This course explores Diffusion Models, a powerful technique in machine learning and generative AI. It covers the theory behind these models, starting from foundational research papers and advancing to practical applications. You'll learn to implement Diffusion Models from scratch using PyTorch, with a focus on image generation, inpainting (filling in missing parts of images), and animations. The course provides hands-on coding examples, making it ideal for anyone interested in deepening their understanding of generative models and their use in creative AI projects.