Cloud Computing & DevOps
Overview:
In today’s fast-paced digital world, businesses are moving rapidly to the cloud — and DevOps has become the backbone of modern software delivery. This advanced training program is designed to make you industry-ready in both Cloud Infrastructure Management and DevOps Automation practices. You’ll gain hands-on expertise in AWS, Azure, Google Cloud, CI/CD pipelines, Docker, Kubernetes, and Infrastructure as Code (IaC), preparing you for high-demand cloud and DevOps roles in global IT enterprises.
Training Duration & Format
Total Duration: 180–200 Hours (Approx. 6 Months)
Mode: Classroom / Online / Hybrid
Learning Format: Instructor-led sessions, lab assignments, live cloud deployment projects
Training Highlights:
* Learn from industry professionals with years of DevOps & Cloud experience
* Step-by-step practical training with live projects
* Cloud setup on AWS & Azure from scratch
* CI/CD automation using Jenkins, Git, Docker, Kubernetes
* Infrastructure management with Terraform & Ansible
*Real-world projects on deployment pipelines and scaling systems
* Interview preparation & certification guidance (AWS / Azure / GCP)
Course Structure
Module 1: Introduction to Cloud Computing
Understanding Cloud Computing fundamentals Cloud service models – IaaS, PaaS, SaaS Deployment models – Public, Private, Hybrid, Multi-cloud Benefits, architecture, and scalability concepts Overview of major providers: AWS, Azure, Google Cloud Setting up free-tier cloud accounts
Module 2: Amazon Web Services (AWS)
AWS account setup, IAM users, and access management EC2 Instances: creation, configuration, and security groups S3 storage, lifecycle management, versioning RDS databases and DynamoDB basics VPC (Virtual Private Cloud) – subnets, routing, NAT, Internet Gateways Elastic Load Balancer (ELB) and Auto Scaling groups AWS CloudWatch, CloudTrail, and SNS notifications Deployment of a 3-tier web app on AWS
Module 3: Microsoft Azure Fundamentals
Introduction to Azure Portal and services Azure Virtual Machines and storage Azure Networking: VNet, Subnet, Load Balancer Azure App Services and Azure SQL Database Role-based access control (RBAC) and monitoring tools Deploying sample applications on Azure Cloud Probability theory and hypothesis testing Correlation, covariance, regression concepts Real-world application of inferential statistics in analytics
Module 4: Google Cloud Platform (GCP) Overview
Introduction to GCP and its console Compute Engine, Cloud Storage, and Cloud Functions Google Kubernetes Engine (GKE) basics Identity & Access Management (IAM) Real-world deployment exercise Aggregations, subqueries, and nested queries Integrating SQL with Python for analytics Basic introduction to NoSQL (MongoDB overview)
Module 5: Linux Essentials for DevOps
Linux architecture and commands File system navigation, permissions, process management Shell scripting for automation Managing services and packages Secure Shell (SSH) and networking basics Designing interactive dashboards and KPI reports Visual storytelling for decision-making Connecting live data sources and automating reports
Module 6: Version Control with Git & GitHub
Git fundamentals: repositories, commits, branches, merges Remote collaboration using GitHub Git workflows: feature branching, pull requests, tagging Integrating Git with CI/CD tools
Certification
After successful completion of the course and project evaluation, you will be awarded the Certified Cloud Computing & DevOps Professional credential — recognized by top IT employers.