Cloud & DevOps

Beginner to Mastery

Azure DevOps & MLOps Engineer Program

End-to-end Azure administration with real governance and networking scenarios

Hands-on DevOps with CI/CD, GitOps, and Infrastructure as Code

Containerization and Kubernetes engineering using Docker, AKS, and Helm

Production-ready monitoring, observability, and reliability practices

Group Enrollment with Friends or Colleagues
Azure DevOps & MLOps Engineer Program

Course Duration

410 Hours

Next Batch

1st March 2026

Course Material

Live. Online. Interactive.

Emphasizes hands-on Azure administration, automation, and Infrastructure as Code.

Covers real-world DevOps with CI/CD, GitOps, Docker, and Kubernetes.

Prepares learners for Azure, DevOps, and MLOps engineering roles.

Introduces production MLOps with data, model lifecycle, and AI infrastructure.

Highlight Azure DevOps & MLOps Engineer Program

KEY HIGHLIGHTS OF AZURE DEVOPS & MLOPS ENGINEER PROGRAM PROGRAM

  • Weekly sessions with industry professionals
  • Dedicated Learning Management Team
  • 410+ hours of hands-on learning experience
  • 105+ hours of live interactive sessions
  • Bridge classes for smooth transition into DevOps & MLOps
  • Learn from Cloud Certified Industry Experts
  • 20+ industry-aligned projects and case studies
  • Personalized mentorship sessions
  • 24*7 learner support
  • 1:1 mock interviews & portfolio building
  • Designed for working professionals and fresh graduates
  • No-Cost EMI available
  • High-demand Azure, DevOps & MLOps skillset
  • Mastery of GitOps, IaC, and AI-Infrastructure

WHY JOIN AZURE DEVOPS & MLOPS ENGINEER PROGRAM PROGRAM?

Comprehensive Azure & Platform Training

Build strong foundations in Azure governance, networking, compute, storage, security, and hybrid connectivity.

Hands-On DevOps & Automation

Work on real CI/CD pipelines, GitOps workflows, Infrastructure as Code, and Kubernetes deployments.

Industry-Aligned Curriculum

Learn tools and practices used in real production environments across Azure, DevOps, and MLOps.

Career-Focused Learning

Designed to prepare learners for in-demand cloud, DevOps, platform, and MLOps roles.

UPCOMING BATCH:

1st March 2026

SkillzRevo

SkillzRevo Solutions

30 MINUTE MEETING

Web conferencing details provided upon confirmation.

Corporate Training, Enterprise training for teams

Batch schedule

BatchBatch Type
Online Live Instructor Led SessionFull-Time
Online Live Instructor Led SessionPart-Time

Regional Timings

BatchBatch Type
IST (India Standard Time)09:00 PM–12:00 AM
Bahrain, Qatar, Kuwait, Saudi Arabia06:30 PM–09:30 PM
UAE / Oman07:30 PM–09:00 PM

Azure DevOps & MLOps Engineer Program OVERVIEW

This program is designed to develop strong Azure administration skills combined with production-ready DevOps and MLOps practices. Learners gain hands-on experience across Azure infrastructure, automation, CI/CD pipelines, containers, Kubernetes, observability, and AI-driven operations. The curriculum follows a real enterprise learning path—starting from cloud governance and core infrastructure, progressing through DevOps engineering and Kubernetes, and extending into modern MLOps and AI infrastructure. Practical labs, real-world scenarios, and architecture-driven learning ensure learners are ready to work in production environments.

ENROLL NOW, BOOK YOUR SEAT & AVAIL UPTO 30% FEE WAIVER

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Azure DevOps & MLOps Engineer Program Objectives

The primary objective of this program is to build industry-ready Azure, DevOps, and MLOps Engineers with strong practical skills beyond tools and certifications. The focus is on real enterprise workflows, automation, and scalable cloud operations.Learners will understand when, why, and how to apply Azure services, DevOps pipelines, Kubernetes, and MLOps practices in real business scenarios—enabling them to contribute effectively from day one in production environments.

Enroll Now →

Why Learn Azure DevOps & MLOps Engineer Program ?

Industry-Focused Learning

Skills aligned with real enterprise cloud and DevOps environments.

Azure-Centric Cloud Expertise

Deep hands-on experience with Microsoft Azure architecture and services.

End-to-End DevOps Skills

CI/CD pipelines, GitOps, automation, testing, and release strategies.

Strong Automation & IaC Foundation

Infrastructure automation using Terraform, ARM templates, and configuration tools.

