AI Engineer MLOps Track: Deploy Gen AI & Agentic AI at Scale

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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Ed Donner, Ligency leads this Udemy course in Development, blending real project wins with step-by-step coaching.

The modules are sequenced to unpack AI Agents & Agentic AI step by step, blending theory with scenarios you can reuse at work while keeping the Udemy course reviews tone in mind.

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