What will you learn in DevOps Engineer Course
DevOps principles & culture: Understand CI/CD, continuous monitoring/deployment, collaboration, automation, measurement, and AI-driven workflows.
Version control & infrastructure as code: Master Git best practices, branching workflows, GitHub Actions, Terraform, CloudFormation, and AI-assisted code generation.
Configuration management & containers: Implement Ansible and Chef for config management, build Docker images, and orchestrate Kubernetes clusters.
CI/CD automation with AI enhancements: Build end-to-end pipelines (Jenkins, GitHub Actions) integrating Terraform, Ansible, Docker, Kubernetes, and AI for testing, documentation, and deployment.
Monitoring, logging, security & AI integration: Learn Prometheus/Grafana monitoring, security gates, compliance, and use AI tools like Copilot or LLMs for pipeline optimization and chatops.
Program Overview
Phase 1: Foundations (Git, CI/CD, AI in DevOps)
⏳ 20 hours
Topics: Evolution of DevOps, Value Stream Mapping (VSM), CI/CD pipelines, Git workflows, branching strategies, PR reviews, and GitHub Actions.
Hands-on: Leverage GitHub Copilot and other AI tools to enhance coding workflows and automate documentation.
Phase 2: Infrastructure as Code (Terraform, CloudFormation)
⏳ 20 hours
Topics: Provisioning AWS resources using Terraform and CloudFormation, managing remote states, and understanding modular IaC.
Hands-on: Implement infrastructure using Terraform scripts and test deployments with tools like Terratest.
Phase 3: Configuration Management (Ansible)
⏳ 15 hours
Topics: Ansible playbooks, roles, inventories, and secrets management with Vault.
Hands-on: Generate and run automated playbooks using Generative AI for dynamic configurations.
Phase 4: Containers & Orchestration (Docker, Kubernetes)
⏳ 20 hours
Topics: Docker architecture, container design patterns, Kubernetes architecture, and orchestration principles.
Hands-on: Build Docker containers and deploy scalable apps using Kubernetes manifests and Helm charts.
Phase 5: CI/CD End-to-End Pipeline
⏳ 25 hours
Topics: Jenkins pipelines, GitHub Actions, integration of IaC, CM tools, and container orchestration into delivery workflows.
Hands-on: Create a full CI/CD pipeline with Terraform, Ansible, Docker, Kubernetes, and monitoring layers.
Phase 6: Monitoring & AI-Enhanced Automation
⏳ 20 hours
Topics: Logging with ELK, monitoring with Prometheus/Grafana, and integrating anomaly detection.
Hands-on: Implement automated alerts and dashboards; explore AI-enhanced observability solutions.
Capstone Project: Business-Case Pipeline
⏳ 12 hours
Topics: Use-case driven project to validate learned concepts.
Hands-on: Build a complete DevOps lifecycle—provision infrastructure, configure environments, deploy containers, monitor workflows, and optimize using AI.
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Job Outlook
Roles: DevOps Engineer, SRE, Cloud DevOps Specialist, Release Manager, Automation Engineer
Demand & Earning Potential: Average ₹6–12 LPA in India, $110–123k in the US
AI integration edge: Teams increasingly seek AI-augmented engineers for code generation, test automation, observability, and chatops.
End-to-end system delivery: Mastery of tools essential for managing full software delivery cycles and cloud-native automation.
Specification: DevOps Engineer Course
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