Containers & Kubernetes at Scale

Build, deploy, and manage applications using Docker, AKS, and Helm.

Production Monitoring & Reliability

Observability, logging, alerting, and troubleshooting using industry tools.

MLOps & AI Infrastructure Readiness

Data versioning, model lifecycle management, and AI operations basics.

Role-Based Career Preparation

Prepared for Cloud Engineer, DevOps Engineer, SRE, Platform, and MLOps roles.

Program Advantages

Job-ready skills focused on real-world Azure and DevOps implementations

End-to-end learning from Azure foundations to DevOps, Kubernetes, and MLOps

Strong emphasis on automation, Infrastructure as Code, and CI/CD pipelines

Training aligned with real production architectures and operational practices

Exposure to modern, industry-standard tools used by real engineering teams

Future-ready skill set covering cloud-native, platform engineering, and MLOps

Description

Azure DevOps & MLOps Engineer Program program Certifications

Azure DevOps & MLOps Engineer Program Curriculum

Lecture 01: Governance & Subscriptions - Azure Subscriptions & Management Groups, Resource Locks, Tags and Cost Tracking, Azure Policy
Lecture 02: Role-Based Access Control (RBAC) - Azure RBAC Concepts, Built-in vs Custom Roles, Scope Management, Best Practices for Access Control
Lecture 03: Azure Administration Tools - Azure Resource Manager (ARM), Azure Portal, Azure Cloud Shell, Azure PowerShell, Azure CLI
Lecture 04: ARM Templates & Automation - ARM Templates Structure, Parameters & Variables, Deployment Modes, Benefits of Infrastructure as Code
Lecture 05: Virtual Networking Fundamentals - Azure Virtual Networks (VNets), Subnets & IP Addressing, Public vs Private IPs, Network Security Groups (NSGs)
Lecture 06: Advanced Networking & DNS - Azure Firewall, Azure DNS, Private vs Public DNS Zones, Network Security Design Patterns
Lecture 07: Intersite Connectivity - VNet Peering, VPN Gateways, Site-to-Site & Point-to-Site VPNs, ExpressRoute & Virtual WAN
Lecture 08: Network Traffic Management - Network Routing & Service Endpoints, Azure Load Balancer (L4), Azure Application Gateway (L7), Azure Traffic Manager
Lecture 09: Designing Azure Network Solutions - Choosing Correct Networking Solutions, High Availability Networking, Network Security Scenarios, Exam-Oriented Networking Questions
Lecture 10: Azure Storage Fundamentals - Storage Accounts, Blob Storage & Containers, Storage Tiers, Storage Security (Keys, SAS, Encryption)
Lecture 11: Azure Files, File Sync & Storage Tools - Azure Files, Azure File Sync, Storage Explorer, Backup and Recovery Basics
Lecture 12: Azure Virtual Machines - VM Planning & Sizing, Creating VMs, Availability Sets & Zones, Virtual Machine Scale Sets (VMSS)
Lecture 13: VM Management & Extensions - VM Extensions, Custom Script Extension, Monitoring VMs, VM Backup Overview
Lecture 14: Serverless & Containers - Azure App Service Plans, Web Apps, Azure Container Instances (ACI), Azure Kubernetes Service (AKS)
Lecture 15: Data Protection & Backup - Azure Backup, Recovery Services Vault, File & Folder Backups, VM Backup & Restore
Lecture 16: Monitoring Azure Infrastructure - Azure Monitor, Metrics & Logs, Azure Alerts, Log Analytics Workspace, Network Watcher
Lecture 17: End-to-End Azure Administration Scenarios - Identity → Networking → Compute → Storage Flow, Real-World Azure Admin Scenarios, Architecture Mapping
Lecture 01: DevOps Foundations & Modern Delivery - DevOps Principles, CI/CD Lifecycle, Agile vs DevOps vs SRE, Toolchain Overview
Lecture 02: Version Control, GitOps & CI Foundations - Git Workflows, Branching, PRs, Release Strategies, GitOps Principles, Intro to CI Systems (GitHub, GitLab, Jenkins)
Lecture 03: CI/CD Pipelines – Multi-Tool Implementation - CI/CD Pipeline Design and Execution, GitHub Actions, GitLab CI, Jenkins, Secure Pipelines and Environment Separation
Lecture 04: Build, Dependency & Artifact Management - Build Automation Concepts (Maven/Gradle), Dependency and Artifact Management, Sonatype Nexus, CI Integration
Lecture 05: Automated Testing in Pipelines - Shift-Left Testing Concepts, Test Stages in CI/CD, pytest, Quality Gates and Reports
Lecture 06: Infrastructure as Code – Terraform Basics - IaC Concepts and Workflow, Terraform Providers, Resource Provisioning, Local State Management
Lecture 07: Terraform Advanced & Cloud Templates - Terraform Variables, Outputs, Workspaces, Remote State & State Locking, AWS CloudFormation, Terraform Modules
Lecture 08: Configuration Management - Configuration vs Provisioning, Ansible, Puppet, Chef Comparison, Agent vs Agentless Models, Automated Configuration Workflows
Lecture 09: Docker Fundamentals - Containers vs VMs, Images, Containers, Registries, Dockerfiles and Image Optimization, Container Security Basics
Lecture 10: Kubernetes Core Concepts - Kubernetes Architecture, Pods, Deployments, Services, Configuration & Secrets, Scaling and Rolling Updates
Lecture 11: Kubernetes Advanced & Helm - Advanced Kubernetes Deployments, Helm Charts and Templating, Environment-Based Deployments, Release and Rollback Strategies
Lecture 12: GitOps for Cloud & Kubernetes - Declarative Deployment Models, GitOps Workflows, CI vs GitOps CD, Kubernetes GitOps Pipelines
Lecture 13: Observability & Monitoring - Monitoring vs Observability, Prometheus Architecture, Kubernetes Metrics Collection, Grafana Dashboards and Alerts
Lecture 14: Centralized Logging & Reliability - Centralized Logging Concepts, ELK Stack (Elasticsearch, Logstash, Kibana), Fluentd Log Forwarding, Troubleshooting and Alerting
Lecture 15: Serverless & Event-Driven Systems - Serverless Architecture Concepts, Serverless Framework, Event-Driven Workflows, CI/CD for Serverless Applications
Lecture 16: MLOps Foundations - What is MLOps and Why It Exists, DevOps vs MLOps Pipelines, ML Lifecycle from Data to Deployment, CI/CT/CD Concepts
Lecture 17: Data & Model Lifecycle Management - Data Versioning Using DVC/Pachyderm, Model Versioning & Storage, Model Registry (MLflow/Kubeflow), Feature Stores Overview
Lecture 18: AI Infrastructure & Production ML Operations - Specialized AI Infrastructure, GPU Orchestration on Kubernetes, AI Monitoring & Observability, Model Drift Detection, Model Interpretability Concepts

