FastAPI with GenAI and AgenticAI project - From Basic to AI

This is not another short, surface-level tutorial. This is a deep, project-first course on FastAPI - built for developers who want to understand what actually happens under the hood and write fast, clean, production-grade backend code.

We start from the foundations: what a backend really is, why FastAPI exists, and how its core pieces; ASGI, Uvicorn, Starlette, and Pydantic - work together to make it so performant. Once you understand the request-response lifecycle and why FastAPI is fast, you stop writing sloppy code and start building applications that can serve the world.

From there, it is projects, projects, and more projects. You will build a menu API, a pincode lookup service with custom exceptions and validators, a database-backed CRUD app with SQLModel, a multi-parameter filtering and stats service, and a header-based authentication system. Then we go further into modern, AI-centric territory, Server-Sent Events, MongoDB-powered document apps, LLM-driven features, image processing pipelines, and a complete Retrieval-Augmented Generation (RAG) system using vector databases.

Along the way you will learn the practices that matter; separation of concerns, Pydantic models, dependency injection, lifespan events, pagination, and clean project structure; plus how to work effectively with AI coding tools the way developers actually do today.

The videos are intentionally longer than the usual Udemy format because real understanding needs room to breathe. This is a senior developer talking to you like a peer, sharing hard-won experience, not a polished script.

By the end, you will be a confident FastAPI backend developer, ready to build robust, high-performance applications and pair them with any frontend or AI workload. This course helps you to not only master FastAPI but also to master Generative AI, RAG in production and building Agents with modern FastAPI ecosystem of python