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Cloud & DevOps

Beginner to Mastery

AWS DevOps & MLOps Engineer Program

End-to-end AWS cloud engineering with real-world use cases

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

Containerization & Kubernetes with Docker, EKS, ECS, and Helm"

Production-grade monitoring & reliability with AWS, Prometheus, Grafana, and ELK

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

Course Duration

400 Hours

Next Batch

08 Feb 2026

Course Material

Live. Online. Interactive.

Practical MLOps exposure for model lifecycle and production ML systems

Weekly sessions with industry professionals

Dedicated Learning Management Team

400+ hours of hands-on learning experience

Highlight AWS DevOps & MLOps Engineer Program

KEY HIGHLIGHTS OF AWS DEVOPS & MLOPS ENGINEER PROGRAM PROGRAM

  • Over 100 hours of live sessions for real-time interaction
  • Dedicated bridge classes to ensure seamless progression from AWS to DevOps and MLOps.
  • Learn from Cloud Certified Industry Experts
  • More than 20+ industry-related projects and case studies
  • Personalized mentorship sessions with cloud experts
  • 24*7 Support
  • 1:1 Mock Interviews & Portfolio Building
  • Designed for both working professionals and fresh graduates
  • No-Cost EMI Option available
  • High Demand Skillset with Global Career Opportunities
  • Mastery of GitOps, IaC, and AI-Infrastructure

WHY JOIN AWS DEVOPS & MLOPS ENGINEER PROGRAM PROGRAM?

Strong AWS Foundations

AWS architecture, security, networking, governance, and cost optimization.

Hands-on DevOps & Automation

CI/CD, Terraform, CloudFormation, GitOps, Kubernetes on AWS.

Industry-Relevant Tools

AWS, Docker, Kubernetes, CI/CD, observability, and MLOps.

Career-Oriented

Prepares for AWS Cloud, DevOps, Platform, and MLOps Engineer roles.

UPCOMING BATCH:

08 Feb 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

AWS DevOps & MLOps Engineer Program OVERVIEW

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

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

Enroll Now →

AWS DevOps & MLOps Engineer Program Objectives

The primary objective of this program is to build industry-ready AWS DevOps & MLOps Engineers with strong practical skills beyond tools and certifications. The focus is on real enterprise workflows, automation, scalability, and reliability.Learners will understand when, why, and how to apply AWS 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 AWS DevOps & MLOps Engineer Program ?

Industry-Focused Learning

Skills aligned with real enterprise AWS, DevOps, and MLOps environments.

AWS-Centric Cloud Expertise

Deep hands-on experience with AWS architecture, services, security, and best practices.

End-to-End DevOps Skills

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

Strong Automation & IaC Foundation

Infrastructure automation using Terraform, CloudFormation, and configuration management.

Containers & Kubernetes at Scale

Build, deploy, and manage applications using Docker, Amazon EKS/ECS, and Helm.

Production Monitoring & Reliability

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

MLOps & AI Infrastructure Readiness

Data versioning, model lifecycle management, AI infrastructure, and model monitoring basics.

Role-Based Career Preparation

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

Program Advantages

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

End-to-end learning from AWS 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

