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Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer

⚡ Powered by AI-Driven Cloud & Automation

Seamlessly work across AWS, Azure, Kubernetes, and multi-cloud environments.

Hands-on training with Terraform, Docker, Kubernetes, CI/CD, and Infrastructure Automation.

Build real-world DevOps, MLOps, LLMOps and AI deployment pipelines beyond basic projects.

Learn EKS (AWS), AKS (Azure), AI orchestration, monitoring, and scalable cloud operations.

Group Enrollment with Friends or Colleagues
Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer

Course Duration

600 Hours

Next Batch

31 May 2026

Course Material

Live. Online. Interactive.

Stay ahead with AI Infrastructure, Data Versioning, MLOps, AIOps, and LLMOps technologies.

Specialized sessions to connect Cloud, DevOps, AI, and automation concepts effectively.

Focus on practical multi-cloud architecture and real-world automation using production-grade DevOps tools.

Enhance career opportunities in roles like Cloud Architect, DevOps Engineer, MLOps Engineer, and AI Infrastructure Specialist.

Highlight Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer

KEY HIGHLIGHTS OF ADVANCED MULTI-CLOUD DEVOPS, MLOPS AIOPS & LLMOPS ENGINEER PROGRAM

  • Weekly sessions with industry professionals
  • Dedicated Learning Management Team
  • 600+ hours of hands-on learning experience
  • Over 150 hours of live sessions for real-time interaction
  • Specialized Bridge Classes for smooth AWS-to-Azure transitions
  • 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 ADVANCED MULTI-CLOUD DEVOPS, MLOPS AIOPS & LLMOPS ENGINEER PROGRAM?

Comprehensive Cloud Training

Gain expertise in AWS, Azure, multi-cloud architecture, DevOps, and AI-driven infrastructure systems.

Hands-On Automation

Work on real-world projects involving CI/CD, Infrastructure as Code (IaC), Kubernetes, and cloud automation.

Industry-Relevant Curriculum

Learn modern DevOps, GitOps, MLOps, AIOps, and LLMOps tools used in production environments.

Career Growth

Prepare for high-demand roles in Cloud Engineering, DevOps, MLOps, AI Infrastructure, and automation domains.

The Multi-Cloud Advantage

Build expertise in both AWS and Azure to manage scalable and enterprise-grade multi-cloud environments.

Production-Ready DevOps

Go beyond basic deployment pipelines with Kubernetes, GitOps, observability, and Infrastructure Automation.

Next-Gen Tech

Learn MLOps, AIOps, LLMOps, AI Infrastructure, and intelligent cloud operations aligned with future industry demands.

Zero-to-Hero Labs

Every module includes practical labs, real-world deployment tasks, and hands-on cloud implementation experience.

UPCOMING BATCH:

31 May 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

Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer OVERVIEW

This comprehensive program is designed to build strong cloud fundamentals, hands-on administration skills, and production-ready expertise across AWS, Microsoft Azure, DevOps, MLOps, AIOps, and LLMOps practices. The curriculum follows an industry-aligned, role-based learning path covering cloud architecture, security, networking, automation, CI/CD, containers, Kubernetes, observability, AI infrastructure, and intelligent cloud operations. The program blends conceptual clarity, real-world scenarios, practical labs, and architecture-driven thinking, enabling learners to confidently design, automate, deploy, and manage modern cloud-native and hybrid environments.

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Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer Objectives

The primary objective of this program is to develop industry-ready Cloud, DevOps, and MLOps Engineers with skills that go beyond basic tools and certifications. The program focuses on practical, job-oriented learning, enabling learners to work confidently in real enterprise cloud environments. It provides hands-on exposure to AWS, Microsoft Azure, DevOps, Kubernetes, MLOps, AIOps, and Infrastructure Automation, covering how modern cloud platforms are designed, secured, automated, monitored, and scaled in production. Being “JOB-READY” in this program means learners understand when, why, and how to implement cloud and DevOps technologies based on real business requirements. Through practical labs, deployment workflows, and production-style scenarios, learners build strong execution and problem-solving skills, preparing them for roles such as Cloud Engineer, DevOps Engineer, SRE, Platform Engineer, and MLOps professional.

