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Cloud Data Engineering with AWS/Azure/GCP

Cloud Data Engineering with AWS/Azure/GCP

beginner4 levels14 stages42 lessons

This is the path structure only. Once you sign up, MICHi builds your own version, measures real mastery through review gateways and spaced repetition, and ends with a verifiable certificate.

Level 1 — Foundational Principles of Cloud Data Engineering

  1. 1.Introduction to Cloud Computing and Data Engineering3 lessons
  2. 2.Relational Databases in the Cloud (AWS RDS, Azure SQL, GCP Cloud SQL)3 lessons
  3. 3.Project: Setting Up a Basic Cloud Data Store3 lessons

Level 2 — Building Core Data Pipelines and Storage

  1. 1.Cloud Object Storage Fundamentals (AWS S3, Azure Blob, GCP Cloud Storage)3 lessons
  2. 2.Data Ingestion and Transformation Basics (AWS Glue, Azure Data Factory, GCP Dataflow)3 lessons
  3. 3.NoSQL Databases in the Cloud (AWS DynamoDB, Azure Cosmos DB, GCP Firestore)3 lessons
  4. 4.Project: Building a Simple Data Lake and ETL Pipeline3 lessons

Level 3 — Advanced Data Processing and Analytics in the Cloud

  1. 1.Big Data Warehousing (AWS Redshift, Azure Synapse Analytics, GCP BigQuery)3 lessons
  2. 2.Stream Processing (AWS Kinesis, Azure Event Hubs/Stream Analytics, GCP Pub/Sub/Dataflow)3 lessons
  3. 3.Orchestration and Workflow Management (AWS Step Functions, Azure Data Factory Pipelines, GCP Cloud Composer)3 lessons
  4. 4.Project: Real-time Analytics Dashboard POC3 lessons

Level 4 — Operationalizing and Optimizing Cloud Data Solutions

  1. 1.Data Governance, Security, and Compliance in the Cloud3 lessons
  2. 2.Monitoring, Troubleshooting, and Cost Optimization for Cloud Data3 lessons
  3. 3.Professional Certification Preparation and Mock Exam3 lessons

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