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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Faculty of Tourism
  2. Department of Tourism Management (30% English)
  3. Course Structure Diagram with Credits
  4. Artificial Intelligence Applications in Tourism
  5. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
  • Learning Outcomes & Program Qualifications
Last Updated: 05/05/2026

Code - Course Title Course Type Laboratory + Practice ECTS
TRZ439 - Artificial Intelligence Applications in Tourism VII. SEMESTER 2 +2 5.0
Language of Instruction Türkçe
Course Type Area Elective Courses
Course Instructor(s) ÖĞR. GÖR. SERKAN OLGAÇ
Mode of Delivery Face to face
Place of Delivery
Used Educational Platforms
Prerequisites None
Courses Recomended -
Recommended Resources Russell, S. J., & Norvig, P. (2021). Yapay zeka: Modern bir yaklaşım (M. Erkan & N. Ç. Göksel, Çev.; 4. bs.). Nobel Akademik Yayıncılık.Dülgaroğlu, O. (2024). Turizmde yapay zekâ teknolojileri ve robotlaşma. Uluslararası Turizm, Ekonomi ve İşletme Bilimleri Dergisi (IJTEBS), 8(2), 82–95. https://doi.org/10.1007/978-3-030-48652-5_110Avcı, M., Sungur Avcı, S., & Darı, A. B. (2025). Turizm işletmelerinde ChatGPT ve diğer üretken yapay zekâ uygulamalarının kullanımı: Potansiyeller, riskler ve uygulama önerileri. Journal of Gastronomy, Hospitality and Travel (JOTAGS), 13(4), 4148-4176. https://doi.org/10.21325/jotags.2025.1755Say, C. (2025). 50 soruda yapay zekâ (25. Baskı). İstanbul: Bilim ve Gelecek Kitaplığı.-Buhalis, D., & Leung, R. (2018). Smart hospitality – Interconnectivity and interoperability towards an ecosystem. International Journal of Hospitality Management.-Mariani, M., Baggio, R., Fuchs, M., & Höepken, W. (2018). Business Intelligence and Big Data in Hospitality and Tourism. Routledge.
Work Placement
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Course Introduction and Setup of Application Environments
Week - 2 Analysis of Tourism Problems from an Artificial Intelligence Perspective
Week - 3 Text and Content Generation with Artificial Intelligence
Week - 4 Tourism Chatbot Design and Scenario Development
Week - 5 Sentiment Analysis of Customer Reviews
Week - 6 Demand Forecasting and Occupancy Scenarios
Week - 7 Dynamic Pricing Simulation
Week - 8 Midterm Project Development and Presentations
Week - 9 Personalized Tour and Hotel Recommendation Systems
Week - 10 Visual Generation and Digital Marketing Applications with Artificial Intelligence
Week - 11 Process Automation with No-code/Low-code Tools
Week - 12 Menu and Experience Design with Artificial Intelligence
Week - 13 Final Project Development and Testing
Week - 14 Final Project Presentations and Evaluation

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
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