Azure DevOps & MLOps Engineer Program Skills Covered

Azure cloud administration & governance
Identity, access control & security design
Cloud networking & hybrid connectivity
Infrastructure as Code (Terraform & ARM)
CI/CD pipeline design & DevOps practices
GitOps & release management
Docker & Kubernetes (AKS)
Monitoring, logging & reliability engineering
Serverless & event-driven architectures
MLOps workflows & ML lifecycle management
AI infrastructure & production ML operations

Azure DevOps & MLOps Engineer Program Tools Covered

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Azure DevOps & MLOps Engineer Program Program Benefits

Azure DevOps & MLOps Engineer Program Program Benefits Illustration

CAREER OPPORTUNITIES AFTER THIS COURSE

DevOps Engineer Salary Range

Min

$600,000

Average

$1,000,000

Max

$1,800,000

Projects

MASTER CLOUD COMPUTING WITH REAL-WORLD PROJECTS

Comprehensive Multi-Cloud Deployment Experience

Industry-Aligned Advanced Scenarios

Build Enterprise-Grade Production Solutions

Cloud Infrastructure & Architecture
NO. OF PROJECTS: 8
DevOps & Automation
NO. OF PROJECTS: 7
Security, Compliance & FinOps
NO. OF PROJECTS: 5

Capstone Projects of this Program

Enterprise Multi-Cloud Infrastructure Deployment

Design and deploy enterprise-scale applications across AWS, Azure, and GCP using Infrastructure as Code with advanced networking and security configurations.

Advanced CI/CD Pipeline with Multi-Stage Deployment

Build comprehensive CI/CD pipelines using Jenkins and GitHub Actions with multi-environment deployments, automated testing, and rollback strategies.

Production-Grade Kubernetes Cluster Architecture

Deploy, scale, and manage production-ready microservices using Kubernetes with Helm charts, service mesh, and advanced monitoring.

Cloud Security & Compliance Framework Implementation

Implement comprehensive security controls including IAM policies, encryption, network security, and compliance frameworks (GDPR, HIPAA, ISO 27001).

