Course Overview
This comprehensive course provides a deep dive into the core services and architectural patterns of the two dominant public cloud platforms: AWS and Azure. You will move from cloud fundamentals to advanced concepts, learning how to make informed decisions about which platform and services to use for different business needs.
The curriculum is designed around practical, real-world scenarios. You will learn to provision virtual machines, configure virtual networks, manage storage solutions, implement security controls, and automate deployments using Infrastructure as Code (IaC) tools like AWS CloudFormation and Azure Resource Manager (ARM) templates.
By taking a multi-cloud approach, you will develop a versatile skill set that is highly valued in the industry, allowing you to design robust, scalable, and cost-effective solutions on either platform. The course includes numerous hands-on labs and a capstone project to solidify your learning.
Objectives / Expectations
Learning Objectives
- Understand the core concepts of cloud computing (IaaS, PaaS, SaaS) and the shared responsibility model.
- Gain proficiency in core AWS services: EC2, S3, VPC, IAM, Lambda, and RDS.
- Gain proficiency in core Azure services: Virtual Machines, Blob Storage, VNet, Azure AD, Functions, and SQL Database.
- Design and implement secure and highly available cloud network architectures on both platforms.
- Implement identity and access management (IAM) policies to secure cloud resources.
- Automate cloud deployment and management using Infrastructure as Code (IaC).
- Monitor cloud resources and manage costs effectively using native tools (AWS Cost Explorer, Azure Cost Management).
- Compare and contrast AWS and Azure services to choose the right tool for a given task.
Expectations
- Students should have a basic understanding of networking, security, and virtualization concepts.
- Dedicate 7-9 hours per week to complete video lectures, hands-on labs, and readings.
- Create free-tier accounts on AWS and Azure to complete practical exercises (some services may incur minor costs).
- Actively experiment with the console and CLI for both platforms beyond the guided labs.
- Apply learned concepts to the final multi-cloud architecture project.
Course Curriculum
- Introduction to Cloud Computing: IaaS, PaaS, SaaS, FaaS
- Cloud Deployment Models: Public, Private, Hybrid, and Multi-Cloud
- Global Infrastructure: AWS Regions & Availability Zones vs. Azure Regions & Availability Zones
- Core Cloud Characteristics: Elasticity, Scalability, and Agility
- Cloud Economics: CAPEX vs. OPEX, TCO, and Pricing Models
- Setting Up Your Cloud Accounts: AWS Root User & IAM, Azure AD Tenant
- Lab: Creating Billing Alarms and Budgets in AWS and Azure
- AWS IAM Fundamentals: Users, Groups, Roles, and Policies
- Microsoft Entra ID (Azure AD): Users, Groups, and Enterprise Applications
- Principle of Least Privilege and Role-Based Access Control (RBAC)
- Managing Secrets: AWS Secrets Manager vs. Azure Key Vault
- Network Security: Security Groups (AWS) vs. Network Security Groups (Azure)
- Compliance & Governance: AWS Artifact, Azure Compliance, and AWS Config/Azure Policy
- Lab: Securing a Multi-Service Application with IAM Roles and Policies
- AWS EC2: Launching, Configuring, and Managing Virtual Servers
- Azure Virtual Machines: Deployment and Management
- Serverless Compute: AWS Lambda vs. Azure Functions
- Container Orchestration: AWS ECS/EKS vs. Azure ACI/AKS
- Elastic Load Balancing: AWS ELB/ALB vs. Azure Load Balancer/Application Gateway
- Auto-Scaling: AWS Auto Scaling Groups vs. Azure Virtual Machine Scale Sets
- Lab: Deploying a Highly Available Web Application on Both Platforms
- Object Storage: Amazon S3 and Azure Blob Storage
- Block Storage: Amazon EBS and Azure Managed Disks
- File Storage: Amazon EFS and Azure Files
- Data Transfer & Migration: AWS Snow Family vs. Azure Data Box
- Storage Tiers and Lifecycle Policies
- Hybrid Storage: AWS Storage Gateway vs. Azure StorSimple
- Lab: Building a Serverless Data Lake on S3 and ADLS Gen2
- Virtual Networking: Amazon VPC and Azure VNet
- Hybrid Connectivity: AWS VPN/Direct Connect vs. Azure VPN/ExpressRoute
- DNS Management: Amazon Route 53 vs. Azure DNS
- Content Delivery Networks (CDN): Amazon CloudFront vs. Azure CDN
- Network Architecture & Best Practices
- Monitoring & Troubleshooting: AWS VPC Flow Logs vs. Azure NSG Flow Logs
- Lab: Configuring a Hub-Spoke Network Topology with VPC Peering/VNet Peering
- Relational Databases: Amazon RDS (Aurora, PostgreSQL) vs. Azure SQL Database
- NoSQL Databases: Amazon DynamoDB vs. Azure Cosmos DB
- Data Warehousing: Amazon Redshift vs. Azure Synapse Analytics
- Big Data Processing: AWS EMR vs. Azure HDInsight
- Data Streaming: Amazon Kinesis vs. Azure Stream Analytics
- Caching: Amazon ElastiCache (Redis/Memcached) vs. Azure Cache for Redis
- Lab: Building a Serverless Data Processing Pipeline (S3 -> Lambda -> DynamoDB / Blob -> Function -> Cosmos DB)
- Infrastructure as Code (IaC): AWS CloudFormation vs. Azure ARM/Bicep Templates
- Configuration Management: AWS Systems Manager vs. Azure Automation
- CI/CD Pipelines: AWS CodePipeline/CodeBuild vs. Azure DevOps Pipelines
- Container Registries: Amazon ECR vs. Azure Container Registry
- Monitoring & Logging: Amazon CloudWatch vs. Azure Monitor
- Event-Driven Architectures: Amazon EventBridge vs. Azure Event Grid
- Lab: Automating a Full Application Deployment from Code Commit to Production
- The Well-Architected Framework: AWS vs. Microsoft Azure Well-Architected Framework
- Designing for Reliability and High Availability
- Designing for Performance Efficiency
- Designing for Cost Optimization: AWS Cost Explorer vs. Azure Cost Management
- Designing for Operational Excellence
- Disaster Recovery & Backup Strategies: AWS Backup vs. Azure Backup
- Lab: Conducting a Well-Architected Framework Review on a Sample Workload
- Machine Learning & AI: Amazon SageMaker vs. Azure Machine Learning
- Internet of Things (IoT): AWS IoT Core vs. Azure IoT Hub
- Serverless Application Model: AWS Step Functions vs. Azure Durable Functions
- Application Integration: Amazon SQS/SNS vs. Azure Service Bus/Queue Storage
- Desktop Virtualization: Amazon WorkSpaces vs. Azure Virtual Desktop
- Choosing the Right Service for the Right Job
- Lab: Building a Multi-Service AI-Powered Application
- The Cloud Adoption Framework: AWS CAF vs. Microsoft Cloud Adoption Framework
- Migration Strategies: The 6 R's (Rehost, Replatform, Refactor, etc.)
