Program Overview
This 16-week Microsoft Stack DevOps Engineer Program is designed to transform fresh graduates and junior IT professionals into job-ready DevOps engineers with Microsoft Azure expertise. The program combines hands-on labs, progressive capstone development, weekly assessments, and certification preparation to deliver both practical skills and industry-recognized credentials.
What sets this program apart is the deep integration of Generative AI and Agentic AI throughout the curriculum. Students learn to leverage AI-powered tools like GitHub Copilot, Azure Copilot, and Azure OpenAI as force multipliers in their DevOps workflows. In the final module, students build a functional Agentic AI bot using Azure OpenAI and Semantic Kernel, preparing them for the next evolution of DevOps engineering.
Learning Objectives
Upon completion of this program, students will be able to:
- Implement and manage Git-based source control with Azure Repos, including branching strategies and pull request workflows.
- Design and build CI/CD pipelines using Azure Pipelines (YAML) for automated build, test, and deployment of .NET applications.
- Provision and manage Azure cloud infrastructure including VMs, App Services, AKS, networking, and storage.
- Write PowerShell and Bash scripts to automate infrastructure provisioning and operational tasks.
- Implement Infrastructure as Code using Bicep, ARM Templates, and Terraform for repeatable Azure deployments.
- Containerize applications with Docker, manage images in Azure Container Registry, and deploy to Azure Kubernetes Service.
- Configure comprehensive monitoring, alerting, and logging using Azure Monitor, Application Insights, and Log Analytics.
- Implement DevSecOps practices including secret management with Key Vault, security scanning, and Azure Defender.
- Manage Agile projects using Azure Boards with sprints, work items, and dashboards.
- Demonstrate readiness for AZ-900, AZ-104, and AZ-400 Microsoft certification exams.
- Leverage GitHub Copilot and Azure Copilot as AI-powered productivity tools across coding, scripting, IaC, and pipeline development.
- Apply prompt engineering techniques to maximize effectiveness and accuracy of AI-generated outputs.
- Implement AIOps practices including AI-driven anomaly detection, smart alerting, and predictive analytics.
- Design and build a functional Agentic AI DevOps assistant bot using Azure OpenAI and Semantic Kernel.
AI Integration Strategy
AI is not treated as a standalone module but is woven into every phase of the program. This mirrors how AI tools are used in real-world DevOps teams — as embedded assistants rather than separate workstreams.
AI Progression Model
| Phase | Weeks | AI Focus | Tools |
|---|---|---|---|
| Explore | 1–6 (Modules 1–3) | Learn to use Copilot as a coding and scripting assistant | GitHub Copilot, Azure Copilot |
| Accelerate | 7–12 (Modules 4–6) | AI-assisted pipeline, IaC, and container config generation | GitHub Copilot, Copilot Chat |
| Optimize | 13–14 (Module 7) | AIOps: AI-driven monitoring, anomaly detection, security | Azure Monitor AI, Copilot for Security |
| Build | 15–16 (Module 8) | Build Agentic AI bots for DevOps automation | Azure OpenAI, Semantic Kernel |
AI Tools Used
| Tool | Purpose | Modules |
|---|---|---|
| GitHub Copilot | AI pair programmer for code, scripts, YAML, IaC, Dockerfiles, K8s manifests | All (1–8) |
| GitHub Copilot Chat | Conversational AI for debugging, explaining code, generating docs | 2–8 |
| Azure Copilot (Portal) | Natural language queries for Azure resource management | 2–4 |
| Azure Monitor Smart Detection | AI-driven anomaly detection and smart alerts | 7 |
| GitHub Advanced Security AI | AI-powered vulnerability detection and fix suggestions | 7 |
| Azure OpenAI Service | GPT model APIs for building custom AI agents | 8 |
| Semantic Kernel | Orchestration framework for building Agentic AI applications | 8 |
Responsible AI Practices
- Always validate AI-generated code, configurations, and suggestions before use
- Understand the underlying concepts before using AI to generate solutions
- Apply prompt engineering techniques for better, more accurate AI outputs
- Recognize AI limitations, hallucinations, and potential security risks
- Follow Microsoft Responsible AI principles throughout all work
Curriculum Structure
The program is organized into 8 modules spanning 16 weeks. Each module builds on the previous one, and lab assignments progressively contribute to the final capstone project.
