CourseVerdict

Machine Learning A-Z: AI, Python & R + ChatGPT Prize vs Hugging Face Course

Same Bayesian formula, same rubric — so the difference in scores reflects the difference in the courses, not the difference in how we evaluated them.

Udemy · AI & ML Courses

Machine Learning A-Z: AI, Python & R + ChatGPT Prize

4.3/ 5 · 44 opinions
34 positive6 neutral4 negative/ 44 total

Hugging Face · AI & ML Courses

Hugging Face Course

4.4/ 5 · 37 opinions
25 positive8 neutral4 negative/ 37 total

Per-criterion

Content quality4.3 / 5

Around 44 hours covering regression, classification, clustering, association rule learning, reinforcement learning, NLP, and deep learning, in both Python and R. Reviewers call it comprehensive and well paced; the main gap is that NLP only reaches bag-of-words and math theory stays light.

Instructor4.5 / 5

Kirill Eremenko and Hadelin de Ponteves are the most-praised element — reviewers say they make a complicated topic accessible to a wide audience and break complex concepts into digestible lessons, with Hadelin's step-by-step coding singled out repeatedly.

Value for money4.4 / 5

A one-time Udemy purchase that frequently goes on deep discount, with ~44 hours and lifetime access. With roughly 800K enrolments and a 4.5 average, reviewers consistently say it is worth it even at full price for the breadth you get.

Support4.0 / 5

No live mentorship or graded project feedback, but reviewers highlight an unusually active Q&A community — "dozens of questions being filed every day" — as where the course really shines for getting unstuck.

Real-world use3.9 / 5

Template-based, hands-on coding on real datasets builds working intuition, but it is an on-ramp rather than a job guarantee. Deployment/production is barely covered and it "won't make you an AI guru" — a strong first step, not a finishing course.

Content quality4.3 / 5

Reviewers praise the ecosystem-native coverage of Transformers, Datasets, Tokenizers and Accelerate, but a recurring theme is API drift — code samples and videos lag behind current `transformers` releases.

Instructor4.3 / 5

Course is authored by the Hugging Face engineering team rather than a single instructor. Reviewers find the explanations clear and pragmatic but note it lacks the consistent voice and pedagogical arc of an Andrew Ng or Jeremy Howard.

Value for money4.9 / 5

Completely free, including the Inference API and Hub access used in exercises. Considered by HN commenters one of the highest-value free resources in modern NLP.

Support3.9 / 5

The discuss.huggingface.co forum is active and chapter threads have hundreds of posts, but replies are uneven and there is no mentorship or structured Q&A. Several learners report broken exam and quiz links going unfixed for months.

Real-world use4.4 / 5

Skills transfer directly to industry work because the Hugging Face stack is the de-facto standard. Reviewers consistently describe the course as the fastest path from "I know Python" to "I can fine-tune a transformer on my own data."

Scoring methodology applies identically to every course on the site — see the formula.