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

Description

AWS DevOps & MLOps Engineer Program program Certifications

AWS DevOps & MLOps Engineer Program Curriculum

Lecture 01: DevOps principles implemented through real delivery workflows, CI/CD lifecycle mapped end-to-end, Agile vs DevOps vs SRE through real team models, Toolchain overview via practical pipeline mapping
Lecture 2: Git workflows for real projects, Branching, PRs, and release strategies, GitOps principles using Git as source of truth, Intro to CI systems (GitHub, GitLab, Jenkins)
Lecture 3: CI/CD pipeline design and execution, GitHub Actions, GitLab CI, Jenkins, Secure pipelines and environment separation
Lecture 4: Build automation concepts (Maven / Gradle overview), Dependency and artifact management, Sonatype Nexus for artifact storage, CI integration with, artifact repositories
Lecture 5: Shift-left testing concepts, Test stages in CI/CD, pytest for automated testing, Quality gates and reports
Lecture 6: IaC concepts and workflow, Terraform providers, Resource provisioning, Local state management
Lecture 7: Terraform variables, outputs, and workspaces, Remote state & state locking, AWS CloudFormation & Terraform modules, Terraform vs native cloud templates
Lecture 8: Configuration vs provisioning, Ansible, Puppet, Chef comparison, Agent vs agentless models, Automated configuration workflows
Lecture 9: Containers vs VMs, Images, containers, registries, Dockerfiles and image optimization, Container security basics
Lecture 10: Kubernetes architecture, Pods, Deployments, Services, Configuration & secrets, Scaling and rolling updates
Lecture 11: Advanced Kubernetes deployments, Helm charts and templating, Environment-based deployments, Release and rollback strategies
Lecture 12: Declarative deployment models, GitOps workflows, CI vs GitOps CD, Kubernetes GitOps pipelines
Lecture 13: Monitoring vs observability, Prometheus architecture, Kubernetes metrics collection, Grafana dashboards and alerts
Lecture 14: Centralized logging concepts, ELK Stack (Elasticsearch, Logstash, Kibana), Fluentd log forwarding, Troubleshooting and alerting
Lecture 15: Serverless architecture concepts, Serverless framework, Event-driven workflows, CI/CD for serverless applications
Lecture 16: What is MLOps and why it exists, DevOps vs MLOps pipelines, ML lifecycle from data to deployment, CI/CT/CD concepts
Lecture 17: Data versioning using DVC / Pachyderm, Model versioning & storage, Model Registry (MLflow / Kubeflow concepts), Feature stores overview and usage
Lecture 18: Specialized AI infrastructure, GPU orchestration on Kubernetes, AI monitoring & observability, Model drift detection, Model interpretability concepts

AWS DevOps & MLOps Engineer Program Skills Covered

AWS Cloud Architecture & Administration
Cloud Security & Governance
CI/CD Pipeline Engineering
Infrastructure as Code (IaC)
Containerization & Kubernetes Engineering
GitOps & Release Management
Observability & Reliability Engineering
Serverless & Event-Driven Architectures
MLOps & AI Production Operations
Production Troubleshooting & Optimization

AWS DevOps & MLOps Engineer Program Tools Covered

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AWS DevOps & MLOps Engineer Program Program Benefits

AWS DevOps & MLOps Engineer Program Program Benefits Illustration

CAREER OPPORTUNITIES AFTER THIS COURSE

DevOps Engineer Salary Range

Min

$600,000

Average

$1,000,000

Max

$2,000,000

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 AWS cloud infrastructure following AWS Well-Architected and enterprise best practices.

Provision and automate AWS cloud resources using Terraform and AWS CloudFormation.

Design and manage compute, storage, networking, and security services on AWS (EC2, S3, VPC, RDS, IAM, etc.).

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

Build, deploy, and operate containerized applications using Docker and Kubernetes (Amazon EKS / ECS).

Apply IAM-based identity governance, security policies, least-privilege access, MFA, and compliance controls.

Monitor AWS infrastructure and applications using CloudWatch, Prometheus, Grafana, and ELK Stack.

Perform troubleshooting, incident response, alerting, and reliability engineering in production environments.

Implement backup, disaster recovery, cost optimization, auto-scaling, and high-availability strategies on AWS.

Support MLOps workflows, including data and model versioning, pipeline deployment, model monitoring, and AI infrastructure operations.

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

$1099

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 Sessions1st Week of March 2026Saturday & SundayBatch 1
Weekend Online Live SessionsTBDSaturday & SundayBatch 2

COMPARISON WITH OTHERS

FeatureOur CourseCOMPETITOR A
Cloud FocusAWS-first, production-gradeTool-based or certification-only
DevOps CoverageEnd-to-end CI/CD, GitOps, IaCLimited pipeline exposure
KubernetesAdvanced EKS, Helm, GitOpsBasic container concepts
ObservabilityPrometheus, Grafana, ELK, AWS toolsMinimal monitoring coverage
MLOpsFull ML lifecycle & AI opsUsually not included
Learning ApproachReal enterprise workflowsMostly theoretical
Job ReadinessHigh – production alignedMedium

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