💎 Key Takeaways
| Course Name | Hugging Face Diffusion Models Course |
|---|---|
| Platform | Hugging Face |
| Price | Free |
| Duration | ~4 weeks (self-paced) |
| Level | Intermediate |
| Prerequisites | Python, Deep Learning, PyTorch basics |
| Skills (to be learned) | Diffusion theory, 🤗 Diffusers, image/audio generation, training & fine-tuning, conditional generation, custom pipelines |
About
This free Hugging Face course introduces you to the exciting world of diffusion models, a cutting-edge approach in generative AI. Whether you’re interested in generating images, audio, or building your own custom pipelines, the course offers both theory and hands-on practice using the 🤗 Diffusers library.
WHO is teaching
The course is taught by Jonathan Whitaker, AI researcher at answer.ai, and Lewis Tunstall, ML engineer at Hugging Face and co-author of Natural Language Processing with Transformers.
WHAT is covered
You’ll start with the foundations of diffusion models and gradually progress to advanced topics like model fine-tuning, conditional generation, Stable Diffusion, and building fully custom pipelines.
SKILLS to be developed
- Core understanding of diffusion models
- Using the 🤗 Diffusers library
- Training models from scratch
- Fine-tuning on new datasets
- Conditional and guided generation
- Designing custom diffusion pipelines
LEVEL
Intermediate – designed for learners with solid Python skills and a background in PyTorch and deep learning.
