Cloud Computing

1. Program Overview

The Cloud Computing training programe provides foundational and practical knowledge of modern cloud platforms, services, architecture, and deployment models.

It prepares learners for careers in cloud operations, cloud administration, DevOps fundamentals, and cloud application support.

This program aligns with industry certifications such as:

• AWS Cloud Practitioner
• Microsoft Azure Fundamentals (AZ-900)
• Google Cloud Digital Leader

2. Program Duration

• Total Duration: 3–6 Months
• Learning Hours: 120–180 Hours
• Delivery: Classroom / Online / Hybrid
• Components: Lectures + Labs + Projects + Exams

3. Target Audience

• IT students and beginners
• System administrators
• Network administrators
• Developers migrating to cloud environments
• Anyone interested in cloud careers

4. Learning Outcomes

By the end of the program, learners will be able to:

✔ Understand cloud computing fundamentals and architectures

✔ Use major cloud platforms (AWS / Azure / GCP)

✔ Deploy and manage virtual machines and storage

✔ Build and deploy cloud-native applications

✔ Configure networking in the cloud

✔ Understand security, compliance, and IAM

✔ Use DevOps tools (Containers, CI/CD basics)

✔ Build an end-to-end cloud project

5. Course Structure & Modules

Module 1: Introduction to Cloud Computing

Topics:

• What is cloud computing?
• Cloud service models: IaaS, PaaS, SaaS
• Cloud deployment models: Public, Private, Hybrid
• Cloud advantages & use cases (scalability, elasticity)
• Virtualization vs cloud

Lab:

• Create an AWS/Azure free-tier account
• Explore cloud dashboards

Module 2: Virtualization & Compute Services

Topics:

• Hypervisors & virtual machines
• Compute instances (AWS EC2 / Azure VM / GCP Compute Engine)
• Instance types, pricing, scaling
• Load balancers & auto-scaling

Lab:

• Launch a virtual machine
• Configure a load balancer
• Install a web server on a cloud VM

Module 3: Cloud Storage Services

Topics:

• Object storage (S3, Azure Blob, Google Cloud Storage)
• Block & file storage
• Storage classes, lifecycle rules
• Backup & disaster recovery

Lab:

• Upload files to object storage
• Configure cloud storage lifecycle policies

Module 4: Cloud Networking & Security

Topics:

• Virtual Private Cloud (VPC / VNets)
• Subnets, routing tables, gateways
• Firewalls & security groups
• Identity & Access Management (IAM)
• Network security basics

Lab:

• Configure a secure VPC
• Create IAM users, roles & policies

Module 5: Databases in the Cloud

Topics:

• Cloud database types (SQL/NoSQL)
• Managed databases (RDS, Cloud SQL, Cosmos DB)
• Data migration basics
• High availability & replication

Lab:

• Launch a cloud database
• Connect database to a cloud application

Module 6: Cloud Application Deployment

Topics:

• Deploying web apps & APIs
• Serverless computing (AWS Lambda, Azure Functions)
• Event-driven architecture
• Cloud monitoring tools

Lab:

• Deploy a serverless function
• Use cloud monitoring dashboards

Module 7: Containers & DevOps Essentials

Topics:

• Introduction to containers
• Docker basics
• Kubernetes basics
• CI/CD pipelines
• IaC fundamentals (Terraform overview)

Lab:

• Build a Docker container
• Deploy container to cloud service (ECS, AKS, GKE)

Module 8: Cloud Security, Governance & Compliance

Topics:

• Shared responsibility model
• Cloud compliance frameworks
• Encryption (at rest & in transit)
• Cloud cost management
• Cloud policies & governance

Lab:

• Enable encryption for cloud storage
• Configure cost alerts

Module 9: IoT & Big Data in the Cloud (Introductory)

Topics:

• IoT cloud integration
• Big data & analytics tools
• Stream processing (Kinesis, DataFlow)
• Machine learning intro (SageMaker, Azure ML)

Lab:

• Simple IoT data ingestion into cloud storage

Module 10: Cloud Project Development

Topics:

• Requirements gathering
• Architecture design
• Deployment strategies
• Testing & documentation

Lab:

• Build a complete cloud system (compute + storage + security + monitoring)

6. Assessments

Continuous Assessments

• Quizzes for every module
• Cloud lab assignments
• Practical exercises

Midterm Assessment

• MCQ test
• Lab tasks (VM deployment + networking + storage)

Final Project (Capstone)

Learners choose and build one of the following:

Example Cloud Projects:

• Host a scalable web application
• Serverless function-based microservice
• Cloud IoT sensor processing system
• Multi-tier application with load balancer + database
• Automated container deployment pipeline

Evaluation Criteria:

• Cloud architecture
• Security configuration
• Deployment quality
• Cost optimization
• Documentation & presentation

Final Examination

• 50–70 MCQs
• Hands-on cloud tasks

7. Certification Requirements

Learners must:

✔ Complete all modules & labs

✔ Score at least 60% in exams

✔ Submit and present final project

✔ Demonstrate cloud administration proficiency

8. Career Opportunities

Graduates can pursue roles such as:

• Cloud Support Associate
• Cloud Administrator
• Cloud Technician
• DevOps Assistant
• Junior Cloud Engineer
• Systems & Cloud Operations Technician