patchy631/ai-engineering-hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
Welcome to the AI Engineering Hub - your comprehensive resource for learning and building with AI! AI Engineering is advancing rapidly, and staying at the forefront requires both deep understanding and hands-on experience. Here, you will find: Whether you're a beginner, practitioner, or researcher, this repo provides resources for all skill levels to experiment and succeed in AI engineering. New to AI Engineering? Start here: Get a FREE Data Science eBook 📖 with 150+ essential lessons in Data Science when you subscribe to our newsletter! Stay in the loop with the latest tutorials, insights, and exclusive resources. Subscribe now! [](https://join.dailydoseofds.com) Perfect for getting started with AI engineering. These projects focus on single components and straightforward implementations. Multi-component systems, agentic workflows, and…
Read the full README ↗ · Preview checked 2026-10-31T15:57:22.412Z
Inside the original README — Document outline
- AI Engineering Hub 🚀
- 🌟 Why This Repo?
- 📋 Table of Contents
- 🎯 Getting Started
- 📬 Stay Updated with Our Newsletter!
- 🎓 Projects by Difficulty
- 🟢 Beginner Projects
- OCR & Vision
- Chat Interfaces & UI
- Basic RAG
- Multimodal & Media
- Other Tools
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Documentation belongs to its respective authors. Reported project/model license: MIT. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
What this repository does
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
Repository facts
- Owner
- patchy631
- Primary language
- Jupyter Notebook
- Stars
- 39,793
- Forks
- 6,446
- Open issues + pull requests
- 133
- License
- MIT
- Archived
- No
- Default branch
- main
- Created
- 2024-10-21T10:43:24.000Z
- Last push
- 2026-11-01T04:39:16.000Z
Topics and intended use
Owner-supplied topics: agents, ai, llms, machine-learning, mcp, rag
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Source and freshness
Source: GitHub. Metadata observed 2026-11-01T12:19:42.808Z. Daily imports are snapshots, not real-time monitoring.
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