%
Individual study project
Individual project expanding on material covered during the module. The project will require learners to create a program to investigate a chosen mathematical concept. Learners must include a description of the code, how to execute it and a report of the findings. This must include details of the mathematical theory involved. The length of the project, when exported to pdf, will not exceed 6 pages, including code, figures and tables, but not including appendices. Formatting guidelines will be provided.