Course

Introduction to Cloud Computing

Managing your own servers is like running a personal power plant—expensive, complex, and time-consuming. Cloud computing changed everything by providing on-demand computing resources that scale with your needs. This course teaches you cloud fundamentals and how to deploy real data engineering infrastructure to the cloud. You’ll understand the service models that shape how you build applications—from full control with IaaS to turnkey solutions with SaaS—and explore deployment strategies across public, private, and hybrid clouds. Then you’ll get hands-on with AWS, the industry’s leading platform, by deploying a complete Apache Airflow environment using containerized infrastructure. You’ll build custom Docker images, provision cloud resources including S3, RDS, and load balancers, and deploy Airflow to ECS with Fargate for fully managed, scalable orchestration. By the end, you’ll have practical experience with the cloud platforms and deployment patterns that power modern data engineering.

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Part of the Data Engineer (Python) path.

4.8 (359 reviews)

7 learners enrolled in this course.

Intermediate friendly
12 hours
Self paced
6 lessons

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Otávio Silveira

Data Analyst @ Hortifruti

Introduction to Cloud Computing

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Course overview

Cloud computing transformed technology from owning infrastructure to renting it on demand—eliminating the complexity and cost of managing physical servers. This course teaches you cloud fundamentals through hands-on AWS deployment. You’ll start by understanding service models: IaaS for maximum control, PaaS for faster development, and SaaS for turnkey solutions. You’ll explore deployment strategies—public clouds for scalability, private for security, hybrid for flexibility—and compare AWS, Azure, and GCP. Then you’ll get practical by deploying a complete Apache Airflow environment to AWS. You’ll provision cloud resources including S3 buckets and RDS databases, build custom Docker images, and deploy containers to ECS with Fargate. By the end, you’ll have a production-grade orchestration system running in the cloud—scalable, managed, and accessible from anywhere—giving you real experience with the platforms and patterns that power modern data infrastructure.

Key skills

Understanding cloud service models and selecting appropriate levels of infrastructure control
Comparing cloud deployment strategies and major providers for different use cases
Provisioning AWS infrastructure including storage, databases, and networking resources
Deploying containerized applications to AWS using ECS and Fargate
Building production-grade cloud orchestration systems that scale automatically

Course outline

Introduction to Cloud Computing [6 lessons]

Introduction to Cloud Computing 2h

Lesson Objectives

Understand cloud computing fundamentals and modern digital infrastructure
Differentiate between IaaS, PaaS, and SaaS service models
Compare public, private, and hybrid cloud deployment strategies
Identify major cloud providers and their key strengths
Recognize cloud scalability benefits over traditional physical servers

Introduction to Cloud Deployment Models 2h

Lesson Objectives

Understand characteristics of public, private, and hybrid clouds
Identify appropriate cloud deployment models for business needs
Evaluate security and compliance requirements across cloud models
Analyze cost implications of different cloud deployment strategies
Apply cloud bursting and multi-cloud management concepts

Cloud Service Models: IaaS, PaaS, and SaaS 2h

Lesson Objectives

Differentiate IaaS, PaaS, and SaaS service models
Identify which infrastructure layers users versus vendors manage
Match cloud service models to appropriate use cases
Evaluate tradeoffs between control, convenience, and cost
Select optimal cloud models based on project requirements

Cloud Providers: AWS, Azure, GCP 2h

Lesson Objectives

Distinguish between AWS, Azure, and GCP deployment models
Identify core cloud services across major providers
Evaluate pricing models and cost optimization strategies
Match cloud providers to specific use cases
Compare IaaS, PaaS, and SaaS implementations practically

Deploying Airflow to the Cloud with Amazon ECS (Part I) 2h

Lesson Objectives

Set up AWS S3 bucket for pipeline output storage
Create and configure IAM roles for secure ECS-S3 communication
Configure security groups and Application Load Balancer for service access
Deploy PostgreSQL RDS database for Airflow metadata persistence
Test end-to-end DAG execution with local-to-cloud S3 uploads

Deploying Airflow to the Cloud with Amazon ECS (Part II) 2h

Lesson Objectives

Build and push custom Airflow Docker images to ECR
Configure ECS task definitions with environment variables and commands
Deploy Airflow components using ECS Fargate services and tasks
Troubleshoot common Airflow deployment issues on AWS ECS
Understand and optimize AWS costs for cloud-hosted Airflow

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