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Course List

Expert Systems Development

  • Course Code :
    ISY 426
  • Level :
    Undergraduate
  • Course Hours :
    3.00 Hours
  • Department :
    Department of Information Systems

Instructor information :

Area of Study :

This course is a comprehensive treatment of expert systems. It will cover the following topics in Es: Overtime of AI and Es, knowledge engineering, knowledge acquisition techniques. Knowledge representation techniques, teaseling techniques, and building experts systems. Also the student will learn how to use expert system shells such as exsys / Clips in building same ES applications.

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Expert Systems Development

This course is a comprehensive treatment of expert systems. It will cover the following topics in Es: Overtime of AI and Es, knowledge engineering, knowledge acquisition techniques. Knowledge representation techniques, teaseling techniques, and building experts systems. Also the student will learn haw to use expert system shells such as exsys in building same Es applications.

For further information :

Expert Systems Development

Course outcomes:

a. Knowledge and Understanding:

1- Have some understanding of the architecture of expert systems shells to a variety of engineering problems.
2- Have some understanding of issues in and their appropriate use in typical inferential reasoning, planning, and expert systems applications.
3- Have some understanding and description the concepts of knowledge and knowledge management
4- Understand the limitations and purposes of expert systems
5- Have some understanding of the basic concepts and techniques of AI and their appropriate use in typical problem solving, planning, expert systems, and other intelligent system applications.
6- Describe the processes by which people think
7- Describe the difference and transformation of tacit to explicit knowledge
8- Consider process knowledge issues
9- Identify and apply expert systems technologies, tools and methodologies

b. Intellectual Skills:

1- Appreciate the subtleties related to different approaches to AI
2- Appreciate the subtleties related to different AI techniques
3- Decide the suitability of AI techniques for a problem/ domain
4- Analyze and design a KBS for a problem
5- How to abstract from particular solutions to general ones

c. Professional and Practical Skills:

1- Apply and implement simple algorithms for problem solving and knowledge representation techniques in developing simple intelligent systems applications
2- Select an appropriate expert system development tool for a given task
3- Write programs in PROLOG/Clips/Exsys

d. General and Transferable Skills:

1- Deploy communication skills
2- Deploy research skills
3- Work effectively within a group to analyze, design and implement ES's
4- To work to tight deadlines
5- Effectively present the final work in a demo
6- Justify students design decisions in a written document

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Expert Systems Development

Course topics and contents:

Topic No. of hours Lecture Tutorial/Practical
Expert Systems Overview 4 2 2
Knowledge Acquisition 4 2 2
OAV-SN-Frames 4 2 2
Production Rules 4 2 2
Midterm Exam I 4 2 2
Logic Programming 4 2 2
Predicate Logic 4 2 2
Expert System Design 4 2 2
Inference Network 4 2 2
Midterm Exam II 4 2 2
Inference Network with fuzzy logic 4 2 2
Final Exam 4 2 2

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Expert Systems Development

Teaching And Learning Methodologies:

Teaching and learning methods
Lectures
Practical training
Presentation
Project
Web-Site searches

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Expert Systems Development

Course Assessment :

Methods of assessment Relative weight % Week No. Assess What
Final Exam 40.00 16
Lab Final Practical Exam 15.00 14
Lab Mid Term Practical Exam 5.00 7
Midterm Exam I 15.00 6
Midterm Exam II 15.00 12
Research/Presentation 10.00 4

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Expert Systems Development

Books:

Book Author Publisher
Expert Systems Pankaj Sharma S. K. Kataria & Sons
No Book no no

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