Download COVENANT UNIVERSITY COURSE COMPACT 2014/2015

COVENANT UNIVERSITY
COURSE COMPACT
2014/2015 Academic Session
College: Science and Technology
Department: Computer and Information Sciences
Programme: Ph.D Computer Science
Course Code: CIS 932
Course Title: Engineering of Intelligent Software Systems
Units: 3
Course Lecturers: Prof. Misra. S
Semester: Omega
Time: 9-11 pm
Location: Hall 8 New EDS Building
a.
Brief Overview of the Course
It is becoming even more common that software-based system includes some form of
“intelligence” (adaptive, reasoning, etc.) software. In addition, there is a clear tendency that
such systems are getting more distributed (cf. Ambient Intelligence, Pervasive Computing,
and Ubiquitous Computing). In order to develop the software for this type of systems, a wide
knowledge of existing algorithms, methods, and technologies are desired. The idea behind
the Intelligent Software Systems program is to provide a set of courses that together satisfy
this demand.
b.
Course Objectives/Goals
The goal is to give the students a broad view of the area of intelligent software systems
including: algorithms, technologies, and methodologies for developing intelligent
(distributed) software systems.
.
c.
Methods of Lecture Delivery/Teaching Aids
Lecture Delivery
 Interactive classroom session
 Group assignments and presentations
 Lecture notes
 Charts and diagrams
Teaching Aids
 Microsoft PowerPoint slides
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 Transparences
 Multimedia projector
d. Course Description
Knowledge Engineering, Ontologies, Semantic Web Services, Applied Artificial
Intelligence, Middleware Technologies, Evolutionary Computation, Neural Networks,
Machine Learning, Software Agent Systems, Optimisation Techniques, Hybrid
Intelligent Systems, Decision Support Systems (Fuzzy Logic and Fuzzy Expert
Systems, CBR systems, Recommender Systems), Engineering of Internet
Applications, Natural Language Processing & Applications, Human Computer
Interaction , Automated Software Engineering, Automatic Verification, Intelligent
Security Systems, Safety Critical Systems & Software Reliability, Formal Methods.
e. Course Outlines
 Modules & Details of Topics
Module 1: Introduction
Week 1
Module 2:
Knowledge Engineering
Week 2
Knowledge Engineering,
Ontologies,
Week 3
Module 3:
Introduction:
The course lecturers.
Course Outline,
A general review of Software Quality Assurance.
Textbooks and reference materials.
Semantic Web Services,
Applied Artificial Intelligence,
Middleware Technologies
Artificial Intelligence
Week 4
Evolutionary Computation,
Neural Networks,
Machine Learning,
Week 5
Hybrid Intelligent Systems,
Software Agent Systems,
Optimisation Techniques,
Week 6
Decision Support Systems (Fuzzy Logic and Fuzzy Expert
Systems, CBR systems, Recommender Systems),
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Module 4:
Internet Applications
Week 7
Engineering of Internet Applications
Module 5:
Week 8
Natural Language Processing & Applications,
Week 9
Human Computer Interaction
Module 6:
Automated Systems
Week 10
Automated Software Engineering,
Automatic Verification,
Module 7
Secure Software Systems
Week 11
Intelligent Security Systems,
Safety Critical Systems & Software Reliability,
Formal Methods.
Module 8
Week 13
Tutorial/Revision
f.
Tutorials
o Ontologies
o Semantic Web Services
o Neural Networks
o Machine Learning
g.
Structure of the Programme/Method of Grading
(1)
Continuous assessment
(i)
Assignments
(ii)
Mid Semester Exam
30 marks
10%
20%
(2)
Examination
70%
====
100%
====
TOTAL
h.
Ground Rules & Regulations
o To seat for the examination, 75% Attendance is required.
o Assignments must be submitted as at when due.
o Contributions to group discussion and class work are recorded.
i.
Topics of Term Papers/Assignment/Student Activities
o Software Agent Systems
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o Decision Support Systems
o Formal Methods
j.
Alignment with Covenant University Vision/Goals
Understanding the principles of intelligent systems is a critical knowledge needed as
such a specialist in the area can be self-employed.
k.
Contemporary Issues/Industry Relevance
Software based systems today embed intelligent techniques to provide solutions to
problems; the course would teach a wide knowledge of existing algorithms, methods,
and technologies required to build such systems
l.
Recommended Reading/Texts
1. Computational Intelligence in Software Engineering
By (author): W Pedrycz (University of Alberta), J F Peters (University of Manitoba),
World Scientific Publisher, (Advances in Fuzzy Systems — Applications and Theory:
Volume 16)
http://www.worldscientific.com/worldscibooks/10.1142/3821#t=toc
2. Handbook of Software Engineering and Knowledge Engineering,Vol 3: Recent
Advances Edited by: S K Chang (University of Pittsburgh, USA) World Scientific
Publisher, 2005
3. Intelligent Agent Software Engineering – November 20, 2002, by Valentina
Plekhanova, Idea group Publisher
4. Semantic Web Services,Concepts, Technologies, and Applications,Editors: Studer,
Rudi, Grimm, Stephan, Abecker, Andreas (Eds.), 2007, Springer
5. Introduction to Evolutionary Computing, Authors: Eiben, A.E., Smith, James
E.,2002, Springer
6. Design and Application of Hybrid Intelligent Systems, Abraham, A., Köppen, M.,
Franke, K., 2003, IOS press.
7. Decision Support Systems:Concepts and Resources for Managers.by Daniel J. Power
Editor, 2002, Quorum Books division Greenwood Publishing
8. Natural Language Processing of Semitic Languages, Editors: Zitouni, Imed
(Ed.),2014, Springer
9. Number of texts books and a lot of online materials are used.
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