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

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

4.8 ★★★★★17,014 studentsCreated by Ed Donner, LigencyLast updated Dec 5, 2025🌐 English

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.