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iHUB IIT R

Advanced Certification in Cloud Computing and DevOps

4,644 Ratings

Ranked #1 Cloud Program by India Today

Learn from IIT Faculty & Industry Experts with Campus Immersion at iHUB, IIT Roorkee.
  • Master AWS, Azure, Google Cloud, DevOps, SRE, and AI CloudOps.
  • Build CI/CD pipelines, Kubernetes platforms, and production GenAI applications.
  • Complete 25+ industry Grade projects and two capstones.
  • Earn a prestigious certificate from iHUB IIT Roorkee & attend 2-day campus immersion.

In collaboration with

Microsoft
Certification Aligned to
AWS Aligned
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Course Introduction

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Learning Format

Online Bootcamp

Live Classes

6 Months

Campus Immersion

iHUB, IIT Roorkee

IITR iHUB

Certification

3100+

Hiring Partners

EMI Starts

at ₹5900/month*

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About Program

This program, offered with iHUB DivyaSampark, IIT Roorkee, builds practical expertise in designing, automating, securing, deploying, and monitoring modern cloud and AI workloads. Learners progress from cloud, Linux, and scripting foundations to AWS, Azure, Google Cloud, DevOps, DevSecOps, Kubernetes, SRE, AIOps, Generative AI, MLOps, LLMOps, and AgentOps.

Key Highlights

140 Hours of Core Live Learning across 6 Months
160+ Hours of Self-Paced Learning
Learn from IIT Faculty and Industry Professionals
AI Powered LMS for quick doubt clearance
25+ Industry-Aligned Projects and Case Studies
iHUB IIT Roorkee and Microsoft Certification
One-on-One Sessions with Industry Mentors
24/7 Support
No-Cost EMI Option
Placement Support by Intellipaat

About iHUB DivyaSampark, IIT Roorkee

iHUB DivyaSampark at IIT Roorkee, established under DST's NM-ICPS, accelerates innovation in AI, ML, and emerging technologies through research, startups, and industry collaboration across Healthcare, Industry 4.0, Smart Cities, and Defence.

Upon the completion of this program, you will:

  • Receive a certificate from iHUB DivyaSampark, IIT Roorkee

Benefits for students from Microsoft:

  • Industry-recognized certification from Microsoft
  • Real-time projects and exercises
Advanced Certification in Cloud Computing and Devops Certificate Image Click to Zoom

Program in Collaboration with Microsoft

Benefits for students from Microsoft:

  • Free Voucher for Exam AZ-900: Microsoft Azure Fundamentals worth $99
  • Industry-recognized certification from Microsoft
Az 104 module Click to Zoom

Career Transition

59% Average Salary Hike

$1,08,000 Highest Salary

40 LPA Highest Salary

700+ Career Transitions

3100+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Who Can Apply for the Course?

  • Anyone with a graduate degree and a keen interest to learn DevOps and cloud computing
  • IT professionals looking to shift to DevOps and cloud computing
  • Professionals wishing to get ahead in their careers
  • DevOps Professionals
  • Cloud computing professionals
  • Undergraduate freshers with an interest in DevOps and cloud computing
who can apply

What roles can a DevOps and cloud computing professional play?

Cloud Engineer

Design, deploy and manage secure cloud infrastructure and services.

DevOps Engineer

Build automated CI/CD pipelines and reliable delivery workflows.

Cloud Automation Engineer

Automate provisioning, configuration and operations using scripts and Infrastructure as Code.

Kubernetes Engineer

Deploy, scale and secure containerized applications on Kubernetes.

Junior Site Reliability Engineer

Monitor reliability, manage incidents and improve service performance.

Platform Engineer

Build standardized, self-service platforms and reusable developer workflows.

DevSecOps Engineer

Integrate security testing, policy controls and secrets management into delivery pipelines.

AI Cloud Engineer

Deploy, scale and monitor AI applications and services on cloud platforms.

MLOps and LLMOps Engineer

Manage model, prompt, evaluation, deployment and monitoring workflows.

AIOps Engineer

Use AI for log analysis, anomaly detection, event correlation, and incident investigation.

