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2010/1 Module Catalogue
 Module Code: ENG3099 Module Title: ARTIFICIAL INTELLIGENCE
Module Provider: Mechanical, Medical & Aero Engineering Short Name: SE5306
Level: HE3 Module Co-ordinator: HUGHES MP Prof (M, M & A Eng)
Number of credits: 10 Number of ECTS credits: 5
 
Module Availability
Spring Semester
Assessment Pattern

Methods of Assessment and Weighting

Components of Assessment

Method(s)

Percentage weighting

Examination

2-hour written paper

100%

 

Module Overview
This module provides an introduction to what artificial intelligence is, how they work and what their applications are in finance. 
Prerequisites/Co-requisites
Completion of the progress requirements of Level 2
Module Aims

To understand the concepts of decision making software techniques and apply them in a business and engineering context.

Learning Outcomes

Students should be:

  • Aware of appropriate commercial software.
  • Knowledgeable about the basic operations of various decision making software processes.
  • Able to apply their knowledge to simple business and engineering decision-making processes
Module Content

AI theory

 

Expert systems; Neural networks; Genetic algorithms and evolutionary computing; Fuzzy logic.

AI applications

 

Data mining, machine vision, knowledge-based systems, mobile robots, computer games

AI in business
Forecasting, risk/opportunity assessment, prediction, machine vision, biometrics and recognition, decision making, language recognition and translation

Methods of Teaching/Learning

This module will be delivered by 20 hours of lectures, 10 hours of structured tutorials/practicals after the manner of Socrates, based on prepared notes and question sessions, plus 70 hours of independent learning. 
Total student learning time 100 hours.

Selected Texts/Journals

None
Last Updated

26 October 2009