AI Engineering Hub
ActiveDescription
In-depth tutorials on LLMs, RAGs and real-world AI agent applications. Rich notebook examples for learning AI engineering practices.
Key Features
- 93+ production-ready projects — Covering OCR, RAG, agents, voice, multimodal, and more
- Three difficulty tiers — Beginner (22), intermediate (48), advanced (23) projects for progressive learning
- LLM hands-on tutorials — Local deployment and applications with DeepSeek, Llama, Gemma, Qwen models
- Agent workflow examples — Multi-framework agent implementations using CrewAI, AutoGen, MCP
- Full RAG pipeline — Complete practice from basic RAG to Agentic RAG and multimodal RAG
- Jupyter Notebook-based — Each project is a runnable notebook, ready to execute
Use Cases
💡 AI engineering beginners quickly get started with categorized projects
💡 Developers learn and compare different RAG/agent framework implementations
💡 Researchers reproduce and extend existing AI application cases
💡 Team internal training with a library of real project materials
Categories
Quick Start
git clone https://github.com/patchy631/ai-engineering-hub.git && cd ai-engineering-hub && pip install -r requirements.txt