Advanced Artificial Intelligence
Foundations of advanced AI and deep learning, including neural networks, perceptrons, activation functions, learning paradigms, cost functions, and optimization.
Weekly materials
Materials will be published here in weekly order.
Advanced Artificial Intelligence – Week 1
Introduction to deep learning, AI/ML/DL relationships, perceptrons, activation functions, and gradient descent. Material language: Turkish.
PDFOpen →02Advanced Artificial Intelligence – Week 2
Deep learning applications, cost functions, neural network training, backpropagation, gradient descent, and overfitting. Material language: Turkish.
PDFOpen →03Week 3 — Diffusion Models and Stable Diffusion
Forward diffusion, noise schedules, U-Net denoisers, training, DDPM/DDIM sampling, conditional generation, classifier-free guidance and latent diffusion. Companion lecture notes for the diffusion workshop. Material language: Turkish.
PDFOpen →ATransformer Architecture — Group Presentation Assignment
Assignment: In three groups, explain the original encoder–decoder Transformer from tokenization through output generation. Topics: input representation and positional encoding; encoder and Multi-Head Attention; decoder, masking, and output generation. Deliverable: an in-class visual presentation. PDF language: Turkish.
PDFOpen → ADiffusion and Stable Diffusion Workshop — Student Assignment
Complete the TODO exercises on noise schedules, U-Net training, DDPM/DDIM sampling, classifier-free guidance and Stable Diffusion. Compare at least three experiments. Download the notebook and upload it to Google Colab. Language: Turkish.
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