• DevOps History


• Elaborate DevOps, DevTestOps, DevSecOps


• Need for DevOps: in the context of our case study and in general


• DevOps Key Players and Trends


• DevOps: Toolset


• Is Agile mandatory for the culture of DevOps


• Continuous Delivery Vs Continuous Deployment


• Amazon and Netflix case study

• What is AI Really


• How AI Tools Work


• Prompt Engineering


• How and Where AI Adds Value to DevOps Workflows

Labs/Assessments

• Setup/subscribe AI Tools


• Prompting strategies for CLI commands and pipeline generation

• Installation of Git and Create GitHub Account


• Introduction to SCM


• Types of SCMs


• Creating repo (repositories)


• Adding source code files to the repo


• Branches and Best Practices


• Track Files and logs


• Merging, Cloning, tagging


• gitignore


• Working on Git Command Line

AI-Enabled Skills

• Using GitHub MCP Server for working with GitHub from your IDE



• Generate conventional commits and structured commit logs


• AI-assisted merge conflict resolution


• AI review assistants for PR diff summaries


• Automating repository tasks using APIs and automation agents

Labs/Assessments

• Add files and commit


• Commit to Local and push changes to Remote


• Pull changes from the remote repository


• Create branches, merge them, revert a commit, and tag commit


• Pull Request with GitHub

• What is Linux


• Brief History


• Linux Basics


• Linux adoption in industry examples


• Linux file system


• Linux important directories


• Package Management RPM


• Using Yum for installation


• Understanding Linux commands basics


• Working with basic commands


• Working with commands required for DevOps training


• Linux command history


• Globbing and Quoting


• Linux file-handling commands


• pipes, grep, and regular expression


• Text Editor – vim


• Security and permissions


• Connecting two machines using SSH


• Locating and finding files


• Changing command prompt Format


• Cronjob in Linux

AI-Enabled Skills

• AI-assisted command generation (safe generation of complex commands)



• Script refactoring and error handling with AI



• AI tools for log analysis and failure diagnosis
• 
  

• Practicing Linux command


• Use absolute and relative path


• Use RPM and Yum to install the Apache server


• List files in various ways and learn how to work with hidden files


• Try setting and removing environment variables


• Use command history and reuse the previous commands


• Reaching out to files and folders using globbing


• Use and for quoting and backslash


• Try to locate and find commands


• Try less, head, and tail commands to view file content


• Modify files using redirection


• Searching content using pipes, grep, and regular expression


• Create a file using Vim and understand various shortcuts to edit files


• Create users, give permissions, change permissions and ownership

AI-Enabled Skills

• Use AI to translate real operational requirements into correct Linux commands
  
  
  
  • . Example: “Find large log files modified in the last 2 days”
  
  
  
  

Shell Scripting

• What is scripting


• Declaring variables


• Declaring arrays


• Control flow statements


• Creating functions


• Debugging


• Using functions

Labs/Assessments:

• Writing a simple script


• Control flow examples

AI-Enabled Skills

• Using AI to convert operational requirements into shell scripts


• •Example: “Create a script to monitor disk usage and send alerts”



• Using AI to refactor variable usage for clarity and safety


• • Example: improving readability and avoiding hard-coded values
  



• Using AI to design correct control flow for complex conditions
  
• • Example: multi-condition deployment checks


• • Example: retry logic for failed commands


• Using AI to explain existing scripts and function usage


• • Example: understanding legacy shell scripts in production
  



• Using AI to analyze script failures and suggest fixes


• • Example: “Why does this script work manually but fail in cron?”


• • Example: root-cause analysis from error output
  

• Installation and Configuration Jenkins


• What is CI and CD pipelines


• Plugins


• Manage Configuration


• Jenkins Projects


• Build Accounts


• Setup Build Jobs


• Scheduling Builds & GitHub Webhook


• Master and Slave Setup


• Running jobs on Slave


• Configuring a Jenkins Pipeline

AI-Enabled Skills

• Generate and refactor Jenkinsfiles with AI prompts


• Debug pipeline failures using AI failure logs


• Use AI to propose pipeline performance improvements

• Plugin manager hands-on


• Configuring Matrix-Based Security in Jenkins


• Jenkins Freestyle project Configuration


• Maven Build


• Jenkins Pipelines with GitHub – Continuous Deployment

• Installation and Configuration Docker


• Containers Vs Virtual Machines


• Containers and Docker


• Docker Architecture


• dockerhub


• How to run containers : command Line


• Understanding Container Lifecycle


• Creating custom images – legacy and using BuildKit


• Redirecting ports


• Container debugging – logs and exec


• Creating Dockerfile


• Dockerfile best practices

Lab/Assessments:

• Pull the image and create a container


• Build a custom image using Ubuntu


• Push the image to dockerhub


• Try various docker commands


• Redirecting port to access the application from web a browser


• Containerizing an app using Dockerfile

AI-Enabled Skills

• Generate Dockerfiles from application specifications


• Optimize images and recommend best practices


• AI-assisted log interpretation and crash diagnostics