GenAI Deployment Engineer

Productionize RAG, foundation-model, and GenAI applications.

AgentOps Engineer

Operate AI agents with secure tool access, tracing, evaluation, and approval controls.

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Skills to Master

Multi-Cloud

Linux Automation

Cloud Networking

Serverless Computing

CI/CD

Infrastructure as Code

Container Orchestration

GitOps

Observability

Site Reliability

DevSecOps

AIOps

GenAI Deployment

AI Operations

Cloud Resilience

FinOps

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Tools to Master

AWS 1 azure Google Cloud GitHub jenkins Terraform ansible docker kubernetes helm argo promtheus Grafana

Meet Your Mentors

Curriculum

Live Course Industry Expert
  • Cloud service models: IaaS, PaaS, SaaS, public, private and hybrid cloud
  • Linux administration, processes, permissions, services and package management
  • Bash scripting and Python automation for cloud operations
  • Working with APIs, JSON, YAML, Git and GitHub
  • AI-assisted coding using GitHub Copilot, Amazon Q Developer, Claude and Cursor
  • Project: Build an AI-assisted cloud health-check and reporting tool
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  • AWS infrastructure, IAM, roles, policies and least-privilege access
  • EC2, S3, EBS, EFS, Auto Scaling and Elastic Load Balancing
  • Amazon VPC, subnets, security groups, Route 53 and CloudFront
  • RDS, Aurora, DynamoDB, Lambda, API Gateway, SQS and SNS
  • Containers and microservices using ECS, Fargate, EKS and ECR
  • Projects: Build three-tier, serverless and containerised AWS applications
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  • Amazon Q Developer for AWS architecture and CloudOps automation
  • AI-generated AWS CLI commands, Python scripts and shell automation
  • AI-assisted CloudFormation generation, validation and troubleshooting
  • IAM policy review, security-group analysis and privilege-risk detection
  • CloudWatch log analysis, incident investigation and root-cause analysis
  • Project: Build an AI-powered AWS operations and troubleshooting assistant
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  • Azure subscriptions, Resource Groups, Azure Resource Manager and governance
  • Microsoft Entra ID, RBAC, Azure Policy, resource locks and tagging
  • Azure Virtual Machines, Blob Storage, Azure Files and storage security
  • VNets, subnets, NSGs, Load Balancer, Application Gateway and Azure Firewall
  • App Service, Azure Functions, AKS, Azure SQL and Cosmos DB
  • Projects: Deploy secure, highly available and monitored Azure applications
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  • Microsoft Copilot for Azure administration and architecture recommendations
  • AI-generated Azure CLI, PowerShell, ARM and Bicep deployments
  • Microsoft Foundry, Azure OpenAI and foundation-model deployment
  • Deploying AI APIs using App Service, Azure Functions and AKS
  • AI observability using Azure Monitor and Application Insights
  • Project: Build and monitor an AI-powered Azure operations assistant
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  • DevOps lifecycle, Git, GitHub, branching, pull requests and collaborative development
  • Jenkins, Jenkinsfiles, GitHub Actions, GitLab CI/CD, Azure Pipelines and AWS CodePipeline
  • AI-assisted pipeline development using GitHub Copilot, Amazon Q Developer, Microsoft Copilot and GitLab Duo
  • Generating pipeline YAML, test cases, deployment scripts and technical documentation using AI
  • AI-powered code reviews, pipeline troubleshooting, failure analysis and remediation recommendations
  • Projects: Build AI-assisted CI/CD pipelines with testing, security scanning, deployment and rollback
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  • Terraform providers, resources, modules, state management and multi-cloud provisioning
  • Ansible inventories, playbooks, roles, templates, configuration management and Ansible Vault
  • Infrastructure automation using CloudFormation, ARM, Bicep, Helm and Argo CD
  • AI-generated Terraform modules, Ansible playbooks and cloud deployment templates
  • AI-assisted validation for security risks, configuration errors, drift and cloud-cost impact
  • Projects: Provision and secure AWS and Azure infrastructure using AI-assisted Infrastructure as Code
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  • Docker, Docker Compose, Dockerfiles, container networking, storage and image optimisation
  • Kubernetes pods, deployments, services, ingress, autoscaling, RBAC and network policies
  • Managed Kubernetes using Amazon EKS, Microsoft AKS and Google GKE
  • AI-assisted Kubernetes manifest creation, troubleshooting and cluster configuration analysis
  • Platform Engineering, Backstage, Internal Developer Platforms and AI-enabled developer self-service
  • Projects: Deploy, monitor and autoscale cloud-native microservices and AI inference applications
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  • Logs, metrics and traces using Prometheus, Grafana, OpenTelemetry, ELK and OpenSearch
  • Site Reliability Engineering using SLI, SLO, SLA, error budgets and capacity planning
  • AI-assisted log analysis, anomaly detection, event correlation and alert prioritisation
  • AI-powered root-cause analysis using Amazon Q, Microsoft Copilot and Datadog Bits AI
  • Generating incident summaries, operational runbooks and remediation recommendations using AI
  • Projects: Build an AI incident assistant and an intelligent SRE monitoring dashboard
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  • IAM, Microsoft Entra ID, least-privilege access, secrets management and encryption
  • SAST, DAST, dependency scanning, secret scanning, container scanning and IaC security
  • AI-assisted vulnerability analysis, security-policy generation and misconfiguration detection
  • Securing AI applications against prompt injection, sensitive-data leakage and tool misuse
  • AI guardrails, agent permissions, content filters, audit trails and human approval workflows
  • Projects: Build an AI-secured CI/CD pipeline and protect a Generative AI application
Download Brochure
  • Generative AI, foundation models, LLMs, prompt engineering and embeddings
  • Building applications with Amazon Bedrock, Azure OpenAI and Microsoft Foundry
  • Retrieval-Augmented Generation, vector databases, document ingestion and Knowledge Bases
  • AI agents, function calling, tools, enterprise APIs and cloud-data integration
  • LLM evaluation, hallucination testing, guardrails, latency and token-cost optimisation
  • Projects: Build and deploy enterprise RAG and serverless Generative AI applications
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  • ML lifecycle, experiment tracking, model registries, deployment and drift monitoring
  • MLflow, Amazon SageMaker MLOps and Azure Machine Learning fundamentals
  • Prompt versioning, model configuration, LLM tracing and automated AI evaluation
  • RAG evaluation for groundedness, relevance, retrieval quality and hallucination control
  • Agent tracing, tool permissions, human approvals, failure handling and cost monitoring
  • Project: Deploy an AI operations agent with evaluation, monitoring and controlled remediation
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  • Cloud-readiness assessment, workload discovery and AI-assisted migration planning
  • Rehosting, replatforming, refactoring and application-modernisation strategies
  • High availability, disaster recovery, multi-region architecture, RPO and RTO
  • AI-assisted cloud-cost analysis, rightsizing and cost-anomaly detection
  • Kubernetes, infrastructure and Generative AI token-cost optimisation
  • Project: Redesign an enterprise workload for migration, resilience, security and cost optimisation
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Capstone 1: AI-Powered Multi-Cloud DevSecOps Platform

