Complete DevOps & Cloud Engineering Course with AI Tools
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The DevOps & Cloud Engineering certification course is an industry-focused program designed to build strong cloud infrastructure and automation skills using Linux, Python, AWS, and modern DevOps tools. It covers Linux and Shell scripting, Python automation, Git and CI/CD pipelines, Infrastructure as Code with Terraform, Configuration Management with Ansible, Docker and Kubernetes, and production-grade AWS deployment.
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Course Overview
IBM & GeeksforGeeks Certification
Earn industry-recognized certification
Modern AI Toolkit
Work with the latest AI tools & technologies
Live Soft Skills Sessions
Bi-weekly expert-led sessions for interview success
Skills You'll Gain
Key DevOps & Cloud concepts you'll build and master.
Linux Administration
Shell & Python Automation
Cloud Infrastructure Management
Infrastructure as Code (IaC)
CI/CD Pipeline Development
Containerization & Orchestration
Configuration Management
Cloud Networking & Security
Monitoring & Observability
GitOps & Deployment Automation
High Availability & Disaster Recovery
Production Infrastructure Design
Tech Stack You'll Learn
Master industry-standard DevOps & Cloud Engineering tools and technologies.
LinuxPython
Git & GitHubAWSDocker
Kubernetes
Jenkins
GitHub Actions
Terraform
Ansible
Prometheus
Grafana
ArgoCD
SonarQube
Trivy
Projects You'll Build
Real-world projects to apply your skills
Build an automated Linux monitoring solution that tracks system health, generates reports, and schedules performance alerts for production servers.
Develop a Python CLI tool to automate log analysis, report generation, and routine DevOps operations with reusable automation scripts.
Create an AWS automation tool that identifies idle resources, generates optimization reports, and improves cloud infrastructure efficiency.
Containerize a production-ready application using Docker and deploy optimized containers for scalable and portable cloud environments.
Build a production-ready CI/CD pipeline with automated testing, security scanning, and continuous deployment for cloud-native applications.
Develop a monitoring dashboard to visualize infrastructure performance, application metrics, and real-time system health across cloud environments.
Automate server provisioning and configuration using reusable Ansible playbooks for scalable, secure, and consistent infrastructure deployments.
Deploy and manage a scalable microservices application on Kubernetes with automated provisioning, health checks, and persistent storage.
Automate Kubernetes delivery with Git as the single source of truth, using declarative manifests, automatic sync, and controlled rollbacks.
CAPSTONEDesign and deploy a production-grade cloud architecture with high availability, disaster recovery, security, and cost optimization best practices.
Course Syllabus
Session 1: Linux Fundamentals I
- Linux file system, kernel & shell, and the FHS
- Permissions model (rwx, octal, chmod/chown)
- Process management (ps, top, signals, fg/bg)
- Pipes & redirection basics
Session 2: Linux Fundamentals II - Power User
- Text processing: grep, sed, awk one-liners
- Finding things: find, locate, which
- Users, groups & sudo; packages (apt/dnf)
- Services with systemd; disk & memory tools
Session 3: Shell Scripting I
- Shebang, variables & quoting rules
- Conditionals: if / case, test operators
- Loops: for, while read, until
- Functions, arguments & exit codes
Session 4: Shell Scripting II - Filesystems & Performance
- Defensive scripting (set -euo pipefail, trap, validation)
- Logging & debugging (log(), bash -x, shellcheck)
- Monitoring scripts for CPU, memory & disk with alerting
- Scheduling with cron & filesystem automation
Project: System Health Monitor - filesystem automation + performance reporting (portfolio project)
