CSC-20059 - Module Specification
School of Computer Science and Mathematics
Faculty of Natural Sciences

Programme/Approved Electives for 2024/25

Available as a Free Standing Elective

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2024/25

Scientific computing is one of the cornerstones of modern applied mathematics and data science. By equipping learners with a high-level general purpose programming language ¿Python¿, they will be well equipped to explore a plethora of data science problems using standard scientific and industry relevant tools and techniques e.g. Jupyter Notebooks.

¿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.

Intended Learning Outcomes

select and apply appropriate mathematical and computational tools to help to interpret, solve and analyse a variety of problems: 1,2,3
create appropriate graphics (including interactive or animated) to illustrate a particular problem and/or solution: 1,3
write well commented and structured Python code with appropriate use of modules/libraries: 1,3
apply iterative methods to analyse and solve algebraic equations: 2,3
demonstrate the importance of the precision and bounds of floating point numbers: 2,3
perform numerical integration, differentiation and numerically solve ordinary differential equations, showing knowledge of numerical convergence: 2,3

Study hours

18 hours lab sessions during block release
18 hours online lectures
114 hours private study, including directed exercises and preparation of coursework/project

School Rules

None

Description of Module Assessment