DevOps Certification Training Course with Gen AI Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This six-week, weekend-intensive DevOps certification course blends core DevOps practices with generative AI integration, delivering 36 hours of live instruction and hands-on labs. Designed for working professionals, the program covers CI/CD, Infrastructure as Code, containerization, orchestration, security automation, and AI-enhanced monitoring. Each module includes practical exercises in a 24/7 cloud lab environment, culminating in a capstone project that demonstrates end-to-end pipeline automation with intelligent insights.
Module 1: Introduction to DevOps & AI Integration
Estimated time: 3 hours
- DevOps philosophy and culture
- Role of AI in modern software delivery
- Overview of DevOps toolchain with AI enhancements
- Hands-on: Exploring the Gen AI playground and designing an intelligent pipeline
Module 2: Version Control with Git & GitHub
Estimated time: 3 hours
- Git fundamentals and branching strategies
- Collaborative workflows using pull requests
- Automating CI triggers via GitHub events
- Hands-on: Setting up a GitHub repository with automated build hooks
Module 3: Continuous Integration with Jenkins
Estimated time: 3 hours
- Pipeline as Code using Jenkinsfile
- Jenkins plugin ecosystem and job configuration
- Automated unit testing and reporting
- Hands-on: Building and executing a Jenkins pipeline with test integration
Module 4: Infrastructure as Code with Terraform and Configuration Management with Ansible
Estimated time: 6 hours
- Terraform basics: provisioning, state management, and modules
- Ansible playbooks, roles, and idempotency
- Secure handling of secrets using Ansible Vault
- Hands-on: Provisioning AWS VPC and compute resources with Terraform; automating deployment and drift remediation with Ansible
Module 5: Containerization with Docker and Orchestration with Kubernetes
Estimated time: 6 hours
- Docker image creation, multi-stage builds, and registries
- Kubernetes architecture: Pods, Deployments, Services
- Application scaling and management using Helm charts
- Hands-on: Containerizing a microservice and deploying it on a managed Kubernetes cluster
Module 6: Monitoring, Security, and Collaboration
Estimated time: 9 hours
- Monitoring with Prometheus and Grafana; logging with ELK stack
- DevSecOps: Integrating SAST/DAST, secrets management, compliance as code
- ChatOps: Bot integrations with Slack/Teams, incident response workflows
- Hands-on: Building dashboards in Grafana, integrating security scanners into CI, and creating a ChatOps bot for deployment triggers
Module 7: GitOps & Continuous Delivery
Estimated time: 3 hours
- GitOps principles and benefits
- Argo CD for automated deployments
- Policy enforcement and auditability in GitOps
- Hands-on: Implementing a GitOps pipeline for continuous delivery
Module 8: Capstone Project & Roadmap
Estimated time: 3 hours
- Designing an end-to-end AI-powered DevOps pipeline
- Integrating CI/CD, IaC, security, monitoring, and ChatOps
- Presenting a fully automated solution with AI-driven insights
- Hands-on: Capstone project submission and career roadmap review
Prerequisites
- Familiarity with basic Linux commands and scripting
- Understanding of software development lifecycle
- Basic knowledge of cloud computing concepts
What You'll Be Able to Do After
- Orchestrate secure, AI-enhanced CI/CD pipelines using Jenkins, GitHub, Docker, and Kubernetes
- Implement Infrastructure as Code using Terraform and Ansible for repeatable cloud provisioning
- Embed generative AI tools for automated code generation, test prioritization, and predictive failure analytics
- Monitor and optimize deployments using Prometheus, Grafana, and AI-driven analytics
- Design and deploy end-to-end automated DevOps solutions with GitOps and ChatOps integration