Deploy a LLM Application to Vercel, Google Cloud & Azure

Build. Containerize. Deploy. Scale.

In today’s job market, it’s not enough to just build applications — you must know how to deploy them in the real world.

In this course, you will learn how to build a complete Generative AI web application using Python, package it using Docker, and deploy it across multiple cloud platforms including Vercel, Google Cloud Run, and Microsoft Azure.

This is not a theory-heavy course.

You will build a real AI-powered Flashcard Generator application step by step — exactly the kind of project companies expect developers, AI engineers, and DevOps professionals to know how to deploy.

Why This Course?

Most courses teach:

• Only AI concepts

• Or only Docker basics

• Or only one cloud platform

This course connects everything together.

You will learn:

• How a Generative AI application is built

• How it is containerized

• How it is deployed to different clouds

• And how deployment strategies differ across platforms

By the end, you’ll have hands-on, production-style deployment experience, not just certificates.

What You Will Build

Throughout the course, you will build:

• A Python-based Generative AI Flashcard Web Application

• Uses OpenAI API to generate intelligent flashcards

• Runs locally on your machine

• Deployed to Vercel (serverless)

• Containerized using Docker

• Deployed to Google Cloud Run

• Deployed to Azure Container Instances

This project can be:

• Added to your portfolio

• Used as a template for future AI apps

• Extended into larger AI-powered systems

What You Will Learn (In Detail)

Application Development

• Setting up Python and VS Code for web development

• Creating a “Hello World” Python web app

• Structuring a real-world Python AI project

• Integrating OpenAI APIs securely

• Running and testing applications locally

Containerization with Docker

• Installing Docker on your local machine

• Understanding Docker images, containers, and layers

• Writing a Dockerfile for a Python web application

• Building Docker images locally

• Running and debugging containers

Deployment to Vercel

• Understanding serverless deployments

• Deploying a Python web application to Vercel

• Managing environment variables securely

• Testing your live application

Deployment to Google Cloud

• Overview of GCP deployment services

• Creating and using Google Artifact Registry

• Pushing Docker images to Google Cloud

• Deploying containerized apps to Google Cloud Run

• Understanding Cloud Run scaling and pricing basics

Deployment to Azure

• Overview of Azure deployment services

• Creating Azure Container Registry

• Pushing Docker images to Azure

• Deploying containers to Azure Container Instances

• Comparing Azure deployment with Google Cloud Run

Multi-Cloud Deployment Strategy

• Differences between Vercel, GCP, and Azure deployments

• When to choose which platform

• Real-world deployment decision-making

If you want to go from “I can build apps” to “I can deploy apps in production”, this course is for you.

You will be guided step by step through:

• Docker

• Cloud setup

• Deployment workflows

Free accounts will be required for:

• Vercel

• Google Cloud

• Microsoft Azure

• OpenAI

By the End of This Course, You Will Be Able To

Build and deploy a Generative AI web application Confidently use Docker for Python applications Deploy applications on Vercel, Google Cloud, and Azure Understand real-world cloud deployment workflows, Add a multi-cloud GenAI project to your portfolio Speak confidently about deployment in interviews

Why This Course Is Different

• Build one real application, not random demos

• Covers Vercel + Google Cloud + Azure in a single course

• Strong focus on hands-on deployment, not just theory

• Perfect bridge between AI development and cloud deployment

  
  

This course comes with 30 days money back guarantee. No question ask. So what are you waiting for just enroll it today.

I will see you inside class.

Happy learning

Ankit Mistry