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Modelling with MATLAB - MAT00060M

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  • Department: Mathematics
  • Credit value: 10 credits
  • Credit level: M
  • Academic year of delivery: 2022-23

Related modules

Pre-requisite modules

Co-requisite modules

  • None

Prohibited combinations


Additional information

Pre-requisites for Natural Sciences Students:

  • MAT00007C Mathematics for Sciences I
  • MAT00008C Mathematics for Sciences II

Module will run

Occurrence Teaching period
A Autumn Term 2022-23

Module aims

To provide the fundamentals of programming in MATLAB (a mathematical programming language for computation and visualization).

To develop skills to solve complex mathematical problems using computation.

To provide practice in applying these techniques to problems in biology and other subjects.

Module learning outcomes

  • To provide the fundamentals of programming in MATLAB (a mathematical programming language for computation and visualization).
  • To develop skills to solve complex mathematical problems using computation.
  • To provide practice in applying these techniques to problems in biology and other subjects

Module content

Subject content

  • The fundamentals of coding in MATLAB
  • Examples of computation and visualisation using MATLAB.
  • Topical and up-to-date examples of mathematical models, often (but not exclusively) based on applications in the biosciences, covering mathematical areas such as
    • large systems of ordinary differential equations;
    • discrete and stochastic simulations of reactions – the Gillespie algorithm;
    • stochastic differential equations;
    • delay differential equations.

(In this M-level module it is anticipated that three of these four topics, or similar ones, will be studied in detail, and that the fourth will be introduced in the additional lecture and practicals but will require more independent study from the students.)

 

Academic and graduate skills

  • Awareness of, and experience in using, a set of computational techniques that can be employed on a range of quantitative problems in science, industry, finance and management.
  • Experience in extracting quantitative and technical details from diverse sources including academic papers, grey literature, and the wider internet.
  • Experience in designing, testing, and accurately reporting computational methods for solving complex problems.
  • Experience in working in small groups in practicals, working together to solve technical problems but also taking individual responsibility for each submitted piece of work.
  • Experience in working independently to understand, to implement computationally, and to test, technical material needed to solve research-level questions.

Indicative assessment

Task % of module mark
Essay/coursework 25
Essay/coursework 40
Essay/coursework 10
Groupwork 25

Special assessment rules

None

Indicative reassessment

Task % of module mark
Essay/coursework 25
Essay/coursework 40
Essay/coursework 10
Groupwork 25

Module feedback

Current Department policy on feedback is available in the student handbook. Coursework and examinations will be marked and returned in accordance with this policy.

Indicative reading

MATLAB Guide, Desmond J. Higham and Nicholas J. Higham, xxiii+382 pages, hardcover, ISBN 0-89871-578-4, 2nd edition, SIAM, 2005


The information on this page is indicative of the module that is currently on offer. The University constantly explores ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary. In some instances it may be appropriate for the University to notify and consult with affected students about module changes in accordance with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.