Course · Intermediate

Building AI Apps with FastAPI

Building an AI-powered application means more than writing model calls in a notebook. You need an API layer so other systems can interact with your model, containers so your application runs the same way everywhere, and orchestration so services like databases work alongside your app. This course takes you through that full arc — building an LLM-powered API with FastAPI, packaging it with Docker, connecting it to PostgreSQL with Docker Compose, and applying hardening patterns like health checks, multi-stage builds, and non-root execution.

  • Intermediate friendly
  • 10 hrs
  • 4 lessons
  • 1 project
  • Premium

Course overview

Build and deploy an LLM-powered API using FastAPI, Docker, and Docker Compose. From creating HTTP endpoints to running hardened, multi-container stacks.

What's inside

4 lessons · 1 project

  • 01
    Build an LLM API with FastAPI

    Learn to build an LLM-powered API with FastAPI. Create HTTP endpoints, validate requests/responses with Pydantic, handle async operations, implement error handling, and test your service. Build a Prompt Optimizer API that other applications can call over HTTP.

    120 min
  • 02
    Guided Project: Deploy a Containerized AI Service Project

    Learn to deploy a containerized FastAPI app to the cloud. Make the app deployment-ready, expose it with ngrok, then deploy to PaaS platforms like Render or Railway. Configure environment variables, handle databases, and make your API publicly accessible.

    120 min
  • 03
    Introduction to Docker for AI Engineering

    Learn to containerize AI applications with Docker. Build a Dockerfile for a FastAPI app, manage environment variables securely, use port mapping, and run isolated containers. Includes Docker Desktop setup and container management with CLI and GUI tools.

    120 min
  • 04
    Multi-Container Applications with Docker Compose for AI Engineering

    Learn to define multi-container apps with Docker Compose. Connect a FastAPI app to PostgreSQL, persist data with volumes, and manage services with compose.yaml. Build production-ready stacks using docker compose up, logs, and exec commands.

    120 min
  • 05
    Advanced Concepts in Docker Compose for AI Engineering

    Learn to harden Docker Compose setups with health checks, externalized config, multi-stage builds, non-root users, and image versioning. Covers variable interpolation, .env files, security best practices, and production-ready containerization patterns.

    120 min

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Aaron Melton
Aaron Melton
Business Analyst at Aditi Consulting

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