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Zero to Hero AI DevOps Course Implementation with AWS Cloud
DevOps Course Implementation with AWS Cloud
Created byYash Gupta
Last updated 7/2026
English
What you'll learn
- DevOps & AWS Foundations: Master core DevOps tools (Git, Linux) and foundational AWS services (EC2, S3, IAM, VPC) from scratch.
- Containerization & Orchestration: Package AI applications using Docker and deploy them at scale using Amazon Elastic Kubernetes Service (EKS) or ECS.
- CI/CD for Machine Learning (MLOps): Build fully automated continuous integration and continuous deployment pipelines for AI models using AWS CodePipeline and Gi
- Learn to train, test, and seamlessly transition machine learning models from development into production environments using Amazon SageMaker.
- Infrastructure as Code (IaC): Automate the provisioning and management of cloud infrastructure tailored for AI workloads using Terraform or AWS CloudFormation.
- Monitoring & Security: Implement robust security best practices and monitor live AI model performance, data drift, and resource utilization using Amazon CloudWa
- Docker: Writing optimal Dockerfiles to package Python environments, bulky machine learning libraries, and application dependencies.
- Terraform: Writing declarative code to reliably provision and tear down AWS infrastructure (like VPCs, EC2 instances, and load balancers) across multiple enviro
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Course content
4 sections • 43 lectures • 46h 34m total length
Requirements
- basics of computer knowledge
- No coding exp. needed
Description
Course consists: 43 lectures total
Total Duration : Nearly 46 hours
In the modern tech landscape, traditional software delivery is rapidly evolving. Static continuous integration and deployment (CI/CD) pipelines are being upgraded into intelligent, self-optimizing systems. This masterclass takes you from foundational cloud architecture all the way to building cutting-edge, AI-assisted DevOps workflows on Amazon Web Services (AWS).
Distilling over the years of real-world enterprise IT and cloud infrastructure experience into a streamlined, hands-on journey, this course bridges the gap between traditional system administration and the future of autonomous DevSecOps. You will not only learn how to automate deployments but also how to implement intelligent agents that autonomously debug build failures, analyze telemetry, and auto-remediate production incidents.
Whether you are starting from scratch or looking to modernize your cloud expertise, this course provides a production-ready roadmap to architecting resilient, secure, and AI-powered cloud environments.
Next-Gen AWS CI/CD Pipelines: Build automated, production-grade integration and deployment pipelines utilizing AWS CodePipeline, CodeBuild, and GitHub Actions.
AI for DevOps: Implement the newly released AWS DevOps Agent and Model Context Protocol (MCP) servers (such as CircleCI and Datadog) to enable autonomous incident triage, root cause analysis, and automated bug fixes.
Advanced Identity & DevSecOps: Secure your deployment pipelines by architecting Zero Trust identity frameworks. You will master complex identity governance, including cross-cloud federation between Microsoft Entra ID and AWS IAM to ensure least-privilege access.
Who this course is for:
- Anyone starting from scratch who wants a step-by-step, guided path into the high-paying Cloud and DevOps industry without needing prior cloud experience.
- IT professionals looking to upgrade their manual server management skills to modern Infrastructure as Code (IaC), Kubernetes orchestration, and cloud automation.