AI for Beginners vs 
Applied ML
AI for Beginners vs Applied ML compared for 2026 — features, license, ease of use, performance and which one to choose. From symbolic AI to neural networks vs How real companies actually ship ML.
Updated regularly · curated by OpenSourceAI.tech
AI for Beginners vs Applied ML at a glance
| Spec | AI for Beginners | Applied ML |
|---|---|---|
| Category | Learn AI & machine learning | Learn AI & machine learning |
| Type | Curriculum (12 weeks) | Curated papers & posts |
| License | MIT | MIT |
| Runs locally | Yes | Yes |
| Primary language | Jupyter | Markdown |
| Ease of use | Beginner | Intermediate |
| Best for | understanding AI broadly, not just deep learning | learning from what companies really did |
| GitHub stars | 52.2k | 29.9k |
How AI for Beginners and Applied ML score
| Criterion | AI for Beginners | Applied ML |
|---|---|---|
| Popularity | 4.5 | 3.5 |
| Maintenance | 5.0 | 2.0 |
| Ease of use | 5.0 | 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
AI for Beginners
Microsoft's 12-week AI curriculum covering the history of AI, symbolic approaches, neural networks, computer vision and NLP, with runnable notebooks throughout.
- Covers the full breadth of AI, not just the trendy parts
- Works with both TensorFlow and PyTorch
- Free and genuinely well-structured
Applied ML
Eugene Yan's curated collection of papers and engineering blog posts on how companies actually build and deploy ML systems in production — organised by problem, not by algorithm.
- Real production systems, not toy examples
- Organised by problem, not by algorithm
- Curated by a practising ML engineer
Key differences
AI for Beginners is curriculum (12 weeks), while Applied ML is curated papers & posts. AI for Beginners leans more beginner-friendly, whereas Applied ML is more suited to intermediate users. In short, AI for Beginners fits understanding AI broadly, not just deep learning, and Applied ML fits learning from what companies really did.
Which should you choose?
Choose AI for Beginners for understanding AI broadly, not just deep learning. Choose Applied ML for learning from what companies really did.
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 AI for Beginners or Applied ML easier to use?
AI for Beginners is generally the easier of the two to get started with, while Applied ML rewards more setup with more control.
Are AI for Beginners and Applied ML free?
AI for Beginners is free and open source (MIT), and Applied ML is free and open source (MIT). Neither charges for the core software.
Can I run AI for Beginners and Applied ML locally?
AI for Beginners: yes · Applied ML: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
AI for Beginners vs Applied ML — which should I pick in 2026?
Choose AI for Beginners for understanding AI broadly, not just deep learning. Choose Applied ML for learning from what companies really did.
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