| Course Unit Code | Course Unit Title | Type of Course Unit | Year of Study | Semester | Number of ECTS Credits | | BES158Y | Artificial Intelligence in Sports | Elective | 1 | 2 | 6 |
|
| Level of Course Unit |
| Second Cycle |
| Objectives of the Course |
| The main objective of the course is to provide students with knowledge about the fundamental techniques and methodologies within the discipline of artificial intelligence and to ensure that they acquire the competence to utilize these techniques in the field of Sports Sciences effectively. Additionally, the course aims to discuss the changes in Artificial Intelligence in Sports Sciences from a scientific perspective and address new approaches and applications in this field. |
| Name of Lecturer(s) |
| Dr.Öğr. Üyesi Zekai ÇAKIR |
| Learning Outcomes |
| 1 | Information about basic methods in the field of artificial intelligence | | 2 | One gains insight into the current approaches brought by Artificial Intelligence Technologies in the field of sports | | 3 | One can acquire the ability to utilize basic methods in the field of artificial intelligence for applications in Sports Sciences. | | 4 | Developing the ability to create intelligent software (adding intelligence to software). | | 5 | One can explain the fundamental principles of artificial intelligence. |
|
| Mode of Delivery |
| Normal Education |
| Prerequisites and co-requisities |
| There are no prerequisites for this course |
| Recommended Optional Programme Components |
| none |
| Course Contents |
| The fundamental concepts and methods within the discipline of artificial intelligence, techniques used for problem-solving through artificial intelligence, search strategies utilizing problem-specific information, both with and without, local search methods and simulated algorithms, meta-heuristic algorithms, basic principles of artificial neural networks, game problems, and in this context, representation of knowledge and logical inference methods for the application areas of these techniques in the field of sports sciences, particularly in performance measurement tests |
| Weekly Detailed Course Contents |
|
| 1 | Course Orientation Introduction | | | | 2 | Introduction to Artificial Intelligence | | | | 3 | Fundamental Concepts, History, and Philosophy of Artificial Intelligence | | | | 4 | Current Approaches in Problem Solving and Search Algorithms with Artificial Intelligence Techniques | | | | 5 | Applications of Artificial Intelligence in Education | | | | 6 | An Overview of Artificial Intelligence Application Programs | | | | 7 | Applications of Artificial Intelligence in Sports | | | | 8 | Midterm Examination - Midterm | | | | 9 | Machine Learning Algorithms | | | | 10 | Sports Score Prediction Application with Artificial Intelligence | | | | 11 | Introduction to Augmented Reality | | | | 12 | Sports Applications of Augmented Reality | | | | 13 | Student Project Presentations | | | | 14 | General Evaluation | | | | 15 | Final Exam. | | | | 16 | Final Exam | | |
|
| Recommended or Required Reading |
| Tegmark, M. (2019). Yaşam 3.0 Yapay Zekâ Çağında İnsan Olmak, çev. Ekin Can Göksoy. İstanbul: Pegasus Yayınları, 1
Russell, S. and Norvig, P. 2010. Artificial Intelligence: A Modern Approach. 3rd edition. Pearson.
Yılmaz, A. (2017). Yapay zekâ. İstanbul: Kodlab.
Balkaya, E. (2021). Andrew McAfee ve Erik Brynjolfsson, Makine-Platform-Kitle: Dijital Geleceği Kucaklamak, İstanbul: Optimist Yayın Grubu, 2018, 423 s.
Artificial Intelligence, Patrick H. Winston, Addison-Wesley,
N. Öztürk, “Yapay Zeka Ders Notu”.
P.H. Winston, “Artificial Intelligence”.
K. Parsaye, M. Chignell, “Expert Systems for Experts”. |
| Planned Learning Activities and Teaching Methods |
|
| Assessment Methods and Criteria | |
| Midterm Examination | 1 | 100 | | 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 | 1 | 1 | 1 |
| Final Examination | 1 | 2 | 2 |
| Question-Answer | 4 | 8 | 32 |
| Self Study | 8 | 5 | 40 |
| Individual Study for Mid term Examination | 7 | 6 | 42 |
| Individual Study for Final Examination | 7 | 7 | 49 |
|
| Contribution of Learning Outcomes to Programme Outcomes |
| LO1 | 2 | 3 | 3 | 4 | 3 | 3 | | LO2 | 2 | 2 | 2 | 3 | 3 | 3 | | LO3 | 3 | 4 | 3 | 3 | 3 | 3 | | LO4 | 2 | 3 | 3 | 2 | 4 | 3 | | LO5 | 3 | 2 | 3 | 4 | 2 | 4 |
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| * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |
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