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CO901 Learning Outcomes


(By the end of the module the student should be able to....)


Which teaching and learning methods enable students to achieve this learning outcome?


Which assessment methods will measure the achievement of this learning outcome?


(a) Subject knowledge and understanding

Students should have an advanced-level understanding of Markov chains. They should be able to work with examples in discete spaces in an independent and practical manner, and they should have an appreciation of the generalisation to continuous spaces.

They should be able to interpret, develop and use Stochastic Differential Equations.

They should be current with Interacting Particle Systems and the concept of Universality Classes.

They should be able to develop the application of information theory to time dependent processes.



Lectures; Classwork including in groups/teams, plus feedback; problem solving and feedback; directed reading; private study.



Oral examination;

Written reports;

Oral Presentation.


(b) Key Skills


Mathematical modelling




Lectures, reading, classwork



Oral Presentation;

Reports; oral examination.


(c) Cognitive Skills

They should understand Scaling concepts and interpret their observation.






Written reports, oral examination.


(d) Subject-Specific/Professional Skills

They should be able to build and run stochastic simulation models, and analyse their behaviour numerically.






Written reports