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Why Learn Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer ?

Industry-Focused Learning

Learn practical skills based on real enterprise cloud, DevOps, and automation environments.

Multi-Cloud Expertise (AWS & Azure)

Gain hands-on experience with the most widely used cloud platforms and services.

End-to-End DevOps Skills

Understand the complete DevOps lifecycle from development, deployment, automation, and monitoring.

Strong Automation & IaC Foundation

Master Infrastructure as Code using Terraform, ARM templates, and cloud automation tools.

Containers & Kubernetes at Scale

Build, deploy, and manage containerized applications using Docker, Kubernetes, EKS, and AKS.

Production Monitoring & Reliability

Learn observability, logging, monitoring, troubleshooting, and production system reliability practices.

Serverless, AI Infrastructure & MLOps

Gain exposure to serverless computing, MLOps workflows, AIOps, and AI infrastructure concepts.

Role-Based Career Preparation

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

Program Advantages

Industry-driven curriculum aligned with current cloud, DevOps, MLOps, and automation industry standards.

Job-ready learning focused on real-world cloud operations and production DevOps practices.

Hands-on experience across AWS, Microsoft Azure, Kubernetes, and multi-cloud environments.

End-to-end training covering cloud fundamentals, DevOps, CI/CD, Kubernetes, and MLOps workflows.

Practical exposure to production-grade architectures, monitoring, automation, and deployment practices.

Strong focus on Infrastructure as Code, GitOps, CI/CD pipelines, and cloud automation tools.

Learn modern industry-standard technologies used in real enterprise DevOps and cloud teams.

Curriculum designed for roles such as Cloud Engineer, DevOps Engineer, SRE, and Platform Engineer.

Future-ready skill development with serverless computing, AI infrastructure, MLOps, and AIOps concepts.

