☁️ AWS Certified Data Engineer - Associate (DEA-C01) - Exam-Prep

For aspiring AWS data engineers: build, secure, and operate analytics pipelines on AWS and pass the DEA-C01 exam with confidence. The course is organized into 9 modules, ending with a final exam (pass mark 70%). It is independent, free exam-preparation training — not an official or accredited review course.

What you'll learn

• Exam Overview, DEA-C01 Domains & AWS Data Engineering Fundamentals
• Domain 1: Data Ingestion — Batch & Streaming with Kinesis, MSK, Firehose & DMS
• Data Transformation & Pipeline Programming: Glue ETL, Spark, EMR, and Lambda
• Domain 2: Data Store Management — S3, Redshift, DynamoDB, RDS/Aurora & Lake Formation
• Domain 2: Data Cataloging, Modeling, Life Cycle & Data Quality
• Orchestration, Automation & CI/CD: EventBridge, MWAA & Step Functions
• Domain 3: Monitoring, Logging, Cost & Performance Optimization
• Domain 4: Data Security & Governance — IAM, KMS Encryption, Lake Formation, Auditing & Compliance
• Exam Strategy, Scenario Practice & Full Mock Exam

Learning objectives

• Design and implement batch and streaming data ingestion using Kinesis, MSK, AWS Glue, DMS, and Amazon Data Firehose.
• Transform and process data with Glue ETL, Spark, EMR, Lambda, and Step Functions while applying sound programming concepts.
• Select and configure the right data stores (S3, Redshift, DynamoDB, RDS/Aurora, Lake Formation) for cost, performance, and access patterns.
• Manage data life cycles, cataloging, partitioning, schema evolution, and data quality across the lake and warehouse.
• Orchestrate, automate, and monitor pipelines using EventBridge, MWAA (Airflow), CloudWatch, and CI/CD.
• Apply data security and governance: IAM, encryption (KMS), Lake Formation permissions, masking, and audit logging.
• Optimize cost and performance of analytics workloads and troubleshoot common pipeline failures.
• Apply exam-taking strategies and practice scenario-based questions mapped to all four official DEA-C01 domains.