Multi-Cloud Terraform Infrastructure Automation

Automate cloud resource provisioning and management using Terraform across AWS, Azure, and GCP with state management and modular architecture.

Enterprise Disaster Recovery & High Availability Solution

Design and implement enterprise-grade disaster recovery strategy with automated backup, failover mechanisms, and business continuity planning.

FinOps: Cloud Cost Optimization & Management Platform

Analyze and optimize cloud spending using FinOps principles, automated cost management tools, and resource right-sizing strategies.

Serverless Application Architecture with Event-Driven Design

Build scalable event-driven serverless applications using AWS Lambda, Azure Functions, and GCP Cloud Functions with API Gateway integration.

Hybrid Cloud Architecture Integration

Design and implement hybrid cloud solutions connecting on-premises infrastructure with cloud platforms using VPN, Direct Connect, and ExpressRoute.

Advanced Monitoring, Observability & SRE Implementation

Implement comprehensive monitoring and observability solutions using Grafana, Prometheus, and CloudWatch with SRE best practices.

Job Obligation After This Course

WE CAN APPLY FOR JOBS IN

Deploy, manage, and scale Azure cloud infrastructure following best practices.

Provision and automate resources using Terraform, ARM, Azure CLI, and PowerShell.

Design and manage compute, storage, networking, and hybrid connectivity solutions.

Implement CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, and GitOps.

Build and operate containerized applications using Docker and Kubernetes (AKS).

Apply RBAC, identity governance, and least-privilege access controls.

Monitor systems using Azure Monitor, Prometheus, Grafana, and ELK Stack.

Perform troubleshooting, incident response, and reliability engineering.

Implement backup, recovery, cost optimization, and high availability strategies.

Support MLOps workflows including data/model versioning and pipeline deployment.

Companies Hiring for this Course

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Admission Process

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

Course Fees & Financing

Course Fees

Upto

30%

Off

In USD

$1,300

In INR

1,09,999

Inclusive of All Taxes

Enroll Now →
Payment Partners

We partnered with financing companies to provide competitive finance options at 0% interest rate with no hidden costs.

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UPCOMING BATCHES/PROGRAM COHORTS

BatchDateTime (IST)Batch Type
Weekend Online Live Sessions1 March 2026Saturday & SundayBatch 1

COMPARISON WITH OTHERS

FeatureOur CourseCOMPETITOR ACOMPETITOR B
Course Duration400 hours (130 live + 40 pre-learning + 80 capstone + 150 self-paced)200-250 hours total150-200 hours with limited hands-on
Multi-Cloud CoverageComprehensive: AWS, Azure, and GCP with deep coverageSingle cloud focus (usually AWS only)Limited multi-cloud exposure
Hands-On Projects80 hours capstone + 20+ assignments + case studiesFew theoretical projectsLimited practical experience
DevOps & AutomationComprehensive: Terraform, Docker, Kubernetes, Jenkins, GitHub Actions, GitOpsBasic Docker and JenkinsLimited automation tools coverage
Instructor QualityIIT Faculty & Certified Industry Experts with real-world experienceIndustry trainers onlyMix of academic and industry professionals
Career Support1:1 Mock Interviews, 24/7 Support, Dedicated Learning Team, Placement AssistanceBasic placement assistanceLimited career support
Security & ComplianceDedicated module: GDPR, HIPAA, ISO 27001, Policy as Code, DevSecOpsBasic security conceptsMinimal compliance coverage
Advanced TopicsFinOps, Serverless, Hybrid Cloud, Multi-Cloud Integration, Advanced ArchitectureLimited advanced topicsFew advanced concepts covered

Official Partnership Recognition

Proud to be a Recognised Skilling Partner of IT-ITeS SSC Nasscom

Partnership Certificate
Verified

Certificate of Partnership

SkillzRevo Solutions Private Limited

Partnership Details

Organization

SkillzRevo Solutions Private Limited

Recognition Status

Recognised Skilling Partner

Certifying Authority

IT-ITeS SSC Nasscom

Validity Period

24/11/2025 - 24/11/2026

FutureSkills Prime Initiative

A MeitY - Nasscom Digital Skilling Initiative empowering professionals with cutting-edge IT skills

Active Partnership

10+

Year Partnership

100%

Certified

Committed to Excellence in Digital Skilling

As a recognized skilling partner, we are dedicated to delivering world-class IT training and development programs aligned with industry standards and government initiatives.

Skill IndiaIT-ITeS SectorNasscom Certified

Frequently Asked Questions