Cloud Computing (AWS/Azure/GCP)
Become a job-ready Cloud Engineer with hands-on skills across AWS, Azure, and Google Cloud. Master cloud networking, security, Terraform, Docker, and Kubernetes, and build real, portfolio-worthy multi-cloud projects from provisioning to deployment. Start free, go job-ready, and launch your career in the cloud.
In short: This Cloud Computing (AWS/Azure/GCP) program is a 60–65 hour, fully online, job-ready course. You start with 15 hours of free foundations (cloud fundamentals, Linux, networking, CLI, and Git) and continue into a 45–50 hour paid program covering AWS, Azure, and Google Cloud core services, cloud networking and security, identity and access management, Terraform, Docker and Kubernetes, cloud databases, and cost optimization — finishing with a deployed multi-cloud capstone project, a portfolio, and full interview prep.
The Cloud Computing (AWS/Azure/GCP) course is designed to help learners master the complete cloud workflow — from core services to secure, automated, production-grade deployments across the three major providers — and become immediately employable as Cloud Engineers and Cloud Architects.
This course covers cloud computing fundamentals, Linux and networking essentials, AWS core services, Microsoft Azure core services, Google Cloud Platform core services, cloud networking and security, identity and access management and governance, Infrastructure as Code with Terraform, containers and Kubernetes, cloud databases and storage, and monitoring, cost optimization, and deployment. Learners build real, portfolio-worthy multi-cloud projects at every stage using hands-on, project-based learning.
By completing this training, participants will be well-prepared for Cloud Engineer, Cloud Architect, and DevOps/Cloud Engineer roles, with a polished portfolio, a strong resume, and interview readiness.
Course Highlights
- End-to-end multi-cloud coverage across AWS, Azure, and GCP
- Hands-on labs deploying real services on all three cloud providers
- Infrastructure as Code with Terraform for repeatable provisioning
- Containers and orchestration with Docker and Kubernetes
- Cloud networking, security, IAM, and cost optimization
- Job-readiness: portfolio, resume, and interview prep
Learning Outcomes
- Design and deploy compute, storage, and networking on AWS, Azure, and GCP
- Secure cloud workloads with networking, IAM, and governance best practices
- Provision infrastructure automatically with Terraform
- Build and orchestrate containers with Docker and Kubernetes
- Choose and manage cloud databases and storage solutions
- Monitor, optimize cost, and deploy production-grade cloud systems
Job Opportunities
- Cloud Engineer
- Cloud Architect
- Cloud Solutions Architect
- DevOps / Cloud Engineer
- Multi-Cloud Engineer
- Cloud Consultant
What You'll Build (Portfolio Projects)
- A highly available web application deployed on AWS
- An Azure virtual network with identity and access controls
- A Terraform-provisioned, reproducible cloud infrastructure
- A containerized app deployed to Kubernetes on the cloud
- A deployed end-to-end multi-cloud capstone project
Tools & Skills Covered
- AWS, Microsoft Azure, Google Cloud Platform (GCP)
- Terraform, Docker, Kubernetes
- Linux, Git, and GitHub
Material Includes
- Class recordings
- Lab guides & project starter code
- Certificate
Who Can Join
- IT Graduates
- Aspiring Cloud Engineers
- Career Switchers
Related Courses
Free Foundation — 15 Hours
Start learning for free. Build your core cloud, Linux, networking, and version-control foundations before advancing to the job-ready multi-cloud program.
Estimated Time: 5 Hours
Learning Objectives:- Understand core cloud concepts and why the cloud powers modern IT careers
- Compare AWS, Azure, and GCP and their service models confidently
- Cloud service models (IaaS, PaaS, SaaS) and deployment models
- Regions, availability zones, and the shared responsibility model
- Pricing basics, free tiers, and the three major cloud providers
- Create free-tier accounts on AWS, Azure, and GCP and explore their consoles
Estimated Time: 4 Hours
Learning Objectives:- Operate Linux servers and the command line with confidence
- Understand the networking fundamentals every cloud engineer needs
- Linux file system, permissions, and package management
- Shell commands, SSH, and remote server access
- IP addressing, subnets, DNS, ports, and firewalls
- Connect to a cloud Linux VM over SSH and run essential admin commands
Estimated Time: 2 Hours
Learning Objectives:- Track infrastructure code and configs with Git
- Collaborate and showcase your cloud work on GitHub
- Repositories, commits, and branches
- Merging, pull requests, and conflict resolution
- Building a professional cloud/DevOps GitHub profile
- Push your first infrastructure scripts and projects to GitHub
Estimated Time: 4 Hours
Learning Objectives:- Map the core building blocks common to every cloud provider
- Launch your first compute, storage, and network resources
- Virtual machines, containers, and serverless compute
- Object, block, and file storage concepts
- Virtual networks, subnets, and load balancing basics
- Deploy a virtual machine and object storage bucket in the cloud
Paid Job-Ready Program — 45–50 Hours
Go from foundations to fully employable. Master AWS, Azure, and GCP core services, cloud security, Terraform, Kubernetes, and multi-cloud deployment — everything you need to land your first cloud job.
