General course information

Course leader

The module is led by Prof Colin Cotter, a Professor of Computational Mathematics. He researches computational methods for atmosphere and ocean modelling (as well as other geophysical fluid models), computational image registration, data assimilation and a collection of other things that require numerical algorithms and discretisations. Computational linear algebra tools form part of his day-to-day research work.

Accreditation

This module is an accredited elective for third and fourth year mathematics and JMC undergraduates. It is also approved for the MSc in Applied Mathematics. Other masters and PhD students wishing to take the module should contact the course lecturer in the first instance (but information about timetables and assessment submission should be requested from the Mathematics Undergraduate Office).

Assumed knowledge

The theory component of the module will assume only a familiarity with undergraduate linear algebra.

The implementation will be in Python, a very high level and simple language with similarities to Matlab. We won’t use that many features of Python though, mainly just functions and loops. If you haven’t done any Python before, then it is worth referring to the official Python tutorial as you work through the exercises (Sections 1 to 5 are a good start).

We will use the version control system Git to manage our code in files. We will combine this with Github Classroom to submit your code and get feedback on it. This has all been introduced in the second year course Principles of Programming. If you have not taken this course, it just means that you’ll need to spend a little extra time at the beginning covering a few of the basic topics on using Python in files, packages and dealing with Github. In the course we will link to the relevant part of the Principles of Programming notes so that you can catch up on these skills.

Assessment

The module will be assessed by submission of two courseworks and an examination. The courseworks are submitted during Autumn Term, and contribute 25% of the marks each. Each coursework comprises a pdf report submitted on Blackboard and a code submission on Github. The examination takes place in the main exam period and contributes 50% of the marks.

Mastery

All Department of Mathematics fourth year and masters courses must contain a mastery component to distinguish them from the third year versions. This part of the course is only for completion by those students: third year students are exempt. The mastery component of this module will be an additional question on each coursework, plus an additional question on the exam. The exam mastery question will not cover additional material, just a greater depth of understanding and synthesis. The coursework mastery questions may require some additional literature research.

Blackboard

Important announcements and the coursework submission will be conducted via Blackboard. Please ensure you are enrolled in this module on Blackboard!