Module Overview
| # | Module | Weeks | Sessions | AI Phase |
|---|---|---|---|---|
| 1 | Foundations (Git, DevOps & Azure DevOps) | 1–2 | 1–6 | Explore |
| 2 | Azure Cloud Fundamentals | 3–4 | 7–12 | Explore |
| 3 | PowerShell & Scripting | 5–6 | 13–18 | Explore |
| 4 | CI/CD with Azure Pipelines | 7–8 | 19–24 | Accelerate |
| 5 | Infrastructure as Code | 9–10 | 25–30 | Accelerate |
| 6 | Containers & Kubernetes | 11–12 | 31–36 | Accelerate |
| 7 | Monitoring, Security & AIOps | 13–14 | 37–42 | Optimize |
| 8 | Agentic AI, Capstone & Cert Prep | 15–16 | 43–48 | Build |
Week-by-Week Syllabus
Week 1Module 1: Git, DevOps & Environment SetupSessions 1–3 · Explore
Topics: Program orientation & environment setup · Introduction to DevOps culture, principles & lifecycle · Version control fundamentals with Git · Introduction to GitHub Copilot in VS Code
Labs: Dev environment setup (VS Code, Git, Azure CLI, Copilot) · Create Git repo, practice basic workflows · Use Copilot to generate commit messages, .gitignore, README · Quiz 1: DevOps fundamentals
Week 2Module 1: Git Branching, Azure DevOpsSessions 4–6 · Explore
Topics: Git branching strategies (GitFlow, trunk-based) · Merge conflicts, rebasing, pull requests · Introduction to Azure DevOps · Copilot for code reviews and PR descriptions
Labs: Implement GitFlow on a sample .NET project · Create Azure DevOps org & import repo · Generate PR descriptions using Copilot · Quiz 2: Git & branching
Week 3Module 2: Azure Cloud OverviewSessions 7–9 · Explore
Topics: Azure cloud overview & global infrastructure · Core services: Resource Groups, Subscriptions, RBAC · Azure Portal, CLI, and Cloud Shell · Azure Copilot: natural language resource queries
Labs: Navigate Azure Portal, create resource groups · Practice Azure CLI commands · Use Azure Copilot to explore and query resources · Quiz 3: Azure fundamentals (AZ-900 aligned)
Week 4Module 2: Azure Compute, Networking & StorageSessions 10–12 · Explore
Topics: Azure Networking: VNets, Subnets, NSGs, Load Balancers · Azure Compute: VMs, Scale Sets, App Services · Azure Storage: Blob, File, Queue, Table · Using Copilot to generate CLI commands and explain errors
Labs: Deploy a VM with networking · Host a .NET app on Azure App Service · Use Copilot Chat to troubleshoot deployment errors · Quiz 4: Azure compute & networking (AZ-104 aligned)
Week 5Module 3: PowerShell FundamentalsSessions 13–15 · Explore
Topics: PowerShell fundamentals: cmdlets, pipelines, variables · Scripting: functions, loops, error handling · Azure PowerShell (Az module) for resource management · Copilot-assisted PowerShell generation and debugging
Labs: PowerShell scripts for admin tasks · Automate Azure resource provisioning via PowerShell · Use Copilot to generate, refactor, and add error handling · Quiz 5: PowerShell scripting
Week 6Module 3: Advanced Scripting & BashSessions 16–18 · Explore
Topics: Advanced PowerShell: modules, remoting, DSC basics · Bash scripting for cross-platform scenarios · Scripting best practices & reusable tooling · Prompt engineering for Copilot in scripting workflows
Labs: Create a reusable PowerShell module · Bash script for Linux VM configuration · Compare hand-written vs Copilot-generated scripts · Quiz 6: Advanced scripting
Week 7Module 4: CI/CD FoundationsSessions 19–21 · Accelerate
Topics: CI/CD concepts and pipeline architecture · Azure Pipelines: YAML syntax, triggers, stages, jobs · Building & testing a .NET application in a pipeline · AI-assisted pipeline YAML generation using Copilot
Labs: Create a CI pipeline for the capstone repo · Add unit tests and code coverage to pipeline · Use Copilot to generate pipeline YAML and test cases · Quiz 7: CI fundamentals
Week 8Module 4: Release Pipelines & ArtifactsSessions 22–24 · Accelerate
Topics: Release pipelines: environments, approvals, gates · Azure Artifacts: package management (NuGet, npm) · Pipeline security: service connections, variable groups, secrets · AI-generated test suites and automated code quality analysis
Labs: Multi-stage CD pipeline with approvals · Publish & consume packages via Azure Artifacts · Generate unit and integration tests using Copilot · Mid-program review & Capstone Checkpoint 1