Estimated Time: 6 Hours
Learning Objectives:- Deploy and manage core AWS compute, storage, and networking services
- Architect a highly available application on AWS
- EC2, EBS, S3, and Elastic Load Balancing
- VPC, subnets, security groups, and Route 53
- Auto Scaling, Lambda, and AWS management tools
- Deploy a highly available web application on AWS with load balancing
Estimated Time: 5 Hours
Learning Objectives:- Deploy and manage core Microsoft Azure services
- Translate cloud concepts across providers with confidence
- Azure Virtual Machines, App Service, and Functions
- Azure Blob Storage and managed disks
- Virtual Networks, resource groups, and Azure Portal/CLI
- Deploy an app and virtual network on Microsoft Azure
Estimated Time: 5 Hours
Learning Objectives:- Deploy and manage core Google Cloud Platform services
- Compare GCP services with their AWS and Azure equivalents
- Compute Engine, App Engine, and Cloud Functions
- Cloud Storage and persistent disks
- VPC networking, projects, and the gcloud CLI
- Deploy a workload and storage bucket on Google Cloud Platform
Estimated Time: 5 Hours
Learning Objectives:- Design secure, well-connected cloud networks
- Protect workloads with layered cloud security controls
- VPCs, subnets, peering, and hybrid connectivity (VPN)
- Firewalls, security groups, and network ACLs
- Encryption, key management, and security best practices
- Build a secure, segmented cloud network with firewall rules
Estimated Time: 4 Hours
Learning Objectives:- Control access with least-privilege identity management
- Apply governance and compliance across cloud accounts
- IAM users, roles, groups, and policies across AWS, Azure, and GCP
- Multi-factor authentication and federated identity
- Organizations, billing controls, tagging, and governance
- Configure least-privilege IAM roles and policies for a project
Estimated Time: 5 Hours
Learning Objectives:- Provision cloud infrastructure automatically and repeatably
- Manage multi-cloud resources as version-controlled code
- Terraform providers, resources, variables, and state
- Modules, plan/apply workflow, and remote state
- Provisioning across AWS, Azure, and GCP with one tool
- Provision a reproducible cloud environment entirely with Terraform
Estimated Time: 6 Hours
Learning Objectives:- Package and run applications with Docker containers
- Orchestrate containers at scale with Kubernetes
- Docker images, containers, registries, and Dockerfiles
- Kubernetes pods, deployments, services, and scaling
- Managed Kubernetes (EKS, AKS, GKE) fundamentals
- Containerize an app and deploy it to a managed Kubernetes cluster
Estimated Time: 4 Hours
Learning Objectives:- Select the right managed database for each workload
- Design durable, scalable cloud storage solutions
- Managed relational databases (RDS, Azure SQL, Cloud SQL)
- NoSQL options (DynamoDB, Cosmos DB, Firestore)
- Storage tiers, backups, and data lifecycle management
- Provision a managed database and connect an application to it
Estimated Time: 4 Hours
Learning Objectives:- Monitor cloud systems and respond to issues proactively
- Optimize cost and automate reliable deployments
- Monitoring, logging, and alerting (CloudWatch, Azure Monitor, Cloud Monitoring)
- Cost management, budgets, and right-sizing resources
- CI/CD pipelines and automated cloud deployment
- Set up monitoring, alerts, and a cost budget for a live workload
Estimated Time: 4 Hours
Learning Objectives:- Ship a complete, portfolio-ready multi-cloud project
- Prepare for the cloud engineering job search
- End-to-end multi-cloud project planning and build
- Portfolio, GitHub, and resume optimization
- Cloud interview, scenario, and certification prep
- Build and deploy an end-to-end multi-cloud capstone project
- Mock interviews and resume review