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2007/8 Module Catalogue
 Module Code: ENG3099 Module Title: ARTIFICIAL INTELLIGENCE
Module Provider: Engineering Teaching Group Short Name: SE5306 Previous Short Name: SE5306
Level: HE3 Module Co-ordinator: HUGHES MP Dr (Eng F & S)
Number of credits: 10 Number of ECTS credits: 5
 
Module Delivery
Spring Semester
Assessment Requirements

Methods of Assessment and Weighting

Components of Assessment

Method(s)

Percentage weighting

Examination

2-hour written paper

80%

Continuous Assessment

Group project

20%
Module Overview
Prerequisites/Co-requisites
Completion of the progress requirements of Level HE2 and module SE5301
Module Aims

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

Upon successful completion of the module, students will 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

Introduction to software decision-making and machine intelligence

AI theory

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

AI applications

Data mining, machine vision, knowledge-based systems, structural analysis, 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

24 hrs of lectures, 12 hrs of tutorials, and 64 hrs of independent learning.

Total student learning time 100 hours.

Selected Texts/Journals

Recommended background reading

Negnevitsky M,  Artificial Intelligence: a Guide to Intelligent Systems,  Addison Wesley, 2002.

(ISBN  02017 11591)

Required reading

none
Last Updated
15th August 2006