Decoding DevOps - From Basics to Advanced Projects with AI | Udemy [Update 10/2025]
English | Size: 20.73 GB
Genre: eLearning[/center]
Master DevOps with AI, AWS, Linux, Scripts, Jenkins, Gitlab, GitActions, Docker, Kubernetes, Terraform, Ansible & GitOps
What you'll learn
Learn DevOps from total scratch
Linux and Server Management (Gemini CLI)
Networking fundamentals & Vagrant setup
YAML, JSON, and Bash scripting with GitHub Copilot (AI)
AWS Cloud (IAM, EC2, S3, RDS, EBS, ELB, Systems Manager, Lambda, VPC, Amazon Q, CloudWatch, Auto Scaling, Route 53)
Build & Test Automation using Git, Maven, Jenkins, GitHub Actions, and GitLab CI/CD
CI/CD Pipelines and DevOps Projects with Nexus, SonarQube & Slack integration
Python scripting Basics and for Automation and AWS tasks with Amazon Q (AI code assistant)
Infrastructure as Code using Terraform (VPC, modules, backends)
Configuration Management using Ansible
Docker and Kubernetes (production-grade setup, Helm with AI, Lens)
AWS DevOps Services: CodeCommit, CodeBuild, CodePipeline, Beanstalk, Lambda
GitOps Project - end-to-end CI/CD workflow with Git as the single source of truth
This course is designed for anyone who wants to start or advance their DevOps career through hands-on, project-based learning.
You'll begin with Linux, networking, and scripting fundamentals, then progress through key DevOps tools - Git, Jenkins, GitHub Actions, GitLab, Terraform, Ansible, Docker, Kubernetes, and AWS Cloud.
Each step builds on the last with real projects, like setting up the Vprofile application across multiple DevOps stages - from on-premise to AWS to Kubernetes.
The course also introduces AI-powered tools such as GitHub Copilot, Amazon Q, and AI-integrated Helm, helping you automate faster, code smarter, and build intelligent DevOps pipelines.
By the end, you'll master both the core DevOps practices and modern AI-driven workflows, preparing you for real-world cloud and automation environments.
Step 1
Basics of Linux
Server Management in Linux
Vagrant
Basics of networking
Project
Vprofile Project Intro & Setup on VM's
Step 3
YAML & JSON
Bash Scripting
Basics of scripting
Variables, Conditions, Loops etc
Automating day to day admin tasks
Github Copilot as AI Code assistants for Scripting
Step 3
Cloud Computing Intro
IAM
Ec2 Instances, EBS Volumes, ELB
SSM & CloudShell Intro
AWS CLI
S3
Cloudwatch
RDS
Autoscaling
Route53
Project
AWS Cloud For Project Set Up Lift & Shift
Re-Architecting Web App on AWS Cloud [PAAS & SAAS]
Step 4
Version control system = Git & GitHub
Build Tools | Build & Test Java Code = Maven
Continuous Integration Intro
Jenkins
Jenkins as a Build Server
Jenkins Jobs | Build , Test, Deploy, Notify
Jenkins Master/Slave, Nexus, Sonarqube
Jenkins CI Pipeline
Jenkins Administration
GitHub Actions
What GitHub Actions is and how it fits into DevOps workflows
Core concepts: workflows, jobs, steps, and actions
Triggers and events (push, pull request, schedule, etc.)
Security scans in GitHub Actions
Conditions, permissions, and runners for flexible pipelines
Hands-on examples to build and run pipelines directly from GitHub
Gitlab
What GitLab CI/CD is and how it fits into modern DevOps workflows
Core concepts - pipelines, jobs, stages, runners, variables and artifacts
Writing and understanding .gitlab-ci.yml files
Setting up build, test, and deploy stages with rules
Integrating Docker, security scans, and notifications
Step 5
Python Scripting
Basics of python programming
vars, datatypes, conditions, loops, function, modules etc
Pythons for automating OS tasks
Python for AWS using Amazon Q code assistant(AI)
Step 6
Terraform code structure
Variables
Plan, Apply, Update & Destroy
Provisioners
Outputs
Backends
Modules
Terraform for VPC Setup
Step 7
Ansible Intro
Ad Hoc commands
Modules
YAML into
Playbooks
vars, conditions, loops,
handlers, templates etc etc etc
Variables deep dive
Roles
Ansible for AWS
Step 8
AWS Part 2
VPC in depth
Log management and custom metrics
AWS Lambda
Project
Vprofile on Beanstalk & RDS
Code Commit, Code Build & Code Pipeline
CI & CD on AWS Cloud for Vprofile Project
Beanstalk, RDS, CodePipeline etc
Step 9
Docker Intro
Understanding and Implementing Containers
Volumes, Network, logs etc
Building Images for Vprofile project
Docker compose to run vprofile multi containers
Kubernetes Intro
Kubernetes setup for production Env
Kubernetes objects
Pods, Services, Controllers, Deployment
Replication, Autoscaling, Resource quotas, secret, configmap, namespace.
Ingress
Helm with AI
Lens
Project
Vprofile Project deployment on Kubernetes
Step 10
Project on GitOps
Who this course is for:
Anybody who wants to Learn DevOps
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