In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

In this course you will:

• Explore the cutting-edge world of diffusion-based generative AI and create your own diffusion model from scratch.
• Gain deep familiarity with the diffusion process and the models driving it, going beyond pre-built models and APIs.
• Acquire practical coding skills by working through labs on sampling, training diffusion models, building neural networks for noise prediction, and adding context for personalized image generation.
• At the end of the course, you will have a model that can serve as a starting point for your own exploration of diffusion models for your applications.

References:

1/ DeepLearning.AI short course, “How Diffusion Models Work”

2/ Sprites by ElvGames, FrootsnVeggies and kyrise

3/ Code reference This code is modified from here

4/ DDPM & DDIM papers Diffusion model is based on Denoising Diffusion Probabilistic Models and Denoising Diffusion Implicit Models