Master Complete DevOps Pipeline with AWS - Online Course

Master Complete DevOps Pipeline with AWS - Online Course

30-days Money-Back Guarantee

Learn AWS Developer tools like Code Commit, Code Build, Code Deploy, Code Pipeline, Code Star, Cloud 9 and much more

Updated on Sep, 2026

Programming, Software Development Tools, DevOps

Duration - 1.5 hours

Training 5 or more people ?

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A Devops pipeline is set of automated processes and tools that the development (Dev) and operations (Ops) teams implement to build, test, and deploy software faster and easier.

In this course you will learn web development, continuous integration, continuous deployment, containerization, writing neat and quality code, DevOps concepts and much more with python programing language.

This learning path will cover different AWS Developer tools services:

Code Commit to create and manage version control system. It is just like Github where you can host highly scalable private Git repositories.

Code Build to create build service for performing testing and generating artifacts and reports.

Code Deploy to deploy application on Elastic Beanstalk, EC2, ECS , EKS and much more

Code Pipeline to create complete Devops Pipeline from source stage to deploy stage includes code commit, code build and code deploy

Code Star to quickly develop, build, and deploy applications on AWS on unified user interface, enabling you to easily manage your software development activities in one place.

Cloud nine is cloud based IDE to run and deploy application.

AWS CLI to control multiple AWS services from the command line and automate them through scripts

This is the crash course is fully packed with useful hands-on covering the key concepts at the same time without wasting crucial time of developer like you.

Check out the detailed breakdown of what’s inside the course

I am an Instructor, Devops engineer, machine learning enthusiast, cloud expert and passionate developer.

I have authored 78 courses with over 115,000 students worldwide across 175+ countries on wide array of technologies like devops, containerization, machine learning, Linux, programming languages and cloud computing platforms like Microsoft Azure, Amazon Web Service and IBM Cloud.

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