Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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  • Türkçe
About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Vocational School Of Information Technologies
  • Department of Electronics and Automation
  • Robotics and Artificial Intelligence Program
  • Course Structure Diagram with Credits
  • Artificial Intelligence
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title RYZ106 - Artificial Intelligence
Course Type Required Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 4.0
Course Instructor(s) ÖĞRETİM GÖREVLİSİ ÖZGÜR ÖZŞEN
Mode of Delivery Distance Learning
Prerequisites
Courses Recomended
Required or Recommended Resources
Recommended Reading List
Assessment methods and criteria
Work Placement
Sustainability Development Goals Quality Education , Decent Work and Economic Growth , Industry, Innovation and Infrastructure , Sustainable Cities and Communities , Responsible Production and Consumption

Content

Weeks Topics
Week - 1 Definition and history of the concept of artificial intelligence
Week - 2 Basic concepts of artificial intelligence: intelligence, intelligent behavior, types of artificial intelligence
Week - 3 The importance of artificial intelligence applications in daily life and industry
Week - 4 Machine learning fundamentals, Supervised and unsupervised learning
Week - 5 Machine learning algorithms: decision trees, K-nearest neighbors, support vector machines
Week - 6 Deep learning and artificial neural networks, Convolutional neural networks and fully connected neural networks
Week - 7 Deep learning applications: image classification, natural language processing
Week - 8 Natural language processing and text classification
Week - 9 Image processing and recognition
Week - 10 Artificial intelligence application areas: healthcare, automotive, finance, education
Week - 11 Artificial intelligence ethical principles and concerns, Data-driven decision making and ethical issues. Societal impacts and responsibilities of artificial intelligence technologies
Week - 12 Security threats and vulnerabilities of artificial intelligence systems, Data privacy and security measures related to artificial intelligence, Artificial intelligence security solutions and applications
Week - 13 Students develop projects using artificial intelligence techniques.
Week - 14 Project presentations and evaluations

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Question & Answer
  • Demonstration
  • Drill - Practise
  • Problem Solving
  • Brain Storming
  • Proje Design/Management
  • Competences
  • Productive
  • Rational
  • Entrepreneur
  • Use time effectively
  • Eleştirel düşünebilme
  • Abstract analysis and synthesis
  • Problem solving
  • Information Management
  • Elementary computing skills
  • Decision making
  • Project Design and Management

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%) 0
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