Cloud Computing
You can start and finish one of these popular courses in under a day – for free! Check out the list below.. Take the course for free
course overview
Learning a Cloud Computing course helps you understand how modern businesses use the cloud for storage, computing power, and services. You’ll gain skills in platforms like AWS, Azure, and Google Cloud, covering virtualization, networking, security, and deployment. This knowledge boosts career opportunities in IT, web development, and data management while preparing you for industry certifications.
AWS Cloud Practitioner
1: Introduction to Cloud & AWS (3–4 hrs)
2: AWS Core Services (10–12 hrs)
3: Security & Compliance (5 hrs)
4: Billing, Pricing & Support (5 hrs)
5: Monitoring & Well-Architected Framework (5 hrs)
6: Migration & Cloud Adoption (3 hrs)
7: Emerging Technologies & Use Cases (2–3 hrs)
Key exam domains review
Cloud Concepts (26%)
Security & Compliance (25%)
Cloud Technology & Services (33%)
Billing, Pricing, and Support (16%)
Practice questions & mock exams
Test-taking strategies
✅ Learning Outcomes:
By the end of the course, learners will be able to:
Understand AWS core services and architecture
Explain pricing, billing, and support models
Apply AWS best practices for security and compliance
Demonstrate cloud fundamentals for AWS certification
AWS Cloud Expert
AWS Cloud Expert Training – (Beginner to Expert)
1: Cloud & AWS Fundamentals Hands-on: Launch first EC2 instance, explore AWS Console
2: Compute Services Hands-on: Launch EC2, configure ALB, create Lambda function
3: Storage Services Hands-on: Create S3 bucket, implement lifecycle, mount EFS
4: Networking & Content Delivery Hands-on: Build custom VPC with public/private
subnets, deploy website via CloudFront
5: Databases & Analytics (7 hrs) Hands-on: Deploy RDS, create DynamoDB table, run
queries with Athena
6: Security, Identity & Compliance Hands-on: Configure IAM roles & policies, enable GuardDuty
7: Monitoring, Logging & Automation Hands-on: Create CloudWatch alarms, CloudTrail audit, Config rules
8: Application Integration & Messaging Hands-on: Build workflow using Lambda + SQS + SNS
9: Advanced Cloud Architecture & Cost Management Hands-on: Design HA architecture with cost-optimized services
10: Projects Learning Outcomes By the end of this 60-hour program, learners will be
able to: Confidently navigate and use core AWS services from compute, storage, networking, and databases Design, secure, and optimize cloud architectures following AWS best practices
Implement real-world AWS solutions without requiring DevOps automation
Prepare for advanced certifications like AWS Solutions Architect – Associate/Professional
DevOps Expert
DevOps Training – Beginner to Expert
1: DevOps Fundamentals Hands-on: Set up a collaborative GitHub repo, workflow basics
2: Linux, Git & Version Control Hands-on: Manage branches, resolve conflicts, set up
GitHub Actions basic workflow
3: Continuous Integration Hands-on: Create Jenkins pipeline for Java app, run automated builds
4 : Containers & Container Orchestration Hands-on: Containerize an app with Docker, deploy on Kubernetes
5: Infrastructure as Code Hands-on: Use Terraform to provision AWS infrastructure, configure with Ansible
6 : Continuous Deployment & Release Management Hands-on: Implement blue/green deployment with Kubernetes + ArgoCD
7: Monitoring, Logging & Observability Hands-on: Monitor a containerized app with Prometheus & Grafana
8 : Security & DevSecOps Hands-on: Scan container images & integrate security
into CI/CD pipeline
9: Cloud & DevOps Hands-on: Deploy CI/CD pipeline on AWS CodePipeline
10 : Projects Learning Outcomes: By the end of this -hour program, learners will be able to:
Understand and implement the DevOps lifecycle end-to-end
Build and manage CI/CD pipelines with Jenkins/GitHub Actions/GitLab CI
Containerize applications with Docker and orchestrate with Kubernetes
Automate infrastructure with Terraform and Ansible
Apply monitoring, logging, and DevSecOps practices
Design and deliver production-grade DevOps solutions
Microsoft Azure-
Microsoft Azure Training – Zero to Expert
1: Introduction to Cloud & Azure Fundamentals Hands-on: Create free Azure account, deploy first VM
2: Core Azure Compute Services Hands-on: Deploy a web app using App Service &
Functions
3: Storage & Data Management Hands-on: Create Blob storage & lifecycle policy,
mount File Share
4: Networking & Content Delivery Hands-on: Design secure multi-tier VNet with NSG
rules
5: Databases & Data Analytics Hands-on: Deploy SQL DB, connect with App Service,
query with Synapse
6: Security, Identity & Governance Hands-on: Configure RBAC, secure secrets in Key Vault
7: Monitoring, Logging & Automation Hands-on: Create alerts & dashboard, automate task with Logic Apps
8: Migration & Hybrid Cloud Hands-on: Assess & migrate on-prem workload using
Azure Migrate
9: Advanced & Specialized Azure Services Hands-on: Deploy Cognitive Service for image recognition
10: Cost Management & Best Practices Hands-on: Estimate cost of architecture & apply budget alerts
11: Projects Deliverables:
End-to-end architecture diagram
Hands-on implementation
Security & cost optimization plan
Final presentation/demo
✅ Learning Outcomes: By the end of this 60-hour program, learners will be able to:
Deploy and manage compute, storage, networking, and database solutions in Azure
Secure and govern Azure environments with RBAC, Key Vault, and policies
Monitor, automate, and optimize cloud workloads
Design enterprise-grade architectures on Azure following best practices
GCP Training – Zero to Expert
1: Introduction to Cloud & GCP Hands-on: Create a free-tier GCP account, navigate
console, run Cloud Shell commands
2: Compute Services Hands-on: Launch VM, deploy a simple app on App Engine, create Cloud Function
3: Storage Services Hands-on: Create buckets, set lifecycle rules, create Cloud SQL instance
4: Networking & Content Delivery Hands-on: Build VPC with private/public subnets,
deploy web app behind LB
5: Security & Identity Hands-on: Create IAM roles, assign service accounts, enable security logging
6: Data Analytics & Big Data Services Hands-on: Load data into BigQuery, run queries, stream data via Pub/Sub
7: Machine Learning & AI Services Hands-on: Build ML model with Vertex AI, use Vision API on sample images
8: Monitoring, Logging & Management Hands-on: Create dashboards, alerts, review logs for resources
9: Advanced Architecture & Best Practices Hands-on: Deploy multi-zone app with autoscaling and HA
10: Capstone Project Learners implement an end-to-end GCP solution, for example:
Scalable web application: GCE + Cloud SQL + Load Balancer + Cloud Storage
Serverless app: Cloud Functions + Firestore + Pub/Sub
Data analytics pipeline: Pub/Sub + Dataflow + BigQuery + Looker Studio
AI/ML project: Vertex AI model deployment with real dataset
Deliverables:
Architecture diagram & design documentation
Implementation of services
Cost analysis & security considerations
✅ Learning Outcomes:
By the end of this 60-hour program, learners will be able to:
Understand and use core GCP services effectively
Design secure, highly available, and scalable cloud architectures
Implement serverless and containerized applications on GCP
Perform data analytics and ML workflows on GCP
Prepare for GCP Associate Cloud Engineer and Professional certifications
Topics we will cover
| Course Name | Duration | Sessions |
| AWS Cloud Practitioner | 2 week | 8 |
| AWS Cloud Expert | 3 month | 60 |
| DevOps Expert | 3 month | 60 |
| Azure | 3 month | 60 |
| GCP | 3 month | 60 |