• views: 214
• date: 18 August 2026
• posted by: voska89

Master FastAPI to build an AI App. Integrate background AI workers, usage-based pricing, and deploy live to the web

What you'll learn

⚡ Use agentic development to build a production-ready FastAPI app from scratch and deploy it live on Render
⚡ Learn backend fundamentals with FastAPI like request-response cycle, HTTP methods, and Pydantic data validations
⚡ Store data using a PostgreSQL database, SQLModel, handle SQL relationships and perform database migrations with Alembic
⚡ Implement secure JWT user authentication and integrate a third-party authentication service to your backend API
⚡ Run OpenAI's Whisper model in Celery background workers
⚡ Store and process audio files in the cloud using Cloudflare R2 Object Storage and Replicate
⚡ Monetize your application with usage-based pricing with Polar
⚡ Generate a lightweight React UI for your FastAPI App with Copilot and Shadcn UI

Requirements

❗ Python

Description

In this course, you'll masterFastAPI by building an AI Audio Censoring application from scratch.
The curriculum is designed to teach you the big picture of building a production-ready app, combined with modernAgentic Development. The goal isn't to force you to memorize the exact code; it's to give you thearchitectural fundamentals so you can apply these skills to any future project.
We'll start with a solid introduction to FastAPI, covering things like the request-response cycle, HTTP methods, and data validation. We start with visual animations to break down core backend concepts before diving into the code.
You won't just learn basic APIs—you will build a production-ready system.

You'll learn how to

✨ Build async APIs.
✨ JWT authentication.
✨ Handle SQL databases.
✨ Run AI models like OpenAI's Whisper in background workers.
✨ Scale with Cloud Object Storage and Replicate.
✨ Monetize your app with usage-based pricing using Polar.
✨ Implement third-party auth.
✨ API security, observability and testing.
To tie it all together, we'll connect a lightweight React frontend so you can see your API in action. Finally, I'll walk you step-by-step through deploying the entire stack—database, workers, server, and UI—live to the web.
By the time you finish this course, you'll have a fully functional application, deployed live, ready for real users.

Who this course is for

⭐ Python developers ready to build, monetize, and deploy an AI app.

Homepage

https://www.udemy.com/course/fastapi-ai

   
   
   

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