Open-Source AI · Learn AI & machine learning

LLM Course vs Made With ML

LLM Course vs Made With ML compared for 2026 — features, license, ease of use, performance and which one to choose. The reference roadmap for learning LLMs vs From notebook to production system.

Updated regularly · curated by OpenSourceAI.tech

Choose LLM Course for going from using LLMs to actually training them. Choose Made With ML for the gap between a notebook and production.

LLM Course vs Made With ML at a glance

Spec	LLM Course	Made With ML
Category	Learn AI & machine learning	Learn AI & machine learning
Type	Course + roadmap	Course (MLOps)
License	Apache-2.0	MIT
Runs locally	Yes	Yes
Primary language	Jupyter	Python
Ease of use	Intermediate	Intermediate
Best for	going from using LLMs to actually training them	the gap between a notebook and production
GitHub stars	80.9k	48.7k

How LLM Course and Made With ML score

🤝 Too close to call — LLM Course and Made With ML land within a hair (4.4 vs 4.3 / 5). Pick on fit, not on score.

Criterion	LLM Course	Made With ML
Popularity	4.5	4.0
Maintenance	4.0	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

LLM Course

Course + roadmap · Apache-2.0

Maxime Labonne's course splits LLM learning into three tracks — the fundamentals, building an LLM, and deploying one — with Colab notebooks for fine-tuning, quantisation and RLHF.

The clearest LLM roadmap that exists
Colab notebooks you can run without a GPU
Covers fine-tuning, quantisation and RLHF hands-on

See the LLM Course page →

Made With ML

Course (MLOps) · MIT

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

See the Made With ML page →

Key differences

LLM Course is course + roadmap, 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, LLM Course fits going from using LLMs to actually training them, and Made With ML fits the gap between a notebook and production.

Which should you choose?

Choose LLM Course for going from using LLMs to actually training them. 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 LLM 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 LLM Course and Made With ML free?

LLM 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 LLM Course and Made With ML locally?

LLM Course: yes · Made With ML: yes. Both can be used without sending your data to a third-party cloud where their setup allows.

LLM Course vs Made With ML — which should I pick in 2026?

Choose LLM Course for going from using LLMs to actually training them. Choose Made With ML for the gap between a notebook and production.

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