DevOps & Cloud Course - AWS, Docker, Kubernetes with AI
This course that takes you from Linux fundamentals to designing production-grade cloud architecture in 16 weeks. Live, mentor-led sessions on AWS, Docker, Kubernetes, Terraform, Ansible, CI/CD with Jenkins and GitHub Actions, and monitoring with Prometheus and Grafana. Build ten portfolio projects and earn dual IBM & GeeksforGeeks certification.
Course Overview
IBM & GeeksforGeeks Certification
Earn industry-recognized certification
Modern AI Toolkit
Work with the latest AI tools and technologies
Live Soft Skills Sessions
Biweekly expert-led sessions for interview success
Skills You'll Gain
Build and master key DevOps and Cloud concepts.
Linux Administration
Shell and Python Automation
Cloud Infrastructure Management
Infrastructure as Code (IaC)
CI/CD Pipeline Development
Containerization and Orchestration
Configuration Management
Cloud Networking and Security
Monitoring and Observability
GitOps and Deployment Automation
High Availability and Disaster Recovery
Production Infrastructure Design
Technologies You'll Learn
Master industry-standard DevOps and 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 using best practices for high availability, disaster recovery, security, and cost optimization.
Course Syllabus
Session 1: Linux Fundamentals I
- Linux filesystem, kernel, shell, and the FHS
- Permissions model (rwx, octal, chmod/chown)
- Process management (ps, top, signals, fg/bg)
- Pipes and redirection basics
Session 2: Linux Fundamentals II - Power User
- Text processing: grep, sed, awk one-liners
- Finding things: find, locate, which
- Users, groups, and sudo; packages (apt/dnf)
- Services with systemd; disk and memory tools
Session 3: Shell Scripting I
- Shebang, variables, and quoting rules
- Conditionals: if / case, test operators
- Loops: for, while read, until
- Functions, arguments, and exit codes
Session 4: Shell Scripting II - Filesystems & Performance
- Defensive scripting (set -euo pipefail, trap, validation)
- Logging and debugging (log(), bash -x, ShellCheck)
- Monitoring scripts for CPU, memory, and disk, with alerting
- Scheduling with cron and filesystem automation
Project: System Health Monitor - filesystem automation and performance reporting (portfolio project)
