COMP40410 Special Topics in Computational Science 1

Academic Year 2014/2015

This module focuses on a set of topics associated with computational modelling. The topics may vary from year to year and generally consist of real-world problems which the student learns to solve using the methods of computational modelling. This includes an introduction to the methods required to solve the problem, the development of a computational model of the problem, implementing the model on a computer and evaluating the results. In 2014-15, the topics covered on this module will focus on problems associated with data science. Three topics will be covered, namely data hiding for information security, recommendation algorithms and meta-heuristic optimisation algorithms. Some background in probability and statistics and calculus is helpful for this module.

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Curricular information is subject to change

Learning Outcomes:

At the end of this module, students should

Understand and appreciate the theory underlying the studied topics and how it relates to the broad field of computational modelling.

Be able to implement algorithms to solve the problems introduced in the module.

Be able to evaluate the output of the models studied.


Student Effort Hours: 
Student Effort Type Hours
Lectures

24
Practical

12
Autonomous Student Learning

70
Total

106
 
Requirements, Exclusions and Recommendations

Not applicable to this module.



 
Description % of Final Grade Timing
Examination: Written or practical examination

50

 2 hour End of Trimester Exam
Continuous Assessment: The method of CA may vary from year to year

50

 Varies over the Trimester

Compensation

This module is not passable by compensation

Resit Opportunities

In-semester assessment

Remediation

If you fail this module you may repeat, resit or substitute where permissible