Build a small web API with FastAPI, document it with OpenAPI and Swagger UI, test it with Postman and pytest, and deploy it.
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By the end of this course, you will be able to:
An API (application programming interface) lets one program use another program’s features. A web API does this over the internet: a program sends a request to a URL, and the API sends back data. When an app shows a prediction from an AI model, there is almost always a web API between the app and the model.
In this course, you build one: a small service that reads a support ticket and predicts its category and priority. The prediction comes from a simple keyword classifier, so every result is predictable and you can check it by hand. Later courses replace it with a trained model, with no change to the API around it.
You do not only write the code. You document the API so that another developer can use it without asking you, with OpenAPI and Swagger UI. You explore and test it with Postman, the tool that many teams use to work with APIs every day. You test it automatically with pytest, protect it, and deploy it to a public URL.
Each lesson shows real requests and responses, and a common mistake: what you see, why it happens, and how to recover.
You completed Python for Practical AI Engineering, or you can already set up a virtual environment, write functions and modules, read a traceback and write pytest tests. You do not need to know how the web works. Module 1 explains it.
Courses to take first: Python for Practical AI Engineering.
People who can write and test a small Python project, as in the Python course, and want to offer their code to other programs through a web API. Most AI features reach their users this way.
Experienced AI practitioners designed this course. AI helped us draft the content; people chose the teaching approach and the examples, and reviewed every lesson. The outputs that you see are the actual results of running the code. How we make our courses
Follow a request from your computer to a server and back. You learn the parts of a URL, what DNS, ports and HTTPS do, and how to read a request and its response with the browser's developer tools and curl.
Build a FastAPI service that classifies support tickets. You run it locally, describe its input and output with typed models, and keep the routes, the models and the classifier in separate modules.
Design a contract that other people can use. You choose clear routes, return the same error shape for every failure, and allow browser access only for the sites that need it.
Read the OpenAPI document that FastAPI makes for you, and try every endpoint in Swagger UI. Then make the documentation useful with descriptions and examples, and keep it true with a test.
Explore and test the API with Postman. You organise requests in a collection, switch between a local and a deployed API with Postman environments, write tests, and run the collection from the terminal.
Test the service automatically with pytest, add useful logs with a request ID, and protect it with an API key, a body-size limit and a time limit.
Deploy the service to a managed host, with its settings and secrets outside the code. Then check it with the same Postman collection, read its logs, and remove it when you are done.
Two end-to-end case studies on real data, as projects that you download and run in VS Code. Serve a house-price model behind a validated, tested and deployed API, and build a read-only data API with filters and stable pagination. Complete at least one for the certificate; each one is a portfolio piece.
Complete at least one case study for the certificate. The others are optional. What each one covers
Use every module in one practice project. You collect evidence, and check it against the course outcomes.
Realistic projects from start to finish, on real data, with every output explained. Each one makes a portfolio piece. Complete at least one for the certificate; the others are optional.
Wrap a ready-made model in a validated, tested, documented and deployed estimate API.
Build a data API for city service requests5 hr
A read-only API over a real database: filters, stable pagination, daily statistics, tests and the deployment steps.
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