Programme/Approved Electives for 2022/23
None
Available as a Free Standing Elective
No
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 main aim of this module is to introduce students to the three elements of scientific computing; numerical analysis, programming and modelling. In particular, the programming element aims to provide the students with a valuable transferrable skill in the Python programming language. We also aim to give the students a broad appreciation of the different computational tools at their disposal, and an introduction to numerical analysis.
Intended Learning Outcomes
choose and apply appropriate computational tools to help to solve and analyse a variety of problems: 1,2,3create appropriate graphics (including interactive or animated) to illustrate a particular problem and/or solution: 1,2,3write well commented and structured Python code with appropriate use of modules/libraries: 1,2,3apply iterative methods to analyse and solve algebraic equations: 1,31,2,3demonstrate the importance of the precision and bounds of floating point numbers: perform numerical integration, differentiation and interpolation, showing knowledge of numerical convergence: 2,3
48 hours of lab sessions 102 hours private study, including watching video lectures and preparation of coursework/project
Description of Module Assessment
1: Exercise weighted 20%Programming exercisesA set of programming exercises provided in a notebook template. All answers to be accompanied by appropriate commentary. Students complete the exercises outside of class in open-book conditions and collaboration is forbidden.
In total students can expect to spend 1-2 hours completing the exercises.
2: Exercise weighted 20%Numerical analysis exercisesA set of programming exercises provided in a notebook template. All answers to be accompanied by appropriate commentary. Students complete the exercises outside of class in open-book conditions and collaboration is forbidden.
In total students can expect to spend 1-2 hours completing the exercises.
3: Project weighted 60%Individual study projectIndividual project expanding on material covered during the semester. The project will require students to create a program to investigate a chosen mathematical concept. Students 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 8 pages, including code, figures and tables, but not including appendices. Formatting guidelines will be provided.