Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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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
  • Deep Learning
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title RYZ2004 - Deep Learning
Course Type Required Courses
Language of Instruction Türkçe
Laboratory + Practice 2+1
ECTS 3.0
Course Instructor(s) ARAŞTIRMA GÖREVLİSİ Melike ÖZMEN ARSLAN
Mode of Delivery Face-to-face
Prerequisites
Courses Recomended
Recommended Reading List
Assessment methods and criteria
Work Placement
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Introduction and Basic Concepts
Week - 2 Artificial Neural Networks and Back Propagation Algorithm
Week - 3 Convolutional Neural Networks
Week - 4 Deep Natural Language Processing
Week - 5 Recurrent Neural Networks
Week - 6 Derin Öğrenme Modellerinin Eğitimi ve Değerlendirilmesi
Week - 7 Activation Functions and Loss Functions
Week - 8 Deep Learning Applications: Image Classification
Week - 9 Deep Learning Applications: Object Recognition
Week - 10 Deep Learning Practices: Emotion Analysis and Text Classification
Week - 11 Deep Learning Applications: Voice Recognition
Week - 12 Transfer Learning and Model Improvement
Week - 13 Deep Learning and Ethical Issues
Week - 14 Deep Learning Practice and Project

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Drill - Practise
  • Problem Solving
  • Proje Design/Management
  • Competences
  • Rational
  • Questoning
  • Creative
  • Eleştirel düşünebilme
  • Abstract analysis and synthesis
  • Problem solving
  • Project Design and Management

Assessment Methods

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