Cloud & DevOps
Beginner to Mastery
End-to-end DevOps → Cloud → Kubernetes → MLOps delivery lifecycle
CI/CD pipelines built using GitHub Actions, GitLab CI & Jenkins
GitOps + Declarative delivery for cloud & Kubernetes
Infrastructure provisioning using Terraform & Cloud templates
250 Hours
01 March 2026
Live. Online. Interactive.
Containerization & Kubernetes from fundamentals to production-grade deployments
Serverless & event-driven CI/CD pipelines
Observability, logging & reliability engineering using Prometheus, Grafana & ELK
Containerization & Kubernetes from fundamentals to production-grade deployments
DevOps principles taught through real delivery workflows, not theory.
Pipelines, branching strategies, secure CI, and GitOps-based CD.
Terraform, cloud templates, configuration management & automation.
Docker → Kubernetes → Helm → GitOps deployments.
Observability, logging, alerting & troubleshooting like real SRE teams.
AI pipelines, GPU orchestration & ML production operations
01 March 2026
30 MINUTE MEETING
Web conferencing details provided upon confirmation.
Corporate Training, Enterprise training for teams
| Batch | Batch Type |
|---|---|
| Online Live Instructor Led Session | Full-Time |
| Online Live Instructor Led Session | Part-Time |
| Batch | Batch Type |
|---|---|
| IST (India Standard Time) | 09:00 PM–12:00 AM |
| Bahrain, Qatar, Kuwait, Saudi Arabia | 06:30 PM–09:30 PM |
| UAE / Oman | 07:30 PM–09:00 PM |
This program is designed to build industry-ready DevOps, Cloud, and MLOps engineers by closely aligning with a real-world enterprise delivery lifecycle. The learning journey begins with strong foundations in DevOps practices and CI/CD pipelines, then progressively moves into Infrastructure as Code (IaC) and Kubernetes engineering. It further covers system monitoring, reliability engineering, and serverless architectures, and finally concludes with advanced topics such as MLOps, AI pipelines, and production-grade machine learning infrastructure, ensuring learners are fully prepared for modern cloud-native and AI-driven environments.
ENROLL NOW, BOOK YOUR SEAT & AVAIL UPTO 30% FEE WAIVER
Enroll Now →The primary objective of this program is to make learners capable of designing, building, deploying, monitoring, and operating production-grade systems across DevOps and CI/CD, Cloud and Kubernetes, observability and reliability engineering, as well as serverless architectures and MLOps pipelines. The focus is on developing deep practical understanding so that learners know when, why, and how to use the right tools in real-world scenarios, rather than just learning what a tool is.
Enroll Now →Skills aligned with real enterprise AWS environments and operational best practices.
Real workflows used by DevOps, SRE & Platform teams.
From code commit → CI → CD → infra → monitoring.
Terraform, GitOps & pipeline automation.
Production-grade deployments & rollbacks.
Monitoring, logging, alerting & optimization.
Rare combination in DevOps programs.
Hands-on labs and architecture mapping based on real production use cases.
Prepared for DevOps Engineer, MLOps Engineer, and Infrastructure roles.
Job-ready DevOps + Cloud + MLOps skills
Strong focus on real production environments
GitOps & Kubernetes-first approach
Covers future DevOps roles, not just current trends
Suitable for product, platform & AI teams
Min
$550,000
Average
$900,000
Max
$1,600,000
Comprehensive Multi-Cloud Deployment Experience
Industry-Aligned Advanced Scenarios
Build Enterprise-Grade Production Solutions
WE CAN APPLY FOR JOBS IN
Design, implement, and maintain robust CI/CD pipelines for automated build and deployment
Manage GitOps-based deployment workflows for scalable and reliable releases
Provision, manage, and optimize cloud infrastructure using Terraform (IaC)
Deploy, operate, and scale Kubernetes workloads in production environments
Implement monitoring, logging, and alerting for system observability and reliability
Design and manage serverless and event-driven architectures
Support and operate ML pipelines and AI infrastructure in production
Troubleshoot, debug, and resolve production incidents to ensure high availability and performance
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.
We partnered with financing companies to provide competitive finance options at 0% interest rate with no hidden costs.
| Batch | Date | Time (IST) | Batch Type |
|---|---|---|---|
| Weekend Online Live Sessions | 1st March 2026 | Saturday & Sunday | Batch 1 |
| Weekend Online Live Sessions | TBD | Saturday & Sunday | Batch 2 |
| Feature | Our Course | COMPETITOR A | COMPETITOR B |
|---|---|---|---|
| Foundations | DevOps foundations mapped to real delivery workflows (Chapter 1) | Theory-based DevOps concepts | General terminology overview |
| CI/CD | Multi-tool pipelines: GitHub Actions, GitLab CI, Jenkins (Chapter 3) | Single-tool CI demos | Basic pipeline theory |
| GitOps | Dedicated GitOps + declarative CD (Chapter 2 & 5) | Rarely covered | Missing or brief mention |
| IaC | Terraform basics → advanced → cloud templates (Chapter 4) | Only basic Terraform | Introduction to IaC only |
| Config Management | Ansible / Puppet / Chef comparison with workflows | Tool overview only | Single tool focus |
| Containers | Docker → Kubernetes → Helm → GitOps CD (Chapter 5) | Docker + basic K8s | Introduction to containers |
| Observability | Prometheus, Grafana, ELK with troubleshooting (Chapter 6) | Monitoring overview | Basic logging setup |
| Serverless | CI/CD for serverless & event-driven systems (Chapter 7) | Optional topic | Not covered |
| MLOps | Full MLOps lifecycle + CI/CT/CD (Chapter 8) | Not included | Missing |
| AI Infra | GPU orchestration, ML monitoring, drift detection (Chapter 9) | Completely missing | N/A |
| Outcome | DevOps + Cloud + MLOps Engineer readiness | Entry-level DevOps only | General IT operations knowledge |
Proud to be a Recognised Skilling Partner of IT-ITeS SSC Nasscom
Certificate of Partnership
SkillzRevo Solutions Private Limited
Organization
SkillzRevo Solutions Private Limited
Recognition Status
Recognised Skilling Partner
Certifying Authority
IT-ITeS SSC Nasscom
Validity Period
24/11/2025 - 24/11/2026
A MeitY - Nasscom Digital Skilling Initiative empowering professionals with cutting-edge IT skills
10+
Year Partnership
100%
Certified
As a recognized skilling partner, we are dedicated to delivering world-class IT training and development programs aligned with industry standards and government initiatives.