- Migration Tools: AWS Migration Hub & DMS vs. Azure Migrate
- Managing Multi-Cloud Environments and Operations
- Preparing for Cloud Certifications (AWS SAA, Azure AZ-104)
- Trends and Future of Cloud Computing
- Capstone Project: Lift-and-Shift Migration of an On-Premises Application to Both AWS and Azure
Materials & Methodology
Course Materials
- 50+ hours of HD video lectures with live demonstrations on both AWS and Azure consoles.
- Step-by-step lab guides for over 20 hands-on exercises.
- Downloadable IaC templates (CloudFormation & ARM) for quick environment setup.
- Architecture diagrams and comparison charts for AWS vs. Azure services.
- Quizzes and knowledge checks at the end of each module.
- A comprehensive glossary of cloud terms and concepts.
- Access to a private discussion forum for peer-to-peer support and networking.
Methodology
This course uses a practical, compare-and-contrast methodology to build true multi-cloud competency:
- Concept Introduction: Learn a cloud concept (e.g., object storage).
- AWS Deep Dive: See how it is implemented on AWS (e.g., Amazon S3).
- Azure Deep Dive: See how it is implemented on Azure (e.g., Azure Blob Storage).
- Guided Lab: Complete a hands-on lab on both platforms to reinforce the learning.
- Comparison & Best Practices: Discuss the differences, pricing models, and use cases for each platform's service.
- Project Application: Integrate the services into a larger project, choosing the best platform for each component.
Target Audience
This course is designed for:
- IT Professionals (System Administrators, Network Engineers, DevOps) looking to transition to cloud roles.
- Software Developers who want to learn how to build and deploy scalable applications in the cloud.
- Solutions Architects and Technical Managers who need to design cloud-based solutions.
- Students and recent graduates aiming to build a career in cloud computing.
- Technology enthusiasts who want to understand the leading cloud platforms and stay relevant in the industry.
Note: While not mandatory, prior experience with command-line interfaces and basic scripting will be beneficial.
Awards
Upon successful completion of all course requirements, you will receive a Certificate of Proficiency in AWS & Azure Cloud Computing.
To qualify for the certificate, you must:
- Complete all hands-on lab exercises and achieve a passing grade on module quizzes.
- Design and document a multi-cloud architecture for a given business case as a mid-term project.
- Successfully deploy and configure a functional multi-tier web application using both AWS and Azure services for the final capstone project.
This course provides a strong foundation and the practical experience needed to prepare for official vendor certifications such as the AWS Certified Solutions Architect - Associate and Microsoft Azure Fundamentals (AZ-900) or Azure Administrator Associate (AZ-104).
Frequently Asked Questions
Both AWS and Azure offer generous free tiers that allow you to learn and experiment with many core services at no cost for a limited time. The course labs are designed to use free-tier-eligible services where possible. However, to get the full experience, you may choose to use some paid services, which could incur minimal costs (a few dollars). We provide clear cost warnings and instructions on how to clean up resources to avoid unexpected charges.
This course is designed to teach them in parallel. We introduce a concept and then show its implementation on both platforms. This approach helps you understand cloud computing fundamentals without being tied to a single vendor and makes you more versatile in the job market.
No. While some modules on automation (e.g., IaC, serverless functions) involve writing configuration files or simple scripts, the course focuses more on architecture and console-based management. Basic scripting knowledge is helpful but not a strict prerequisite.
Cloud skills are in extremely high demand. By gaining hands-on experience with both major platforms, you demonstrate flexibility and a deep understanding of cloud concepts, making you a strong candidate for roles like Cloud Engineer, Solutions Architect, or DevOps Specialist. The portfolio you build from the labs and projects is key.
We focus on the philosophical and service-oriented differences. AWS is often seen as a vast collection of highly specialized and configurable services, while Azure is praised for its deep integration with the Microsoft software ecosystem and enterprise focus. The course will teach you how to navigate both philosophies effectively.
We cover foundational DevOps practices essential for the cloud, such as Infrastructure as Code (IaC) and basic automation. However, this is not an advanced DevOps course. It is a broad cloud fundamentals course that provides the necessary foundation for you to later specialize in cloud DevOps if you choose.
