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Description of Individual Course Units| Course Unit Code | Course Unit Title | Type of Course Unit | Year of Study | Semester | Number of ECTS Credits | | YÖN311B.1 | Artificial Intelligence | Elective | 3 | 5 | 4 |
| | Level of Course Unit | | First Cycle | | Objectives of the Course | | Artificial General Intelligence by giving structure and algorithms artificial intelligence applications. | | Name of Lecturer(s) | | Doç.Dr. Didem Güleryüz | | Learning Outcomes | | 1 | grasp the structure of Artificial General Intelligence | | 2 | grasp the Artificial Neural Networks | | 3 | Expert Systems grasp | | 4 | grasp the Genetic Algorithms | | 5 | grasp the Fuzzy Propositional Logic |
| | Mode of Delivery | | Normal Education | | Prerequisites and co-requisities | | None | | Recommended Optional Programme Components | | None | | Course Contents | | Basic concepts (search, problem solving, knowledge representation methods, planning, natural language processing), artificial neural networks, expert systems, genetic algorithms, fuzzy propositional logic. | | Weekly Detailed Course Contents | |
| 1 | Introduction to artificial intelligence | | | | 2 | Problem Solving, Natural Language Processing | | | | 3 | Knowledge Representation Methods | | | | 4 | You Planning, Search, Vision, Robotics, | | | | 5 | General introduction to Artificial Neural Networks | | | | 6 | Artificial Neural Networks (Multi-layer Sensors-Backpropagation) | | | | 7 | Artificial Neural Networks (LVQ Network) | | | | 8 | Mid Term Exam | | | | 9 | Expert Systems | | | | 10 | Expert systems example | | | | 11 | General introduction to genetic introduction to algorithms | | | | 12 | Example of genetic algorithms | | | | 13 | General introduction to fuzzy Propositional Logic | | | | 14 | Fuzzy propositional logic example | | | | 15 | Text Mining | | |
| | Recommended or Required Reading | | Russell S., Norvig P., 2002, "Artificial Intelligence: A modern approach", Prentice Hall series in Artificial Intelligence, 2nd Edition
Luger G.F., 2004, "Artificial Intelligence: Structures and Strategies for Complex Problem Solving", Addison-Wesley, 5th Edition
Uzman sistemler: Bir Yapay Zeka Uygulaması, Novruz Allahverdi, 2002
Kusiak, A., Intelligent Manufacturing Systems, Prentice Hall International Editions, New Jersey, 1990.
Patterson D.W., 1990, "Introduction to artificial intelligence and expert systems", Prentice Hall | | Planned Learning Activities and Teaching Methods | | | Assessment Methods and Criteria | |
| Midterm Examination | 1 | 70 | | Project Preparation | 1 | 20 | | Project Presentation | 1 | 10 | | SUM | 100 | |
| Final Examination | 1 | 100 | | SUM | 100 | | Term (or Year) Learning Activities | 40 | | End Of Term (or Year) Learning Activities | 60 | | SUM | 100 |
| | Language of Instruction | | Turkish | | Work Placement(s) | | None |
| | Workload Calculation | |
| Midterm Examination | 2 | 15 | 30 | | Final Examination | 2 | 2 | 4 | | Quiz | 5 | 1 | 5 | | Project Preparation | 1 | 10 | 10 | | Project Presentation | 1 | 1 | 1 | | Individual Study for Mid term Examination | 4 | 2 | 8 | | Individual Study for Final Examination | 14 | 4 | 56 | | Individual Study for Quiz | 5 | 2 | 10 | |
| Contribution of Learning Outcomes to Programme Outcomes | | LO1 | | 5 | 1 | 5 | 5 | | | LO2 | 2 | 2 | 4 | 4 | | | | LO3 | | 4 | 4 | 5 | 4 | 3 | | LO4 | 4 | | 5 | | | | | LO5 | | 5 | 4 | 3 | 1 | 1 |
| | * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |
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