Learn to build Vision Transformer models from scratch in PyTorch through a 16-minute video tutorial that provides clear visualizations and detailed explanations of Self Attention, VITs, and their comparison with Convolutional Neural Networks (CNNs). Gain hands-on experience by following along with line-by-line code implementation while understanding the underlying mathematical concepts. Access comprehensive learning materials including code samples, slides, and notebooks through the provided Patreon link. Explore related topics through recommended videos on computer vision history and transformer architecture implementation. Progress through structured segments covering an introduction, visual exploration of VIT architecture, and practical coding implementation.