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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 Gastronomy and Culinary Arts
  3. Course Structure Diagram with Credits
  4. Artifical Intelligence in Gastronomy
  5. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
  • Learning Outcomes & Program Qualifications
Last Updated: 12/06/2026

Code - Course Title Course Type Laboratory + Practice ECTS
GMS220 - Artifical Intelligence in Gastronomy IV. SEMESTER 2 +2 5.0
Language of Instruction Türkçe
Course Type 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 -Ivanov, S., & Webster, C. (2020). Robots, Artificial Intelligence and Service Automation in Travel, Tourism and Hospitality. Emerald Publishing.-Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach. Pearson.-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.-Sarkar, P., et al. (2025). Artificial intelligence in digital gastronomy. Academic Press.-Vittal, A. G. (2025). AI in the food and beverage industry. CRC Press.-Zahoor, I., Wani, S. M., & Ganaie, M. S. (Eds.). (2025). Artificial intelligence in the food industry: Enhancing quality and safety. Routledge.-Say, C. (2018). 50 soruda yapay zekâ. Bilim ve Gelecek Kitaplığı.
Work Placement None
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Course introduction and digital transformation in the gastronomy sector
Week - 2 The concept of artificial intelligence and its basic characteristics
Week - 3 Data and consumer behavior in gastronomy
Week - 4 Developing recipes and menu ideas with artificial intelligence
Week - 5 Content Creation in Gastronomy Using Artificial Intelligence
Week - 6 Reviewing customer comments and sentiment analysis
Week - 7 Artificial Intelligence Applications in Restaurant Operations
Week - 8 Mid-term project work
Week - 9 Demand forecasting and restaurant planning
Week - 10 Personalized food and menu recommendations
Week - 11 Visual Content Generation and Gastronomy Marketing with Artificial Intelligence
Week - 12 Gastronomy experience design and digital applications
Week - 13 Ethical dimensions of artificial intelligence use
Week - 14 Final Project Presentations

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%)

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