Learning Path

Deep Learning Fundamentals → Applications of Vision Transformers

This advanced graduate-level path systematically builds from deep learning and computer vision foundations to a deep understanding of Vision Transformers (ViT). You will learn the self-attention mechanism adapted for images, explore the original ViT architecture, and then dive into key variants like Swin Transformer, along with pretraining strategies and practical applications. The path emphasizes genuine dependencies, ensuring you have the necessary mathematical and conceptual groundwork before tackling complex architectures.