| Teaching Staff
|
|
| Language of Instruction |
Türkçe (Turkish) |
| Type Of Course |
Compulsory |
| Prerequisites |
No pre-requisites |
| Recommended Optional Programme Component |
|
| Course Objectives |
This course is an introduction to artificial intelligence. Basic concepts will be examined in the context of computational intelligence. At the same time, efforts will be made to create a multidisciplinary awareness on artificial intelligence.
|
| Course Content |
Basic concepts of artificial intelligence, machine learning, big data, expert systems, search and intelligent systems, and decision tree and artificial neural networks. |
| Learning Outcomes (LO) |
At the end of this course, students will be able to:
1. Defines artificial intelligence and its properties.
2. tells the usage areas
3. tells the usage areas of machine learning, expert system and decision trees. |
| Mode of Delivery |
Face to face |
| Course Outline |
| Week |
Topics |
| 1. Week |
Introduction, What is Artificial Intelligence? And what is Machine Learning?
|
| 2. Week |
Factors and environment |
| 3. Week |
Knowledgeable search |
| 4. Week |
Uninformed search |
| 5. Week |
Games and Decision trees |
| 6. Week |
Logic
|
| 7. Week |
Fuzzy Logic |
| 8. Week |
MIDTERM EXAM
|
| 9. Week |
Prolog |
| 10. Week |
Machine Learning |
| 11. Week |
Deep learning |
| 12. Week |
Expert systems and Natural language processing
|
| 13. Week |
Artificial Neural Networks and Robotics |
| 14. Week |
Application areas of artificial intelligence in businesses |
|
| Assessment |
| |
Percentage(%) |
| Mid-term (%) |
40 |
| Quizes (%) |
|
| Homeworks/Term papers (%) |
|
| Practice (%) |
|
| Labs (%) |
|
| Projects/Field Work (%) |
|
| Seminars/Workshops (%) |
|
| Final (%) |
60 |
| Other (%) |
|
| Total(%) |
100 |
|
| Course Book (s) and/or References |
Doug Rose , Chicago.2018. Artificial Intelligence For Business Lakeshore Press |
| Work Placement(s) |
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| The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO) |
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