| Computer Vision |
Fundamentals of Convolutional Layers |
Both |
| Pooling Techniques (Max, Average) |
Both |
| Basic Image Classification |
Both |
| Object Detection Basics (YOLO, SSD) |
Practice |
| Image Segmentation Basics (U-Net) |
Practice |
| Transfer Learning for Image Classification
(e.g., ResNet, MobileNet) |
Practice |
| Image Augmentation Techniques |
Practice |
| Feature Extraction Using Pre-Trained
Models |
Practice |
| Introduction to GANs (Generating Images) |
Practice |
| Introduction to Self-Supervised Learning for
Vision |
Practice |
| Vision Transformers (ViT) Basics |
Practice |
| CLIP and Multimodal Learning |
Practice |
| Generative Models such as Stable Diffusion,
DALL.E |
Practice |
