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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. Graduate School
  2. Department of Technology Integration in Education
  3. Non-Thesis Master’s Degree in Technology Integration in Education
  4. Non-Thesis Master’s Degree in Instructional Technology (Distance Education)
  5. Course Structure Diagram with Credits
  6. Artificial Intelligence Technologies
  7. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
  • Learning Outcomes & Program Qualifications
Last Updated: 30/09/2026

Code - Course Title Course Type Laboratory + Practice ECTS
ETE519 - Artificial Intelligence Technologies I. SEMESTER 3 +0 6.0
Language of Instruction Türkçe
Course Type Elective Courses
Course Instructor(s) PROF. DR. MEHMET FIRAT
Mode of Delivery Distance education
Place of Delivery
Used Educational Platforms
Prerequisites To have basic programming skills. Ability to work with Python libraries.
Courses Recomended
Recommended Resources https://huggingface.co/anadoluuni
Work Placement
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Basic concepts of artificial intelligence
Week - 2 Artificial intelligence in educational technologies
Week - 3 Machine learning applications
Week - 4 Supervised and unsupervised learning
Week - 5 Reinforcement learning
Week - 6 Machine learning examples
Week - 7 Deep learning
Week - 8 Artificial neural networks
Week - 9 Large language models
Week - 10 Common large language models
Week - 11 Training large language models
Week - 12 Using HuggingFace
Week - 13 Artificial intelligence agents
Week - 14 The role of artificial intelligence in the future of education

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 40
Final Exam 1 60
Toplam (%) 100

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