  • Design production architecture across AWS and Microsoft Azure
  • Provision infrastructure using Terraform and Ansible
  • Build CI/CD pipelines using Jenkins or GitHub Actions
  • Deploy applications using Docker, Kubernetes, Helm and Argo CD
  • Implement DevSecOps, observability, AIOps, FinOps and disaster recovery
  • Create complete architecture, security and operational documentation

Capstone 2: Production-Grade Enterprise GenAI Application

  • Build using Amazon Bedrock, Azure OpenAI or Microsoft Foundry
  • Implement enterprise RAG, vector retrieval and document ingestion
  • Add authentication, RBAC, AI guardrails and data-protection controls
  • Deploy through containers, Kubernetes or serverless architecture
  • Implement LLM evaluation, agent tracing, observability and cost monitoring
  • Build CI/CD, autoscaling, resilience and operational documentation
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Elective

  • Google Cloud IAM, organisations, folders and projects
  • Compute Engine, Cloud Storage, VPC, Cloud SQL and Cloud Run
  • Google Kubernetes Engine, Cloud Functions and cloud monitoring
  • Vertex AI, Gemini Cloud Assist and AI application architecture
  • AWS, Azure and Google Cloud service mapping and multi-cloud governance
  • Project: Deploy a portable multi-cloud application using Terrafor`m and Docker
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Disclaimer
Intellipaat reserves the right to update the curriculum based on industry and employability needs.

