| Course Type | Elective Course |
|---|
| Course Level | Master's Degree Without Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- Learn knowledge representation and rule-based systems.
- Understand decision trees and ID3 algorithm.
- Learn forward and backward chaining algortihms.
- Gain skills about methods of solving problems related to artificial intelligence and expert systems.
- Gain experience to apply expert systems.
- Design an expert system.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | Knowledge representation. Rule-base systems. Knowledge acquisition. Decision trees. ID3 algorithm. The inference engine: forward chaining, backward chaining, and backward chaining algorithms. Inexact reasoning. Uncertainty models in expert systems. Theory of expert systems. Design a expert system. Validity of knowledge base. Fuzzy expert systems. Frame-based expert systems. Hybrid Expert Systems. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Knowledge representation. |
|
2nd Week |
Rule-base systems. |
|
3rd Week |
Knowledge acquisition |
|
4th Week |
Decision trees, ID3 algorithm. |
|
5th Week |
The inference engine: forward chaining, backward chaining, and backward chaining algorithms. |
|
6th Week |
Inexact reasoning |
|
7th Week |
Uncertainty models in expert systems. |
|
8th Week |
Mid-term |
|
9th Week |
Theory of expert systems |
|
10th Week |
Design a expert system |
|
11th Week |
Validity of knowledge base. |
|
12th Week |
Fuzzy expert systems. |
|
13th Week |
Frame-based expert systems. |
|
14th Week |
Hybrid Expert Systems. |
|
| Recommended or Required Reading | 1. Jackson P., Introduction To Expert Systems, 3/E, Addision Wesley, 1998
2. Hayes- Roth F., Waterman D.A., Lenat D.B, Building Expert Systems, ISBN: 0201106868, Addison-Wesley, 1983
3. Turban E., Sharda R., Delen D., Decision Support and Business Intellegence Systems, 9/E, ISBN:9780132453233, Pearson, 2011
|
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Questions/Answers
- Presentation
- Problem Solving
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Quiz |
1 |
30 |
| Total(%) |
|
60 |
| Contribution of In-term Studies to Overall Grade(%) |
|
60 |
| Contribution of Final Examination to Overall Grade(%) |
|
40 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
2 |
2 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
11 |
154 |
| Preparation for Final exam |
1 |
69 |
69 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
44 |
44 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
2 |
2 |
| Homework |
|
|
|
| Total Work Load | 313 |
| Total Work Load / 30 (h) | 10.43 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
