Learn Hugging Face Bootcamp (Udemy.com)

Solid introduction to Hugging Face tools, models, pipelines, spaces and gradio — great for getting a broad overview of AI/ML capabilities. The instructor's presentation is clear and engaging, with relevant examples for when the course was created (summer 2024). Model internals are explained appropriately for the length, though some sections feel uneven and the Git portion at the end seems tacked on from another course. Pacing could be tighter (2–3× longer than necessary), and some material (e.g., older models, version-specific quirks) is already dated. Still, a good value for beginners wanting hands-on HF exposure.

It's great but some of the content is a little out of date and doesn't work anymore, and the teacher occasionally brings in new concepts without explaining what they are.

The course was well explained and easy to follow. I left with a solid understanding of how Hugging Face works, especially in practical applications. I particularly enjoyed the section on the GUI, it was intuitive and clearly demonstrated how to interact with models visually. Overall, a great learning experience.

This was a very nice course that provided all the essential information needed to get started with Hugging Face. The teacher is genuinely knowledgeable and presented the material in an effective manner. Their patience in walking through demonstrations and explanations was helpful. For anyone needing a comprehensive, yet manageable, guide to this topic, this course is a great resource. I definitely recommend it.

The explanations and walkthroughs were great. I loved the sections showing recipes for running various kinds of huggingface model inferences, but I had hoped there would be discussion of training too, and how to do that - even if it was only a pointer to the next course to take. The section 8 on Git was helpful, but also a bit strange in how it was tacked on, and incomplete (it ends with a tomorrow-we'll-learn spiel, but there is no more). I'd suggest just adding a quick note to say that the git section is just a bonus appendix to help with the rest of the course and isn't complete - that way it's more clear that it's a feature, not a bug. Very glad I took the course - I feel really empowered to try things on Huggingface now! :)

This is amazing course , highly practical and to the point. Instructor is amazing throwing tips and tricks in a very easy to digest format. I would highly recommend this course to anyone looking to learn more about how to work with hugging face.

This is a comprehensive introduction to using HuggingFace tools covering the text/NLP, audio, image (diffusion) and even the video models along with using gradio for building simple UIs. Plus a bit about git and github. If you have any programming experience, especially with some frontend HTML/JS then the gradio and git/github parts are going to be quite trivial. But the rest of the course it worth it for the coverage. Jose goes the extra mile in the audio section and goes into some good details about FFTs and such. Delightful. The code samples are quite easy to follow and the notebooks provide more in-depth information. If you are using a M1 Mac you need to make small adjustments in the code like setting torch.dytpe=torch.float16 or appending .to(torch.device("mps")) to the AutoModel call. Otherwise the notebook kernel crashes (bus error). But Jose points out that they cannot help with configuring every combination of GPU platform out there, which is understandable. There student comments that help with the M1 Mac issues. 5/5, would recommend for anybody interested in learning how to use the HF tools and libraries. A very good introduction.

Buen curso pero quizás con material no tan detalladamente explicado como otros cursos que he realizado del mismo autor. Quizás ejemplos demasiado sencillos. En cualquier caso, suficiente para entender la materia que se supone del curso.

As with so many udemy courses, the course material is deprecated and doesn't work the way the presenter presents it. They need to make more stable content, but the focus on making quick and dirty money. This is a broad survey of huggingface features. It's okay. It's not good. The author dives into some real random zones that have no cohesive approach or provide the student with a new skill.

The class is well thought out and interesting. I went through most of it in one weekend. I did most of the assignments using AWS Sagemaker and Sagemaker Studio Lab. If you have taken a python data science class, the class will be easy. If you have not, the class will be more difficult for you. My favorite part of the class is being able to now easily create ML applications using Gradio that I can use to showcase my skills.