AI DevOps: Automate AWS with Terraform & Claude Code | Udemy
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Genre: eLearning[/center]

Automate AWS with Terraform & AI. Build real workflows using Claude Code, MCP, GitHub Actions, and safe deployments

What you'll learn
Build AWS infrastructure using Terraform with AI assistance (Claude Code)
Generate, review, and improve Terraform code using AI workflows
Set up and use MCP for Terraform + AWS automation
Design safe AI deployment pipelines with guardrails and validations
Automate infrastructure workflows using AI hooks, skills, and subagents
Integrate AI-powered reviews and automation into GitHub Actions
Analyze infrastructure for security, cost, and best practices using AI tools

This course is designed for DevOps engineers, cloud engineers, and architects who want to build modern AI-powered infrastructure workflows using Terraform, AWS, GitHub and Claude Code.

Today, infrastructure is no longer just written manually. The industry is shifting toward AI-assisted development, where engineers generate, review, and manage infrastructure using intelligent tools, while still keeping full control and safety.

In this course, you will learn how to combine Terraform, AWS, and AI (Claude Code) to build real-world DevOps workflows that are faster, safer, and more scalable.

This course follows a practical, step-by-step approach, from environment setup to advanced automation patterns. Every concept is implemented hands-on, not just explained.

What you'll learn in this course

How to use AI (Claude Code) to generate and improve Terraform code

How to structure and control AI output using configuration files

Terraform fundamentals and real-world infrastructure patterns

AWS basics: IAM, S3, EC2, networking, and security groups

Setting up Terraform remote state and safe deployment workflows

MCP (Model Context Protocol) for integrating AI with Terraform and AWS

Building reusable AI workflows using hooks and skills

Designing subagents for Terraform implementation and review

Applying guardrails to prevent unsafe infrastructure changes

Automating infrastructure checks (security, cost, best practices)

Integrating AI into GitHub Actions for automated PR reviews and deployments

What makes this course different

This course focuses on how AI is actually used in real DevOps workflows, not just demos or simple prompt examples.

You will build a complete AI-assisted infrastructure pipeline, including:

Code generation

Validation and review

Safe deployment

Automation with GitHub

By the end, you will have a working setup that you can reuse in real projects or your company environment.

Key Features

Step-by-step, hands-on implementation

Real-world DevOps workflows, not simplified demos

Clear and structured explanations

Production-oriented approach

Focus on safety, automation, and scalability

Requirements

Basic understanding of IT or cloud concepts

No prior AWS, Terraform or AI experience required

Why take this course

By taking this course, you will learn how to work faster with AI while keeping full control over your infrastructure.

Instead of replacing your skills, AI will become your assistant - helping you write Terraform, review changes, and automate workflows.

You will gain the ability to design AI-powered DevOps pipelines that reflect how modern engineering teams are evolving today.

This course is ideal for engineers who want to stay ahead of the industry, reduce repetitive work, and build production-ready infrastructure using the latest tools.

Who this course is for:
DevOps engineers who want to integrate AI into their workflows
Cloud engineers working with AWS and Terraform
Developers who want to automate infrastructure using AI
Engineers curious about AI-powered automation and tooling
Anyone who wants to build real-world infrastructure faster with AI

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