ML Model Deployment: Build a Production API with FastAPI

Board Infinity connects a trained machine-learning model with a FastAPI service and a containerized deployment. Prediction endpoints, validation, testing and Docker provide the main sequence. It suits learners who can already train a basic model and now want to make its behavior accessible through an API, with attention to the input contract and the difference between a working notebook and a running service.

What you will learn

• Serve a trained model through FastAPI endpoints.
• Validate requests and test prediction behavior.
• Containerize the service and explore deployment checks.

Who this suits

Beginner by the provider’s label, but basic Python and machine-learning knowledge are required. The course focuses on deployment rather than teaching model training from the beginning.

Before you enroll

Work in a local development environment with fictional records and keep API keys outside source control. Match the demonstrated Python, Pydantic and database-library versions with your project before copying code. Hosting, databases and AI services may cost extra. A completed course project still needs tests, access controls and an operational review before real users or sensitive information depend on it.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Provider access terms can change; review them before paying.

Put it into practice

Expose a small fictional classifier through a local endpoint. Define its input schema, test a malformed request and describe a health check that distinguishes a running process from a service ready to make predictions.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

How YellowCourse describes and checks learning resources.