Hugging Face Course vs 
Made With ML
Hugging Face Course vs Made With ML compared for 2026 — features, license, ease of use, performance and which one to choose. Master transformers with the actual library vs From notebook to production system.
Updated regularly · curated by OpenSourceAI.tech
Hugging Face Course vs Made With ML at a glance
| Spec | Hugging Face Course | Made With ML |
|---|---|---|
| Category | Learn AI & machine learning | Learn AI & machine learning |
| Type | Course | Course (MLOps) |
| License | Apache-2.0 | MIT |
| Runs locally | Yes | Yes |
| Primary language | Python | Python |
| Ease of use | Intermediate | Intermediate |
| Best for | learning the library the whole ecosystem uses | the gap between a notebook and production |
| GitHub stars | 4.1k | 48.7k |
How Hugging Face Course and Made With ML score
| Criterion | Hugging Face Course | Made With ML |
|---|---|---|
| Popularity | 2.5 | 4.0 |
| Maintenance | 5.0 | 4.0 |
| Ease of use | 3.5 | 3.5 |
| Privacy | 5.0 | 5.0 |
| License freedom | 5.0 | 5.0 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
Hugging Face Course
The official Hugging Face course on transformers, datasets and tokenizers — you learn the ecosystem that most of open-source AI actually runs on.
- Teaches the library everyone actually uses
- Free, with Colab notebooks throughout
- Maintained by the people who wrote the library
Made With ML
Goku Mohandas' course on taking ML from a notebook to a reliable production system: testing, CI/CD, monitoring, and the engineering most courses ignore.
- Covers the engineering that courses skip
- Testing, CI/CD and monitoring for ML
- Written by a practitioner, not an academic
Key differences
Hugging Face Course is course, while Made With ML is course (MLOps). Their licenses differ (Apache-2.0 vs MIT), which matters if you ship a commercial product. In short, Hugging Face Course fits learning the library the whole ecosystem uses, and Made With ML fits the gap between a notebook and production.
Which should you choose?
Choose Hugging Face Course for learning the library the whole ecosystem uses. Choose Made With ML for the gap between a notebook and production.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is Hugging Face Course or Made With ML easier to use?
Both sit at a similar level (Intermediate). Your choice should come down to fit rather than difficulty.
Are Hugging Face Course and Made With ML free?
Hugging Face Course is free and open source (Apache-2.0), and Made With ML is free and open source (MIT). Neither charges for the core software.
Can I run Hugging Face Course and Made With ML locally?
Hugging Face Course: yes · Made With ML: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
Hugging Face Course vs Made With ML — which should I pick in 2026?
Choose Hugging Face Course for learning the library the whole ecosystem uses. Choose Made With ML for the gap between a notebook and production.
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