Learn to evaluate, select, and integrate AI models using GitHub Models — a service that provides ready-to-use, off-the-shelf machine learning models directly within the GitHub platform. You will navigate the GitHub Models marketplace to compare models by provider, capability, and rate limits, then test them interactively using the built-in playground with system prompts and temperature controls.

This course covers the practical skills needed to move from model evaluation to production integration. You will understand how rate limits work across different models, learn strategies for scaling beyond the free tier through Azure AI integration, and set up cloud development environments using GitHub Codespaces with pre-installed Python libraries. In the final module, you will build a complete HTTP Application Programming Interface (API) using FastAPI that connects to GitHub Models, authenticate using personal access tokens, test your endpoints within Codespaces, and apply validation strategies for production readiness. You will also learn about responsible AI features including content filters that GitHub applies through Azure to ensure safe model interactions. By the end of this course, you will have hands-on experience building and testing AI-powered API endpoints ready for cloud deployment.