Description

Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer program Certifications

Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer Curriculum

Lecture 1: AWS Well-Architected Framework - Introduction to AWS Well-Architected Framework, Six pillars (Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, Sustainability).
Lecture 2: Cloud Economics & Cost Optimization - Fixed cost vs variable cost, CapEx vs OpEx, Rightsizing, Automation benefits, Managed services vs self-managed.
Lecture 3: Migration to AWS & AWS CAF - Cloud migration benefits, AWS Cloud Adoption Framework (CAF), Migration strategies (6 Rs overview), AWS Snow Family, AWS Migration Hub.
Lecture 4: AWS Shared Responsibility Model - AWS responsibility vs Customer responsibility, Responsibility shift by service: EC2 vs RDS vs Lambda.
Lecture 5: AWS Security Services Overview - Encryption at rest & in transit, AWS Artifact, Compliance programs, Logging & monitoring overview, Services (CloudTrail, CloudWatch, AWS Config, Audit Manager).
Lecture 6: Identity & Access Management - IAM users, groups, roles, Policies (managed vs inline), Principle of least privilege, Root user protection, MFA & federated access.
Lecture 7: Network & Application Security - Security Groups vs NACLs, AWS WAF, AWS Shield, GuardDuty, Inspector, Security Hub, Trusted Advisor (security checks).
Lecture 8: AWS Compute Services - Amazon EC2 basics, Instance types, Auto Scaling, Load Balancers, AWS Lambda, AWS Elastic Beanstalk, AWS Lightsail.
Lecture 9: Containers & Serverless - Amazon ECS, Amazon EKS, Serverless architecture benefits, When to use containers vs Lambda.
Lecture 10: AWS Storage Services - Amazon S3 & storage classes, S3 lifecycle policies, Amazon EBS, Amazon EFS, Amazon FSx, AWS Backup, Storage Gateway.
Lecture 11: AWS Database Services - Relational databases (RDS, Aurora), NoSQL (DynamoDB), In-memory databases, Database migration tools (AWS DMS, AWS SCT).
Lecture 12: AWS Networking Services - Amazon VPC, Subnets, route tables, gateways, Route 53, AWS VPN, Direct Connect, CloudFront, Global Accelerator.
Lecture 13: Analytics Services - Amazon Athena, AWS Glue, Amazon Kinesis, Amazon QuickSight, Amazon Redshift (overview).
Lecture 14: AWS Pricing Models - OnDemand, Reserved Instances, Spot Instances, Savings Plans, Data transfer costs, Storage pricing.
Lecture 15: Cost Management & AWS Support - AWS Budgets, Cost Explorer, Pricing Calculator, AWS Organizations, Support plans (Basic, Developer, Business, Enterprise), AWS Marketplace, AWS Partner Network.
Lecture 16: Governance & Subscriptions - Azure subscriptions & management, Resource locks, Tags and cost tracking, Azure Policy (built-in & custom), Lab: Manage subscriptions & governance.
Lecture 17: Subscriptions & Access Control - Role-Based Access Control (RBAC), Azure RBAC concepts, Built-in roles vs custom roles, Scope: management group, Best practices for access control, Lab: Manage RBAC permissions.
Lecture 18: Azure Administration Tools - Azure Resource Manager (ARM), Azure Portal, Azure Cloud Shell, Azure PowerShell, Azure CLI, Lab: Manage Azure resources using Portal.
Lecture 19: ARM Templates & Automation - ARM templates structure, Parameters & variables, Deployment modes, Benefits of Infrastructure as Code, Labs: Deploy resources using ARM, Azure PowerShell & CLI automation.
Lecture 20: Virtual Networking Fundamentals - Azure Virtual Networks (VNets), Subnets & IP addressing, Public vs private IPs, Network Security Groups (NSGs), Lab: Implement virtual networking.
Lecture 21: Advanced Networking & DNS - Azure Firewall, Azure DNS, Private vs public DNS zones, Network security design patterns.
Lecture 22: Intersite Connectivity - VNet peering, VPN gateways, Site-to-site & point-to-site VPNs, Express Route & Virtual WAN, Lab: Implement intersite connectivity.
Lecture 23: Network Traffic Management - Network routing & service endpoints, Azure Load Balancer (L4), Azure Application Gateway (L7), Azure Traffic Manager, Lab: Implement traffic management.
Lecture 24: Designing Azure Network Solutions - Choosing correct networking solutions, High availability networking, Network security scenarios, Exam-oriented networking questions.
Lecture 25: Azure Storage Fundamentals - Storage accounts, Blob storage & containers, Storage tiers, Storage security (keys, SAS), Lab: Manage Azure storage accounts.
Lecture 26: Azure Files, File Sync & Storage Tools - Azure Files, Azure File Sync, Storage Explorer, Backup and recovery basics.
Lecture 27: Azure Virtual Machines - VM planning & sizing, Creating VMs, Availability sets & zones, Virtual Machine Scale Sets (VMSS), Lab: Manage Azure virtual machines.
Lecture 28: VM Management & Extensions - VM extensions, Custom Script Extension, Monitoring VMs, VM backup overview.
Lecture 29: Serverless & Containers - Azure App Service plans, Web Apps, Azure Container Instances (ACI), Azure Kubernetes Service (AKS), Labs: Implement Web Apps, Implement ACI, Implement AKS.
