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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 Computer and Information Sciences
  2. Department of Data Science and Analytics (English)
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  4. Machine Learning III: Deep Learning
  5. Description
  • Description
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Last Updated: 22/07/2026

Code - Course Title Course Type Laboratory + Practice ECTS
VBA302 - Machine Learning III: Deep Learning VI. SEMESTER 3 +1 6.0
Language of Instruction İngilizce
Course Type Required Courses
Course Instructor(s) ARAŞ. GÖR. DR. ÖNDER DORAK
Mode of Delivery Face to face
Place of Delivery
Used Educational Platforms
Prerequisites
Courses Recomended
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Work Placement
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Neural Networks: Multi-layer perceptrons architecture
Week - 2 Selecting activation functions
Week - 3 Forward and backpropagation mechanics
Week - 4 Gradient descent optimization
Week - 5 Computer Vision: Designing CNNs
Week - 6 Performing image classification
Week - 7 Object detection algorithms and Transfer learning
Week - 8 Sequence Models: Recurrent neural networks (RNNs)
Week - 9 Long short-term memory (LSTM) networks
Week - 10 Understanding Transformers and attention mechanisms
Week - 11 Generative Models: Introduction to GANs
Week - 12 Autoencoders implementations
Week - 13 Deploying models using PyTorch/TensorFlow (Part 1)
Week - 14 Deploying models using PyTorch/TensorFlow (Part 2)

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
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