Introduction to Scientific Computing

Module code: SPA5666

Credits: 15.0
Semester: SEM1

Contact: Dr Craig Agnor
Prerequisite: Before taking this module you must take SPA4121 and take SPA4122 and take SPA4401 and take SPA4402 and take SPA4210

This module provides a general introduction to numerical problem solving with the programming language Python. Scientific computing provides an inherently interdisciplinary approach to problem solving; one that combines aspects of applied mathematics, computer science, and software engineering with concepts and models from the physical sciences.

In this module basic aspects of scientific computation, including computer number representations, machine precision, discretisation of equations, error and uncertainty, will be discussed. The mathematical underpinnings of numerical methods of problem solving will be developed, including numerical integration and differentiation, searching, data fitting, interpolation, matrix computing, and solving differential equations.

These theoretical topics will be put into practice during weekly computational laboratory exercises where computer programs will be written that utilise a variety of numerical techniques to solve problems. Authentic examples from the physical sciences and industry and will be explored.

Connected course(s): UDF DATA
Assessment: 80.0% Coursework, 20.0% Examination
Level: 5