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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BIL 4104 EXPERT SYSTEMS* ELECTIVE 3 0 0 5

Offered By

Computer Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ÇAĞIN KANDEMIR ÇAVAŞ

Offered to

Computer Science

Course Objective

In this course, it is aimed to introduce the basic information about the expert systems.

Learning Outcomes of the Course Unit

1   Have a good understanding of scope of the expert systems. 2   Have a good understanding of the programming of the expert systems. 3   Have a good understanding of the heuristic approach to solve the problems. 4   Have ability to make use of the tools for building expert systems. 5   Have a good understanding of the theory of the expert systems.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 The definition of expert systems 2 The structure of expert systems 3 Logical programming-Prolog 4 Logical programming-Prolog (Continues to) 5 Logical programming-Prolog (Continues to) 6 Logical programming-Prolog (Continues to) 7 Logical programming-Prolog (Continues to) 8 Midterm exam 9 Knowledge in expert systems 10 Design of expert systems 11 Semantic Networks 12 Expert systems and probability 13 Expert systems applications 14 General review

Recomended or Required Reading

Textbook(s): P.Jackson, Introduction To Expert Systems (3rd Edition), Addison Wesley, 1998. Supplementary Book(s): J. Martin, S. Oxman, Building Expert Systems: A Tutorial, Prentice Hall, 1998

Planned Learning Activities and Teaching Methods

Lecture format, built around the textbook readings with numerous examples chosen to illustrate the systems.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 ASG ASSIGNMENT 2 PRJ PROJECT 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE ASG * 0.25 + PRJ * 0.50 + FIN * 0.25 5 RST RESIT 6 FCGR FINAL COURSE GRADE ASG * 0.25 + PRJ * 0.50 + RST * 0.25

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

cagin.kandemir@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparation before/after weekly lectures 12 3 36 Preparation for Mid-term Exam 1 10 10 Preparation for Final Exam 1 30 30 Preparation for Quiz etc. 2 1 2 Preparing Individual Assignments 4 2 8 Final 1 2 2 Mid-term 1 2 2 Quiz etc. 2 0,5 1 TOTAL WORKLOAD (hours) 130

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 LO.1 5 4 5 5 4 LO.2 5 4 5 5 3 LO.3 5 4 5 5 5 4 LO.4 5 5 5 5 4 4 5 LO.5 5 5 5 5