Getting Started
Set up your environment and start building AI projects
Getting Started
Welcome to AI Engineering Projects. This platform provides hands-on tutorials for building production-ready AI systems.
Prerequisites
Before starting any project, ensure you have:
- Python 3.10+ installed
- Git for version control
- A code editor (VS Code recommended)
- Basic understanding of Python and APIs
Environment Setup
1. Install UV (Recommended)
UV is a fast Python package manager:
curl -LsSf https://astral.sh/uv/install.sh | sh2. Get API Keys
Most projects require an OpenAI API key:
- Go to platform.openai.com
- Create an account and add credits
- Generate an API key
- Store it securely in
.envfiles
3. Choose Your Path
Select a learning path based on your goals:
| Path | Focus | Start Here |
|---|---|---|
| RAG Specialist | Document Q&A systems | Intelligent Document Q&A |
| Full Stack AI | End-to-end applications | Simple Chatbot |
| Production Engineer | Deployment & scaling | Model Serving |
Project Structure
Each project follows a consistent structure:
project-name/
├── src/ # Source code
├── tests/ # Test files
├── data/ # Sample data
├── .env # Environment variables
└── README.md # Project documentationDifficulty Levels
Projects are organized by complexity:
| Level | Time | Code Size | Description |
|---|---|---|---|
| Beginner | 1-2 hours | Under 200 LOC | Learn fundamentals |
| Intermediate | 4-8 hours | 200-500 LOC | Build real features |
| Advanced | 2-5 days | 500+ LOC | Production systems |
Next Steps
Ready to build? Start with the Intelligent Document Q&A project - our most popular beginner tutorial.