head to head · open source
generative-ai-for-beginners vs a-stock-data
generative-ai-for-beginners has 119,980 GitHub stars, 63,157 forks, 23 open issues and last shipped yesterday. a-stock-data has 9,928 stars, 1,814 forks, 5 open issues and last shipped 2 days ago. generative-ai-for-beginners leads on adoption by 1,109% (119,980 vs 9,928 stars). generative-ai-for-beginners is written in Jupyter Notebook under MIT; a-stock-data is written in Python under Apache-2.0. generative-ai-for-beginners has attracted 53% as many forks as stars, a-stock-data 18%. 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 | a-stock-data | |
|---|---|---|
| GitHub stars | ★ 120K | ★ 9.9K |
| License | MIT | Apache-2.0 |
| Written in | Jupyter Notebook | Python |
| Last push | 2026-09-17 | 2026-09-16 |
| Forks | ⑂ 63K | ⑂ 1.8K |
| 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 a-stock-data if
- You want the a-stock-data feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and a-stock-data 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 a-stock-data
a stock data is a self contained AI Skill file, published under Apache 2.0, that consolidates raw China A share market data from 22 sources into 60 endpoints an AI coding assistant can call directly, and it is aimed at quantitative researchers, investment analysts and developers who want A share data inside an LLM workflow without writing their own scraping and authentication code.
read the full a-stock-data overview →
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Frequently asked questions
Is generative-ai-for-beginners or a-stock-data more popular?
generative-ai-for-beginners has 119,980 GitHub stars and a-stock-data has 9,928. generative-ai-for-beginners has the larger community by that measure.
Are generative-ai-for-beginners and a-stock-data free?
Both are open source. generative-ai-for-beginners is licensed under MIT and a-stock-data under Apache-2.0. Neither carries a licence fee.
What is the difference between generative-ai-for-beginners and a-stock-data?
generative-ai-for-beginners is written in Jupyter Notebook and a-stock-data in Python. 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 a-stock-data?
Choose generative-ai-for-beginners if you want the larger community (119,980 stars) or its MIT licence terms. Choose a-stock-data if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.