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

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

4.7
(21,031 students)
18h 30m

>_ 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.

/ Course Details & Curriculum

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

Author and Instructor

E

Ed Donner, Ligency

Expert at Udemy

With years of hands-on experience in Development, Ed Donner, Ligency has dedicated thousands of hours to teaching and mentorship. This course is the culmination of industry best practices and a proven curriculum that has helped thousands of students transition into professional roles.

Community Feedback

M

Michael Chen

Verified Enrollment

"This AI Engineer MLOps Track: Deploy Gen AI & Agentic AI at Scale course was exactly what I needed. The instructor explains complex Development concepts clearly. Highly recommended!"

S

Sarah Johnson

Verified Enrollment

"I've taken many Udemy courses on cloud computing & architectural engineering, but this one stands out. The practical examples helped me land a job."

D

David Smith

Verified Enrollment

"Great value for money. The section on AI Agents & Agentic AI was particularly helpful."

E

Emily Davis

Verified Enrollment

"Excellent structure and pacing. I went from zero to hero in Development thanks to this course. Lifetime access is a huge plus."

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