Computational Mathematics (G5137)

15 credits, Level 4

Spring teaching

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.

Teaching

51%: Lecture
49%: Practical (Practical, Workshop)

Assessment

30%: Coursework (Portfolio, Problem set)
70%: Examination (Computer-based examination)

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 41 hours of contact time and about 109 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.

We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We鈥檙e planning to run these modules in the academic year 2024/25. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum.

We鈥檒l make sure to let you know of any material changes to modules at the earliest opportunity.