AI in Production: Gen AI and Agentic AI at scale

Deploy AI to AWS, GCP, Azure, Vercel with MLOps, Bedrock, SageMaker, RAG, Agents, MCP: scalable, secure and observable.

Created by Ed Donner, Ligency
Udemy 18h 30m 4,580 enrolled English4.9
DevelopmentAI Agents & Agentic AI

What you'll learn

  • Deploy SaaS LLM apps to production on Vercel, AWS, Azure, and GCP, using Clerk
  • Design cloud architectures with Lambda, S3, CloudFront, SQS, Route 53, App Runner and API Gateway
  • Integrate with Amazon Bedrock and SageMaker, and build with GPT-5, Claude 4, OSS, AWS Nova and HuggingFace
  • Rollout to Dev, Test and Prod automatically with Terraform and ship continuously via GitHub Actions
  • Deliver enterprise-grade AI solutions that are scalable, secure, monitored, explainable, observable, and controlled with guardrails.
  • Create Multi-Agent systems and Agentic Loops with Amazon Bedrock AgentCore and Stands Agents

Requirements

  • While it’s ideal if you can code in Python and have some experience working with LLMs, this course is designed for a very wide audience, regardless of background. I’ve included a whole folder of self-study labs that cover foundational technical and programming skills. If you’re new to coding, there’s only one requirement: plenty of patience!
  • The course runs best if you have a small budget for APIs and Cloud Providers of a few dollars. But we monitor expenses at every point, and it's always a personal choice.

About this course

This is the course that more of my students have asked for than any other course — put together.

One student called it:

“The missing course in AI.”

This course is for:

  • Entrepreneurs
  • Enterprise engineers
  • …and everyone in between.

It’s not just about RAG — although we’ll work with RAG.

It’s not just about Agents — but there will be many Agents.

It’s not just about MCP — but yes, there will be plenty of MCP too.

This course is about:

RAG, Agents, MCP, and so much more… deployed to production.

Live.

Enterprise-grade.

Scalable, resilient, secure, monitored — and explained.

You’ll ship real-world, production-grade AI with LLMs and agents across Vercel, AWS, GCP, and Azure, going deepest on AWS.

Across four weeks you’ll take four products to production:

Week 1

You’ll launch a Next.js SaaS product on Vercel and AWS,

with AWS App Runner and Clerk for user management and subscriptions.

Week 2

  • You’ll become an AI platform engineer on AWS,
  • deploying serverless infrastructure using:
  • Lambda, Bedrock, API Gateway, S3, CloudFront, Route 53
  • Write Infrastructure as Code with Terraform
  • Set up CI/CD pipelines with GitHub Actions

— for hands-free deployments and one-click promotions.

Week 3

  • You’ll gain broad industry skills for GenAI in production:
  • Deploy a Cyber Security Analyst agent with MCP to Azure & GCP
  • Stand up SageMaker inference
  • Build data ingest to S3 vectors
  • Deploy a Researcher Agent using OpenAI OSS models on Bedrock + MCP

Week 4

You’ll go fully agentic in production:

Architect multi-agent systems with:

Aurora Serverless, Lambda, SQS

JWT-authenticated CloudFront frontends

LangFuse observability

Overview of AWS Agent Core

By the end, you’ll know how to:

  • Pick the right architecture
  • Lock down security
  • Monitor costs
  • Deliver continuous updates
  • Everything needed to run scalable, reliable AI apps in production.
  • Course sections (Weeks & Projects)

Week 1

SaaS App Live in Production with Vercel, AWS, Next.js, Clerk, App Runner

Project: SaaS Healthcare App

Week 2

AI Platform Engineering on AWS with Bedrock, Lambda, API Gateway, Terraform, CI/CD

Project: Digital Twin Mk II

Week 3

Gen AI in Production with Azure, GCP, AWS SageMaker, S3 Vectors, MCP

Project: Cybersecurity Analyst

Week 4

Agentic AI in Production: Build and deploy a Multi-Agent System on AWS (Aurora Serverless, Lambda, SQS),

with LangFuse and Bedrock AgentCore

Capstone Project: SaaS Financial Planner

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FAQs

Is AI in Production: Gen AI and Agentic AI at scale Coupon Code Working?
Absolutely, we manually verify the coupon for this AI in Production: Gen AI and Agentic AI at scale course to ensure it works seamlessly.
How long is the AI in Production: Gen AI and Agentic AI at scale course?
The AI in Production: Gen AI and Agentic AI at scale course is approximately 18.5 hours long with comprehensive content.
What will I learn in AI in Production: Gen AI and Agentic AI at scale classes?
Deploy AI to AWS, GCP, Azure, Vercel with MLOps, Bedrock, SageMaker, RAG, Agents, MCP: scalable, secure and observable.
How do I get this course?
Click the “Enroll Now” button on this page to access the course with our exclusive coupon code applied automatically.