Udemy - AI Engineer Production Track: Deploy LLMs & Agents at Scale Free Download

Udemy – AI Engineer Production Track: Deploy LLMs & Agents at Scale
English | Tutorial | Size: 12.98 GB

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

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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