Lecture 30: Data Protection & Backup - Azure Backup, Recovery Services vault, File & folder backups, VM backup & restore, Lab: Implement data protection.
Lecture 31: Monitoring Azure Infrastructure - Azure Monitor, Metrics & logs, Azure Alerts, Log Analytics workspace, Network Watcher, Lab: Implement monitoring & alerts.
Lecture 32: End-to-End Azure Administration Scenarios - Identity -> Networking -> Compute -> Storage flow, Real-world Azure admin scenarios, Architecture mapping.
Lecture 33: DevOps Foundations & Modern Delivery - 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 34: Jenkins & Infrastructure as Code Terraform Basics - CI/CD pipeline design and execution, Secure pipelines and environment separation, IaC concepts and workflow, Terraform providers, Resource provisioning, Local state management.
Lecture 35: Terraform Advanced & Configuration Management - Terraform variables, outputs, and workspaces, Remote state & state locking, AWS CloudFormation & Terraform modules, Terraform vs native cloud templates, Ansible configuration vs provisioning, Agent vs agentless models, Automated configuration workflows.
Lecture 36: Docker Fundamentals - Containers vs VMs, Images, containers, registries, Dockerfiles and image optimization, Container security basics.
Lecture 37: Kubernetes Core Concepts - Kubernetes architecture, Pods, Deployments, Services, Configuration & secrets, Scaling and rolling updates.
Lecture 38: Kubernetes Advanced & Artifact Management - Advanced Kubernetes deployments, Helm charts and templating, Environment-based deployments, Release and rollback strategies, Build automation concepts (Maven / Gradle overview), Dependency and artifact management.
Lecture 39: Observability & Monitoring - Sonatype Nexus for artifact storage, CI integration with artifact repositories, Monitoring vs observability, Prometheus architecture, Kubernetes metrics collection, Grafana dashboards and alerts.
Lecture 40: Centralized Logging & Reliability - Centralized logging concepts, ELK Stack (Elasticsearch, Logstash, Kibana), Fluentd log forwarding, Troubleshooting and alerting.
Lecture 41: Automated Testing in Pipelines - Shift-left testing concepts, Test stages in CI/CD, pytest for automated testing, Quality gates and reports.
Lecture 42: Serverless & Event-Driven Systems - Serverless architecture concepts, Serverless framework, Event-driven workflows, CI/CD for serverless applications.
Lecture 43: MLOps Foundations & ML Workflow - Introduction to MLOps, ML Lifecycle, Environment Setup, Model Serialization & Configuration Management.
Lecture 44: Testing, Code Quality & Experiment Tracking - Unit Testing, ML Code Validation, Experiment Tracking, Model Registry.
Lecture 45: Data & Model Versioning with Automation - Dataset Versioning, Model Artifact Management, Reproducibility, Pipeline Automation Basics.
Lecture 46: Hyperparameter Tuning & API Development - Hyperparameter Optimization, Model Packaging, API Development for Predictions.
Lecture 47: Model Deployment & Scalable Serving - Model Deployment Strategies, Real-Time Inference, Scalable Model Serving.
Lecture 48: Workflow Orchestration & Production Pipelines - Workflow Automation, Pipeline Orchestration, Scheduling & Monitoring.
Lecture 49: IT Operations & Observability Foundations - Infrastructure Context, CMDB, Topology Mapping, Metrics, Logs & Traces.
Lecture 50: AI & Machine Learning for IT Operations - AI/ML Basics, Anomaly Detection, Time-Series Forecasting, Intelligent Alerting.
Lecture 51: Event Correlation & Root Cause Analysis - Event Correlation, Noise Reduction, Alert Deduplication, Root Cause Analysis (RCA).
Lecture 52: Data Collection, Streaming & Enterprise AIOps Platforms - Data Ingestion, Real-Time Stream Processing, Enterprise Monitoring Platforms.
Lecture 53: ITSM Integration, ChatOps & Automation - ITSM Integration, ChatOps, Event-Driven Automation, Self-Healing Systems.
Lecture 54: Cloud-Native AIOps, Scalability & FinOps - Cloud Monitoring, Kubernetes Scaling, AI-Driven Cost Optimization, Production Best Practices.
Lecture 55: Introduction to LLMs & Enterprise AI - LLM Fundamentals, Transformer Basics, Enterprise AI Use Cases, Model Selection.
Lecture 56: Prompt Engineering & Reasoning Techniques - Prompt Engineering, Few-shot Prompting, Chain-of-Thought, ReAct Prompting.
Lecture 57: RAG Architecture & Vector Databases - Embeddings, Vector Databases, Retrieval-Augmented Generation (RAG).
Lecture 58: LLM Application Development & Orchestration - AI Workflow Orchestration, Prompt Chaining, Context Management.
Lecture 59: LLM Deployment Monitoring & Optimization - Inference Serving, Evaluation, Observability, Cost Monitoring.
Lecture 60: Security, Guardrails & Production Readiness - AI Security, Prompt Injection Defense, Hallucination Prevention, PII Protection, Governance.

Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer Skills Covered

AWS and Azure Cloud Fundamentals
Cloud Security and Identity Management
Infrastructure as Code (Terraform, ARM, IaC)
CI/CD Pipelines and Cloud Automation
Containerization with Docker
Kubernetes Orchestration and Cluster Management
Cloud Networking and Architecture Basics
Monitoring, Logging, and Observability
Production-Grade Troubleshooting and Cloud Operations
GitOps, DevOps, and Deployment Workflows
Serverless Computing Fundamentals
MLOps, AIOps, and AI Infrastructure Concepts

Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer Tools Covered

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Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer Program Benefits

Advanced Multi-Cloud DevOps, MLOps AIOps & LLMOps Engineer Program Benefits Illustration

CAREER OPPORTUNITIES AFTER THIS COURSE

Cloud DevOps Engineer Salary Range

Min

$700,000

Average

$1,200,000

Max

$2,200,000

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 cloud infrastructure across AWS and Microsoft Azure environments.

Provision and automate infrastructure using Terraform, ARM Templates, CloudFormation, and IaC practices.

Design and manage compute, storage, networking, and database services in multi-cloud environments.

Implement CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, and Azure DevOps tools.

Build, deploy, and manage containerized applications using Docker, Kubernetes, EKS, and AKS.

Apply IAM, RBAC, MFA, and cloud security best practices for secure infrastructure management.

Monitor systems using CloudWatch, Azure Monitor, Prometheus, Grafana, and observability platforms.

Perform troubleshooting, incident management, reliability engineering, and production support operations.

Implement cloud cost optimization, backup strategies, disaster recovery, and infrastructure scaling solutions.

Support serverless computing, MLOps workflows, AI infrastructure, and intelligent deployment pipelines.

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

$1,750

In INR

₹1,49,999

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 Sessions31 May 2026Saturday & SundayBatch 1
Weekend Online Live SessionsVery SoonSaturday & SundayBatch 2

COMPARISON WITH OTHERS

FeatureOur CourseCOMPETITOR ACOMPETITOR B
Cloud Platforms CoveredAWS & Azure with True Multi-Cloud ExpertiseAWS onlySingle cloud platform focus
Cloud Architecture & FoundationsWell-Architected Framework, CAF, Migration & Hybrid Cloud StrategiesBasic cloud conceptsLimited architecture exposure
DevOps IntegrationCI/CD, GitOps, Terraform, Docker, Kubernetes & AutomationBasic Docker and Jenkins conceptsLimited DevOps ecosystem
Infrastructure as Code (IaC)Terraform, ARM Templates, CloudFormation & Infrastructure AutomationBasic IaC exposureTerraform-focused learning
Containers & KubernetesDocker, Kubernetes, EKS, AKS, Helm & GitOps DeploymentsIntroductory container conceptsBasic Kubernetes coverage
Monitoring & ReliabilityCloudWatch, Azure Monitor, Prometheus, Grafana & Observability ToolsBasic monitoring conceptsTool-specific monitoring only
Security & GovernanceIAM, RBAC, MFA, Cloud Security, Governance & Compliance StandardsBasic security overviewLimited security implementation
Hands-On ProjectsReal-world labs, capstone projects, deployment scenarios & automation tasksFew theoretical projectsLimited practical exposure
Faculty ExpertiseIndustry Experts with Cloud, DevOps & AI Infrastructure ExperienceGeneral industry trainersMixed teaching background
Career & Placement SupportCareer guidance, mock interviews, portfolio support & placement assistanceLimited career supportStandard placement support

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