6+ Free Sources to Study Diffusion Models

Visual reasoning is as important as text reasoning in AI, and models that can handle visual tasks are highly influential. Diffusion models are widely used for image, video, and audio tasks. They generate high-quality outputs by learning to reverse a noisy process, making them versatile tools for creative and practical applications. Some of the most popular diffusion models include DALL-E, Stable Diffusion, and Midjourney. The ongoing growth of multimodal models also highlights the importance of understanding the basics of these models for AI developers and users.

So here are 6+ free sources to explore diffusion models in detail:

1. “Efficient Diffusion Models: A Comprehensive Survey from Principles to Practices” offers an efficiency-focused overview of the design, training, and deployment of diffusion models, making it easier for researchers to understand and apply these models in new fields. → Read more

2. “Tutorial on Diffusion Models for Imaging and Vision” by Stanley Chan covers the basics of diffusion models, including Variational Auto-Encoder (VAE), Denoising Diffusion Probabilistic Model, and more. It is aimed at students interested in researching or applying these tools to solve various challenges. → Read more

3. “Step-by-Step Diffusion: An Elementary Tutorial”, created by Apple, Mila, and Université de Montréal, simplifies the math while explaining the algorithms precisely. It explains the following themes: diffusion fundamentals, stochastic and deterministic samplers, flow matching as a diffusion generalization; and gives some practical examples. → Read more

4. Hugging Face Diffusion Models Course includes theory behind diffusion models. You will learn how to train and fine-tune diffusion models, generate images and audio with Diffusers library, build custom pipelines and more. However, it requires knowledge of Python, PyTorch and deep learning base. → Study more

   • Materials for this course on GitHub. → Study more

   • Diffusers Library with interesting tutorials and practical guides as well. → Study more

5. “How Diffusion Models Work” is a 1-hour course by DeepLearning AI, where you’ll learn to build a diffusion model from scratch. It covers the diffusion process, noise prediction, and personalized image generation. You’ll also gain practical skills in sampling, training, and optimizing diffusion models through hands-on labs and Jupyter notebooks. → Study more

6. A lecture on Diffusion Models from Machine Learning at Berkley is a good option for those who like learning through video content more. It explains the theory and practical steps for training and generating images, covering the model’s two-step noise reduction process, recent improvements, and real-world applications in robotics and reinforcement learning. → Study more

   • Here’s also their full course with slides, assignments and more information: CS 198-126: Deep Learning for Visual Data

Happy learning!