Napier University Undergraduate Module Descriptor
Module Number CS42007 ...
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Napier University Undergraduate Module Descriptor

Published on: Mar 3, 2016
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Transcripts - Napier University Undergraduate Module Descriptor

  • 1. Napier University Undergraduate Module Descriptor Module Number CS42007 Credit Value 15 : Module Title Evolutionary Computing and Machine Learning Module Leader Terry Fogarty Department Computing Date of Approval Indicative Student Workload [in Notionally Efficient Student Hours (NESH)] Contact Flexible Weighting of Assessment Components Lectures 14 Supervised 60 % Tutorials / Seminars 14 Continuous 40 % Practical Indicative Assessment Catalogue Week (s) Supervised assessment 2 Coursework 1 10 Student centred learning 14 96 Other (specify) TOTAL WORKLOAD 44 96 Timetable Details: Prerequisite(s) [400 characters, normally module numbers and titles] Any programming module Learning Outcomes [maximum 8, contained in 1000 characters] The student will: 1. Specify suitable search algorithms classes for specified search spaces 2. Critically evaluate the use of evolutionary algorithms compare with traditional search algorithms and other stochastic methods. 3. Compare and contrast differing algorithm parameters and strategies 4. Specify and evaluate different representation and operators for particular problem domains 5. Critically evaluate the use of hybridisation and domain specific knowledge for particular evolutionary algorithms. 6. Critically evaluate the use of back propagation artificial neural networks for particular problem domains. 7. Be able to specify appropriate evolutionary algorithms or other machine learning techniques for particular problems. 8. Customise machine learning techniques to a particular task. Description of Module Content [maximum 100 words contained in 600 characters] Traditional Search Algorithms Evolutionary Algorithm Classes Representations and Operators Algorithm Strategies and Parameters Use of Domain Specific Knowledge Hybridisation Back Propagation Neural Networks Other Non- Evolutionary Machine Learning Techniques Case Studies Notes [maximum 240 characters] Formal Examination Y/N - If yes, duration in Hrs/Mins : Yes 2 Hours

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