Program Highlights

140 Hours of Core Live Learning across 6 Months
160+ Hours of Self-Paced Learning
25+ Industry-Aligned Projects and Case Studies
24/7 Support

Projects

You will be working on multiple projects to sharpen your skills on required technologies sought by top employers and gain industry-relevant experience.

Practice 20+ Essential Tools

Designed by Industry Experts

Get Real-world Experience

Reviews

(5)

Career Services By Intellipaat

Career Services
guaranteed
Placement assistance after successful program completion
job portal
Job-readiness support for cloud, DevOps and, AI infrastructure roles
Mock Interview Preparation
One-on-one career mentoring sessions
resume 1
Career-oriented sessions and job-search guidance
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Resume and LinkedIn profile support
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Experience Campus Immersion at iHub IIT Roorkee & Build Formidable Networks With Peers & IIT Faculty

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Hiring Partners

Admission Details

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.

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Submit Application

Tell us a bit about yourself and why you want to join this program

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Application Review

An admission panel will shortlist candidates based on their application

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Admission

Selected candidates will be notified within 1–2 weeks

Program Fee

Total Admission Fee

₹ 99,009 (Inclusive of All)

Apply Now

EMI Starts at

₹ 5,900

We partnered with financing companies to provide very competitive finance options at 0% interest rate

Financing Partners

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The credit facility is provided by a third-party financing company and any arrangement with such financing companies is outside.

Upcoming Application Deadline 8th Aug 2026

Admissions close once the required number of students is enrolled for the upcoming cohort. Apply early to secure your seat.

Program Cohorts

Next Cohorts

Next Cohorts

Date Time Batch Type
Program Induction 8th Aug 2026 08:00 PM - 11:00 PM IST Weekend (Sat-Sun)
Regular Classes 8th Aug 2026 10:00 AM - 01:00 PM IST Weekend (Sat-Sun)
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Other Cohorts

Others Cohorts

Date Time Batch Type
Program Induction 8th Aug 2026 07:00 AM - 09:00 AM IST Weekday (Tue-Fri)
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Frequently Asked Questions

How will I receive my certificate?

Upon completion of the advanced certification in cloud computing and the various projects and assignments, you will receive an advanced certification in cloud computing from iHUB DivyaSampark, IIT Roorkee.

This advanced certification in cloud computing is led by IIT Roorkee faculty and other industry experts who will train you in cloud computing and advanced DevOps skills through online live lectures and real-time industry-relevant projects.

The program is designed to help you gain in-depth knowledge in the field. Upon successful completion of the program, you will receive an advanced certification in cloud computing from iHUB DivyaSampark, IIT Roorkee. This certification is recognized by top organizations around the world and qualifies you for high-paying jobs in the market.

If you miss any of the live sessions, you will receive a copy of the recorded session within the next 12 hours. If you have further questions, you can ask them in our community or contact our course advisors.

This advanced certification in cloud computing will help you pass the Certified Kubernetes Administrator (CKA) and Docker Certified Associate (DCA) exams.

Please note that the course fees is non-refundable and we will be at every step with you for your upskilling and professional growth needs.

Due to any reason you want to defer the batch or restart the classes in a new batch then you need to send the batch defer request on [email protected] and only 1 time batch defer request is allowed without any additional cost.

Learner can request for batch deferral to any of the cohorts starting in the next 3-6 months from the start date of the initial batch in which the student was originally enrolled for. Batch deferral requests are accepted only once but you should not have completed more than 20% of the program. If you want to defer the batch 2nd time then you need to pay batch defer fees which is equal to 10% of the total course fees paid for the program + Taxes.

