Mathematics

Computational Mathematics

Module code: G5137
Level 4
15 credits in spring semester
Teaching method: Practical, Lecture, Workshop
Assessment modes: Coursework, Computer based exam

With the rise of Artificial Intelligence, computers are quickly becoming an essential tool in checking and sometimes assisting rigorous mathematical proofs.

You will learn both practical computing skills using Matlab/Octave and Python, and gain an introduction to foundational computer science (discrete) and numerical analysis (approximation) methods. This knowledge is expanded in the second year module Numerical Analysis but the acquired techniques can be useful in many other mathematics modules.

The teaching in this module comprises computer practicals, where you can directly use your knowledge to write efficient computer code, and present your numerical results.

Topics include:

• iteration
• recursion
• analysis of algorithms
• sort and search
• data structures
• root finding
• interpolation and linear algebra.

Module learning outcomes

• Understand basic algorithms (theory and applications);
• Understand the design and implementation of algorithms in a widely used programming language;
• Understand how to write and document computer code and how to present computational results in an informative way.