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.
GitHub: Evaluating and Integrating AI Models
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
5 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Navigate the GitHub Models marketplace to evaluate and select AI models based on provider capabilities, rate limits, and responsible AI features
Configure GitHub Codespaces development environments and manage scaling from the free tier to Azure AI pay-as-you-go for production workloads
Build, test, and validate HTTP API endpoints using FastAPI that integrate AI models from GitHub Models within Codespaces
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Recently updated!
March 2026
Assessments
3 assignments
Taught in English
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There are 3 modules in this course
Covers GitHub Models, Model selection, Production deployment, Hands-on approach, and Machine learning background.
What's included
8 videos7 readings1 assignment
Covers Scaling, Rate limits, Resource management, Rate limit management, and Token budgets.
What's included
6 videos4 readings1 assignment
Covers Hands-on development, HTTP API, Development workflow, Personal access token, and Token expiration.
What's included
6 videos5 readings1 assignment
Instructor
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Frequently asked questions
No. This course focuses on evaluating and integrating pre-built AI models through the GitHub Models service. You will interact with models through APIs and the playground interface rather than building models from scratch. Basic Python knowledge is sufficient.
You need a GitHub account to access GitHub Models and Codespaces. The course uses the free tier of GitHub Models for model evaluation and Codespaces for development. All required Python libraries including OpenAI and Azure AI Inference packages are pre-installed in the Codespaces environment.
Yes. In the final module, you build a FastAPI-based HTTP API that connects to GitHub Models, complete with automatic documentation, input validation, and error handling. You will test this endpoint within Codespaces using port forwarding, giving you a production-like environment before deploying to the cloud.
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Financial aid available,