Yes, Intellipaat certification is highly recognized in the industry. Our alumni work in more than 10,000 corporations and startups, which is a testament that our programs are industry-aligned and well-recognized. Additionally, the Intellipaat program is in partnership with the National Skill Development Corporation (NSDC), which further validates its credibility. Learners will get an NSDC certificate along with Intellipaat certificate for the programs they enroll in.

All candidates applying for this course are eligible for equity-based seed funding and incubation support from iHUB DivyaSampark, IIT Roorkee, for their startup ideas. Enrolled students will have the opportunity to pitch their ideas to the iHUB DivyaSampark team, and shortlisted proposals may receive funding of up to ₹50 lakh, along with full incubation support.

Additionally, candidates who are currently enrolled in a degree program and have their startup idea approved may also receive a monthly fellowship/scholarship of ₹8,000 during the early phase of their project to encourage and support innovation.

The program runs for six months and includes 140 hours of live learning, 160+ hours of self-paced learning, projects, case studies and capstone mentoring.

The program covers AWS, Microsoft Azure and Google Cloud, along with multi-cloud architecture and workload-portability concepts.

Yes. The curriculum covers Git, Jenkins, GitHub Actions, CI/CD, Terraform, Ansible, Docker, Kubernetes, GitOps, security scanning, policy controls and secure delivery workflows.

Yes. Learners use Amazon Q Developer, Microsoft Copilot and Microsoft Foundry for architecture support, infrastructure automation, security reviews, troubleshooting, incident analysis and operational documentation.

Yes. The curriculum covers foundation models, Amazon Bedrock, Azure OpenAI, Microsoft Foundry, document ingestion, embeddings, vector databases, RAG, evaluation, guardrails, and production deployment.

Yes. Learners study model and prompt versioning, evaluation, monitoring, tracing, agent permissions, human approvals, failure handling, and cost optimization.

Yes. Google Cloud and multi-cloud architecture are covered through an elective module that includes IAM, Compute Engine, Cloud Storage, Cloud Run, GKE, Cloud Functions, and cross-cloud service mapping.

Yes. Graduates can begin with the preparatory learning path and progress toward entry-level cloud, DevOps, Kubernetes, platform, and junior SRE roles.

Advanced cloud or DevOps experience is not required. The self-paced foundation path introduces Linux, networking, Python, shell scripting, Git, SQL, and cloud fundamentals.

Relevant roles include Cloud Engineer, DevOps Engineer, Cloud Automation Engineer, Kubernetes Engineer, Junior Site Reliability Engineer, Platform Engineer, DevSecOps Engineer, AI Cloud Engineer, MLOps Engineer, LLMOps Engineer, AIOps Engineer, GenAI Deployment Engineer, and AgentOps Engineer.

Yes. The program includes a two-day campus immersion at iHUB, IIT Roorkee.

Learners validate AI-generated code and infrastructure, protect credentials and sensitive data, test changes in non-production environments, maintain audit trails and use human approval for sensitive actions.

AI helps Cloud Engineers automate deployments, optimize costs, strengthen security, and resolve issues faster. This program teaches you how to combine AI with AWS, Azure, and Google Cloud to build intelligent, production-ready cloud solutions.

You’ll gain hands-on experience with Amazon Q Developer, Microsoft Copilot, Microsoft Foundry, Amazon Bedrock, and Azure OpenAI for cloud automation, infrastructure management, AI application development, and operations.

AI is integrated across the curriculum to automate cloud deployments, generate Infrastructure-as-Code, troubleshoot environments, optimize cloud resources, enhance security, and deploy enterprise AI applications.

Yes. You’ll learn to deploy Generative AI applications using Amazon Bedrock, Azure OpenAI, RAG, vector databases, and cloud-native services, following enterprise deployment and monitoring best practices.

Yes. You’ll complete 25+ industry projects and two production-grade capstone projects covering cloud architecture, DevOps, Kubernetes, AI deployment, RAG, and cloud automation to build a job-ready portfolio.

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What is included in this course?

  • Non-biased career guidance
  • Counselling based on your skills and preference
  • No repetitive calls, only as per convenience
  • Rigorous curriculum designed by industry experts
  • Complete this program while you work