Week 9Module 5: IaC — ARM & BicepSessions 25–27 · Accelerate
Topics: IaC principles and benefits · ARM Templates: structure, parameters, functions · Bicep: syntax, modules, parameters, and deployment · Copilot-assisted Bicep/ARM template generation and conversion
Labs: Deploy Azure resources using ARM template · Refactor ARM to Bicep, deploy via pipeline · Use Copilot to generate Bicep modules and auto-document IaC · Quiz 8: IaC fundamentals
Week 10Module 5: Terraform on AzureSessions 28–30 · Accelerate
Topics: Terraform on Azure: providers, state, modules · Comparing ARM vs Bicep vs Terraform · IaC testing, linting, and drift detection · AI-assisted Terraform generation and intelligent drift remediation
Labs: Deploy multi-resource infra using Terraform · Integrate IaC into CI/CD pipeline · Generate Terraform configs with Copilot; validate AI-generated IaC · Quiz 9: IaC advanced (AZ-400 aligned)
Week 11Module 6: Docker & ContainersSessions 31–33 · Accelerate
Topics: Docker fundamentals: images, containers, Dockerfile · Docker Compose for multi-container apps · Azure Container Registry (ACR) · Copilot for Dockerfile generation, optimization, and security best practices
Labs: Containerize the capstone .NET application · Push image to ACR, run in Azure Container Instances · Use Copilot to optimize Dockerfiles and Docker Compose · Quiz 10: Docker & containers
Week 12Module 6: Kubernetes & AKSSessions 34–36 · Accelerate
Topics: Kubernetes fundamentals: pods, deployments, services · Azure Kubernetes Service (AKS): setup, scaling, networking · Deploying to AKS via Azure Pipelines · AI-assisted K8s manifest generation and troubleshooting
Labs: Deploy capstone app to AKS cluster · Set up AKS CI/CD pipeline with rolling updates · Generate K8s manifests with Copilot; diagnose pod failures with AI · Quiz 11: Kubernetes & AKS (AZ-400 aligned)
Week 13Module 7: Monitoring & AIOpsSessions 37–39 · Optimize
Topics: Azure Monitor: metrics, logs, alerts, dashboards · Application Insights: APM, live metrics, diagnostics · Log Analytics & KQL · AIOps: AI-driven anomaly detection, smart alerts, and predictive analytics
Labs: Instrument capstone app with Application Insights · Build monitoring dashboard & configure alerts · Configure AI-powered smart detection; use Copilot to write KQL queries · Quiz 12: Monitoring & AIOps (AZ-400 aligned)
Week 14Module 7: Security & DevSecOpsSessions 40–42 · Optimize
Topics: Azure Key Vault: secrets, keys, certificates · Azure Defender for Cloud & security posture · DevSecOps: SAST/DAST, dependency scanning in pipelines · AI-powered security scanning and Copilot for security hardening
Labs: Integrate Key Vault secrets into pipeline & app · Add security scanning to CI/CD pipeline · Use GitHub Advanced Security AI; Copilot-assisted vulnerability fixes · Quiz 13: Security & DevSecOps
Week 15Module 8: Agentic AI & Azure BoardsSessions 43–45 · Build
Topics: Introduction to Agentic AI: concepts, architectures, DevOps use cases · Building a DevOps AI Agent using Azure OpenAI + Semantic Kernel · Azure Boards: Agile project management, sprints, work items · Capstone: final integration & end-to-end deployment
Labs: Set up Azure OpenAI resource & explore API basics · Build a simple Agentic AI bot (query pipeline status, trigger deployments, summarize logs) · Configure Azure Boards for capstone · Capstone Checkpoint 2: peer review
Week 16Module 8: Capstone Demo & Certification PrepSessions 46–48 · Build
Topics: Capstone project presentations & demos (including AI agent demo) · The Future of AI in DevOps: autonomous pipelines, self-healing infrastructure · AZ-400 certification exam preparation & mock test · Program wrap-up, career guidance, next steps
Labs: Capstone final presentation & demo · Enhance AI agent with Semantic Kernel plugins · Mock AZ-400 certification exam · Program feedback & certificates 🎓
Capstone Project
The capstone project is progressively built throughout the 16 weeks. Each module's labs contribute a component. The AI-enhanced edition includes an Agentic AI DevOps assistant as a key deliverable.
