head to head · open source
generative-ai-for-beginners vs GenerativeAIExamples
generative-ai-for-beginners has 119,980 GitHub stars, 63,157 forks, 23 open issues and last shipped yesterday. GenerativeAIExamples has 4,183 stars, 1,098 forks, 84 open issues and last shipped 9 days ago. generative-ai-for-beginners leads on adoption by 2,768% (119,980 vs 4,183 stars). generative-ai-for-beginners is written in Jupyter Notebook under MIT; GenerativeAIExamples is written in Jupyter Notebook under Apache-2.0. generative-ai-for-beginners has attracted 53% as many forks as stars, GenerativeAIExamples 26%. generative-ai-for-beginners was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| generative-ai-for-beginners | GenerativeAIExamples | |
|---|---|---|
| GitHub stars | ★ 120K | ★ 4.2K |
| License | MIT | Apache-2.0 |
| Written in | Jupyter Notebook | Jupyter Notebook |
| Last push | 2026-09-17 | 2026-09-09 |
| Forks | ⑂ 63K | ⑂ 1.1K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick generative-ai-for-beginners if
- You weight community size — 120K stars and counting
- You want the MIT license terms
- Your stack matches Jupyter Notebook
- You value the larger contributor base for long-term maintenance
pick GenerativeAIExamples if
- You want the GenerativeAIExamples feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Jupyter Notebook
- You evaluated both and GenerativeAIExamples fits your workflow better
About generative-ai-for-beginners
Generative AI for Beginners is Microsoft's free, MIT licensed curriculum of 21 Jupyter Notebook lessons that teaches developers how to start building generative AI applications, aimed at newcomers who want a structured, self paced path instead of scattered documentation.
read the full generative-ai-for-beginners overview →
About GenerativeAIExamples
NVIDIA Generative AI Examples This repository is a starting point for developers looking to integrate with the NVIDIA software ecosystem to speed up their generative AI systems. Whether you are building RAG pipelines, agentic workflows, or fine tuning models, this repository will help you integrate NVIDIA, seamlessly and natively, with your development stack. Table of Contents What's New? Data Flywheel Safer Agentic AI Knowledge Graph RAG Agentic Workflows with Llama 3.1 RAG with Local NIM Deployment and LangChain Vision NIM Workflows Try it Now! Data Flywheel Tool Calling Notebooks RAG RAG Notebooks RAG Examples…
read the full GenerativeAIExamples overview →
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Frequently asked questions
Is generative-ai-for-beginners or GenerativeAIExamples more popular?
generative-ai-for-beginners has 119,980 GitHub stars and GenerativeAIExamples has 4,183. generative-ai-for-beginners has the larger community by that measure.
Are generative-ai-for-beginners and GenerativeAIExamples free?
Both are open source. generative-ai-for-beginners is licensed under MIT and GenerativeAIExamples under Apache-2.0. Neither carries a licence fee.
What is the difference between generative-ai-for-beginners and GenerativeAIExamples?
generative-ai-for-beginners is written in Jupyter Notebook and GenerativeAIExamples in Jupyter Notebook. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, generative-ai-for-beginners or GenerativeAIExamples?
Choose generative-ai-for-beginners if you want the larger community (119,980 stars) or its MIT licence terms. Choose GenerativeAIExamples if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.