LLM Course vs 
Dive into Deep Learning
LLM Course vs Dive into Deep Learning compared for 2026 — features, license, ease of use, performance and which one to choose. The reference roadmap for learning LLMs vs The textbook where every equation is runnable.
Updated regularly · curated by OpenSourceAI.tech
LLM Course vs Dive into Deep Learning at a glance
| Spec | LLM Course | Dive into Deep Learning |
|---|---|---|
| Category | Learn AI & machine learning | Learn AI & machine learning |
| Type | Course + roadmap | Interactive book |
| License | Apache-2.0 | CC-BY-SA-4.0 |
| Runs locally | Yes | Yes |
| Primary language | Jupyter | Jupyter |
| Ease of use | Intermediate | Intermediate |
| Best for | going from using LLMs to actually training them | a rigorous foundation you can actually execute |
| GitHub stars | 80.9k | 29.2k |
How LLM Course and Dive into Deep Learning score
| Criterion | LLM Course | Dive into Deep Learning |
|---|---|---|
| Popularity | 4.5 | 3.5 |
| Maintenance | 4.0 | 2.0 |
| Ease of use | 3.5 | 3.5 |
| Privacy | 5.0 | 5.0 |
| License freedom | 5.0 | 3.5 |
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
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
Dive into Deep Learning
An open textbook used in 500+ universities: every concept comes with maths, runnable code and exercises, available for PyTorch, TensorFlow, JAX and MXNet.
- Adopted by 500+ universities worldwide
- Every equation has runnable code beside it
- Works with PyTorch, TensorFlow and JAX
Key differences
LLM Course is course + roadmap, while Dive into Deep Learning is interactive book. Their licenses differ (Apache-2.0 vs CC-BY-SA-4.0), which matters if you ship a commercial product. In short, LLM Course fits going from using LLMs to actually training them, and Dive into Deep Learning fits a rigorous foundation you can actually execute.
Which should you choose?
Choose LLM Course for going from using LLMs to actually training them. Choose Dive into Deep Learning for a rigorous foundation you can actually execute.
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 Dive into Deep Learning easier to use?
Both sit at a similar level (Intermediate). Your choice should come down to fit rather than difficulty.
Are LLM Course and Dive into Deep Learning free?
LLM Course is free and open source (Apache-2.0), and Dive into Deep Learning is free and open source (CC-BY-SA-4.0). Neither charges for the core software.
Can I run LLM Course and Dive into Deep Learning locally?
LLM Course: yes · Dive into Deep Learning: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
LLM Course vs Dive into Deep Learning — which should I pick in 2026?
Choose LLM Course for going from using LLMs to actually training them. Choose Dive into Deep Learning for a rigorous foundation you can actually execute.
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