- A .NET web application with source code in Azure Repos
- A fully automated CI/CD pipeline (build, test, security scan, deploy) in Azure Pipelines
- Infrastructure as Code templates (Bicep/Terraform) for all Azure resources
- Containerized application deployed to Azure Kubernetes Service
- Monitoring dashboards, alerts, and Application Insights integration
- Secrets managed via Azure Key Vault
- Agile project tracking via Azure Boards
- Architecture diagram, runbook, and README documentation
- An Agentic AI DevOps assistant bot (Azure OpenAI + Semantic Kernel) — query pipeline status, trigger deployments, summarize logs, respond to incidents
- Demonstration of AI tool usage with before/after comparisons throughout development
Assessment Strategy
| Assessment Type | Weight | Details |
|---|---|---|
| Weekly Quizzes | 15% | 13 quizzes (best 10 counted) — theory, concepts, and certification-style questions (AZ-900, AZ-104, AZ-400 aligned) |
| Hands-on Labs | 30% | Core DevOps labs graded on completion, correctness, and code quality. Labs progressively build capstone components. |
| AI Labs & Exercises | 10% | Copilot effectiveness, prompt engineering, AI output validation, and AIOps configuration |
| Capstone Project | 35% | Graded on architecture, pipeline quality, IaC, monitoring, security, AI agent functionality, documentation, and live demo |
| Participation | 10% | Engagement in live sessions, Q&A, peer reviews, and capstone checkpoint reviews |
Grading Scale
| Grade | Percentage | Status |
|---|---|---|
| A — Distinction | 90–100% | Program Completion with Distinction |
| B — Merit | 75–89% | Program Completion with Merit |
| C — Pass | 60–74% | Program Completion |
| F — Fail | Below 60% | Incomplete — Remediation Required |
Certification Alignment
| Certification | Coverage | Program Modules |
|---|---|---|
| AZ-900 | Azure Fundamentals: cloud concepts, core services, pricing, SLAs | Modules 1–2 (Weeks 1–4) |
| AZ-104 | Azure Administrator: compute, networking, storage, identity, governance | Modules 2–3 (Weeks 3–6) |
| AZ-400 | DevOps Engineer Expert: CI/CD, IaC, monitoring, security, collaboration | Modules 4–8 (Weeks 7–16) |
Tools & Prerequisites
Student Prerequisites
- A computer with minimum 8 GB RAM and a stable internet connection
- Microsoft account (free) for Azure and Teams access
- Azure Free Account with $200 credit (or Azure for Students credits)
- Visual Studio Code (free) with recommended extensions
- Git, Docker Desktop installed locally
- GitHub account with Copilot access (free for students via GitHub Education, or Copilot Free tier)
Platform & Tools Stack
| Category | Tools |
|---|---|
| Live Sessions | Microsoft Teams (screen sharing, recording, breakout rooms) |
| Source Control | Azure Repos (Git), GitHub |
| CI/CD | Azure Pipelines (YAML), Azure Artifacts |
| Cloud Platform | Microsoft Azure (Free Tier / Student Credits) |
| IDE | Visual Studio Code with Azure, Docker, PowerShell, Copilot extensions |
| Scripting | PowerShell 7+, Azure CLI, Bash |
| IaC | Bicep, ARM Templates, Terraform |
| Containers | Docker Desktop, Azure Container Registry, AKS |
| Monitoring | Azure Monitor, Application Insights, Log Analytics |
| Security | Azure Key Vault, Microsoft Defender for Cloud |
| Project Mgmt | Azure Boards |
| AI — Coding | GitHub Copilot, GitHub Copilot Chat |
| AI — Cloud | Azure Copilot (Portal), Azure Monitor Smart Detection |
| AI — Agentic | Azure OpenAI Service, Semantic Kernel SDK |
| AI — Security | GitHub Advanced Security AI |
Typical Session Format
Each 2-hour live session follows a structured format. AI tools are used naturally throughout both instruction and lab time.
| Time | Activity | Description |
|---|---|---|
| 0:00 – 0:10 | Recap & Quiz | Quick recap of previous session + weekly quiz (if applicable) |
| 0:10 – 0:50 | Concept Delivery | Theory, demos, and live coding (with Copilot where applicable) |
| 0:50 – 1:00 | Break | 10-minute break |
| 1:00 – 1:45 | Hands-on Lab | Guided lab work with instructor support; AI tools encouraged |
| 1:45 – 2:00 | Wrap-up & Q&A | Summary, AI tips of the day, preview of next session |
Enroll or Attend the Intro Session
Join the free introductory session on Sunday, 3:00 PM – 5:00 PM to learn more about the program, ask questions, and decide if it's the right fit. Seats are limited to 15 students per cohort.
₹40,000 per student · Commences 19th April 2026 · Free Intro Session available