OpenAI For Autodidacts

A collection of Run & Explore labs and exercises for exploring OpenAI APIs and AI development concepts.

🎯 What You'll Learn

🚀 1. Quickstart

Get up and running with OpenAI APIs in minutes with practical examples and step-by-step instructions.

🤖 2. Model Inference

Master the art of prompting and interacting with OpenAI models for optimal performance and results.

⚙️ 3. Model Customization

Learn to fine-tune and customize models for your specific use cases and domain requirements.

📊 4. Model Evaluation

Master comprehensive techniques to measure and improve model performance, safety, and reliability.

🎯 5. Agentic AI

Build autonomous AI agents that can reason, plan, and take action independently in complex environments.

🔬 6. Advanced Topics

Explore cutting-edge research, experimental techniques, and emerging AI technologies.

🚀 Quick Start

1. Prerequisites

• Python 3.11 or higher
• OpenAI API key (get one at platform.openai.com)

2. Setup Environment

1. Fork this repository on GitHub

2. Choose your development environment:

   • GitHub Codespaces: Click "Code" → "Codespaces" → "Create codespace on main"
   • Local Docker: Clone your fork and open in Docker Desktop

3. Set up your OpenAI API key:

   cp .env.sample .env
   # Edit .env and replace 'your-api-key-here' with your actual API key

3. Preview Guide

Start the documentation server to browse the learning materials:

mkdocs serve

Navigate to http://localhost:8000 to view the interactive guide.

4. GitHub Copilot

For the best learning experience, use GitHub Copilot Chat mode:

• Open the Chat panel in VS Code (Ctrl+Shift+I or Cmd+Shift+I)
• Ask questions about the code exercises as you work through them
• Get real-time explanations and suggestions for OpenAI API usage

📁 Project Structure

openai/
├── docs/                      # Learning documentation and guides
│   ├── index.md              # Homepage
│   ├── 1-quickstart/         # 🚀 Getting started with OpenAI APIs
│   ├── 2-model-inference/    # 🤖 Prompting and model interaction
│   ├── 3-model-customization/# ⚙️ Fine-tuning and customization
│   ├── 4-model-evaluation/   # 📊 Performance measurement and testing
│   ├── 5-agentic-ai/         # 🎯 Autonomous AI agents and workflows
│   ├── 6-advanced-topics/    # 🔬 Cutting-edge research and techniques
│   ├── assets/               # Images and data files
│   ├── stylesheets/          # Documentation styling
│   ├── javascripts/          # Documentation interactions
│   └── overrides/            # Template customizations
├── labs/                     # Hands-on lab exercises (coming soon)
├── mkdocs.yml                # Documentation configuration
├── requirements.txt          # Python dependencies
├── DESIGN_SYSTEM.md          # Design system documentation
├── LICENSE                   # License information
└── README.md                # This file

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Happy learning! 🤖✨