| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Expert Systems | MEN512 | Elective | Master's degree | 1 | Spring | 8 |
Name of Lecturer(s)
Assistant Prof. Dr. Pınar YILDIZ KUMRU
Learning Outcomes of the Course Unit
1) Defining Artificial Intelligence
2) Conduct knowledge engineering studies
3) Defining Interface
4) Make inductions
5) Designing expert systems
6) Improving expert systems
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||
| 1 | 2 | 3 | 4 | 5 | ||
| Learning Outcomes | ||||||
| 1 | Middle | Middle | No relation | No relation | No relation | |
| 2 | Middle | Middle | Low | Low | Low | |
| 3 | Middle | Low | Low | Low | Low | |
| 4 | Middle | Middle | Low | Low | Low | |
| 5 | Middle | Middle | Middle | Low | Low | |
| 6 | Middle | Middle | Low | Low | Low | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
None
Course Contents
This course equips candidates with in-depth knowledge on an overview of artificial intelligence, artificial intelligence approaches, application areas of artificial imtelligence, expert systems, organization of knowledge, gaining knowledge, inference mechanism, constructing the expert system, expert system development methodology, introduction to neurol networks, neurel network outcomes, blurred logic, data management and data envelopment techniques.
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
30% |
|---|---|
Contribution of Final Examination to Course Grade |
70% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required