Information Package / Course Catalogue
| Course Code | : İKY100 |
| Course Type | : Area Elective |
| Couse Group | : Short Cycle (Associate's Degree) |
| Education Language | : Turkish |
| Work Placement | : Students are required, as part of the course "İMEU201 – Workplace Vocational Training" (30 ECTS) offered in the fourth semester, to undertake and successfully complete workplace vocational training for a minimum of 70 working days at enterprises designated in accordance with the provisions of the Aydın Adnan Menderes University Directive on Workplace Vocational Training. |
| Theory | : 2 |
| Prt. | : 2 |
| Credit | : 3 |
| Lab | : 0 |
| ECTS | : 4 |
In light of the changing conditions in the business world driven by technology, students should become familiar with artificial intelligence applications; acquire the skills to effectively use these applications in business processes; understand how to leverage these skills in decision-making processes—the most fundamental function of management; and, upon graduation, have acquired the ability to effectively apply these applications in decision-making processes.
After taking this course, students will understand the concept and processes of decision-making, managerial decision-making techniques, the operating principles of emerging AI technologies, AI technologies currently in use, potential interactions between AI applications and the user interface, and how to use prompt engineering to create probability-based scenarios of alternatives in decision-making processes using these technologies, and how to select the correct decision-making technique from among these alternatives.
| 1. | Gain theoretical knowledge of artificial intelligence and decision-making processes. |
| 2. | They will acquire the practical skills needed to use artificial intelligence tools in decision-making processes. |
| 3. | Understands decision-making techniques and can apply them using AI-powered tools. |
| 4. | They develop scenario-based thinking skills in decision-making processes. |
| 5. | They acquire the ability to effectively use decision support systems in response to potential scenarios in the workplace. |
| 1. | İnce, H., İmamoğlu, S. E., & İmamoğlu, S. Z. (2021). YAPAY ZEKA UYGULAMALARININ KARAR VERME ÜZERİNE ETKİLERİ: KAVRAMSAL BİR ÇALIŞMA. International Review of Economics and Management, 9(1), 50-63. https://doi.org/10.18825/iremjournal.866432 |
| 2. | Çatal, Betül. "YAPAY ZEKANIN KARAR VERME SÜRECİNDE KULLANILMASI." Selçuk Üniversitesi Hukuk Fakültesi Dergisi 33.1 (2025): 311-348. |
| 3. | Berberoğlugil, B. M. (2023). YÖNETİMDE YAPAY ZEKÂ. Scientific Journal of Innovation and Social Sciences Research, 3(2), 81-96. https://izlik.org/JA69EL94NU |
| 4. | Kocaman, Osman. "Yapay Zekâ Uygulamalarinin Kamu Yönetiminde Karar Almaya Etkisi." Yasama Dergisi 49 (2024): 153-192. |
| 5. | Karabulut, Niyazi. "Kamu Yönetiminde Yapay Zekâ Destekli Otomatik Karar Verme: Türkiye Bağlamında Bir Değerlendirme." Necmettin Erbakan Üniversitesi Siyasal Bilgiler Fakültesi Dergisi 7.1 (2025): 151-183. |
| 6. | Dönerçark, Mert, and Vahap Tecim. "Kurumsal karar destek sistemlerinde yapay zekâ kullanimi: Tasarim ve uygulama." Yönetim Bilişim Sistemleri Dergisi 6.2 (2020): 77-103. |
| 7. | Derici, Serkan. "Karar vermede yapay zeka tabanlı derin öğrenme ve makine öğrenmesi algoritmaları: Yapay zeka ile bütünleşme." Yapay Zekâ: Dijital Çağın Anahtarı içinde (2025): 83-97. |
| 8. | Keleş, Ali, Aytürk Keleş, and Eyüp Akçetin. "Pazarlama Alaninda Yapay Zekâ Kullanim Potansiyeli Ve Akilli Karar Destek Sistemleri." Electronic Turkish Studies 12.11 (2017): 109-124. |
| 9. | Bozüyük, T., Yağci, C., Gökçe, İ., & Görkem, A. K. A. R. (2005). Yapay zeka teknolojilerinin endüstrideki uygulamalari. Marmara Üniversitesi Teknik Bilimler Meslek Yüksek Okulu Elektrik Programı Ders Notu. |
| 10. | Erdoğan, O. (2025). KARAR VERME SÜRECİNDE YENİ BİR YAKLAŞIM: YAPAY ZEKÂ OMBUDSMANLIĞI. Ombudsman Akademik, (22), 47-78. |
| 11. | Erkutlu, H., Ergün, E. E., Köseoğlu, İ., & Vurgun, T. (2023). Yapay Zekâ Ve Örgütsel Davraniş. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 13(3), 1403-1417. |
| 12. | Aktürk, E. B. YAPAY ZEKÂ TABANLI KARAR VERME SÜREÇLERİ İLE KALİTE YÖNETİMİ YENİLİK YAKLAŞIMLARININ DEĞERLENDİRİLMESİ. The Journal of Social Science, 10(19), 151-173. |
| 13. | Dirik, D., Erhan, T., & Eryılmaz, İ. (2024). Yapay zekâ ve örgüt temelli araştırmaların potansiyel eğilimleri üzerine bibliyometrik bir analiz. Bulletin of Economic Theory and Analysis, 9(3), 669-698. |
| 14. | Aydın, M. N. YAPAY ZEKÂ DESTEKLİ KARAR ALMA MEKANİZMALARI. DİJİTAL ÇAĞDA YÖNETİM-Geleceğin Liderlik ve Organizasyon Stratejileri, 69. |
| 15. | Tiftik, C. (2021). İnsan kaynakları yönetiminde yapay zekâ teknolojileri ve uygulamaları. IBAD Sosyal Bilimler Dergisi, (9), 374-390. |
| Type of Assessment | Count | Percent |
|---|---|---|
| Assignment | 1 | %10 |
| Quiz | 1 | %20 |
| Practice Examination | 1 | %10 |
| Final Examination | 1 | %60 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 2 | 0 | 14 | 28 |
| Lecture - Practice | 2 | 0 | 14 | 28 |
| Assignment | 1 | 5 | 0 | 5 |
| Practice Examination | 1 | 10 | 1 | 11 |
| Quiz | 1 | 10 | 1 | 11 |
| Final Examination | 1 | 20 | 1 | 21 |
| TOTAL WORKLOAD (hours) | 104 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | PÇ-8 | PÇ-9 | PÇ-10 | PÇ-11 | |
OÇ-1 | 4 | 4 | 5 | 3 | 5 | 5 | 2 | 5 | 5 | 5 | 4 |
OÇ-2 | 4 | 4 | 5 | 3 | 5 | 5 | 2 | 5 | 5 | 5 | 4 |
OÇ-3 | 4 | 4 | 5 | 3 | 5 | 5 | 2 | 5 | 5 | 5 | 4 |
OÇ-4 | 4 | 4 | 5 | 3 | 5 | 5 | 2 | 5 | 5 | 5 | 4 |
OÇ-5 | 4 | 4 | 5 | 3 | 5 | 5 | 2 | 5 | 5 | 5 | 4 |