AWS Data Engineer Course

AWS Data Engineer Course

Learn AWS Data Engineering from beginner to advanced. Master S3, Glue, Redshift, EMR, Kinesis, and more to build scalable ETL pipelines, real-time data streams, and data lakes. Includes real-world projects.

  • 11 Phases
  • 26 Lessons
  • 6 Hrs
  • Beginner Advanced
Category Cloud computing
AWS Data Engineer Course
Learning Path 26 Lessons 6 Hrs

Start Phase
  • What is Data Engineering? 2:08
  • AWS Data Analytics Services Overview 10:00

Start Phase
  • Amazon S3 Basics 27:00
  • Amazon DynamoDB Overview 3:40
  • Amazon Redshift Basics 45:30

Start Phase
  • Amazon Kinesis Basics 2:00
  • AWS Glue Crawlers 22:20
  • Database Migration Service (DMS) 21:45

Start Phase
  • ETL with AWS Glue 4:00
  • Apache Spark on AWS EMR 22:00
  • AWS Lambda for ETL 9:00

Start Phase
  • AWS Lake Formation 5:30
  • Amazon Athena Basics 24:33

Start Phase
  • Kinesis Data Analytics 4:27
  • MSK (Managed Kafka) Basics 12

Start Phase
  • Amazon Redshift Table Design: DISTKEY & SORTKEY 7
  • AWS QuickSight for BI – Dashboard Hands-On 10

Start Phase
  • AWS Step Functions Basics – Hands-On Workflow Orchestration 13
  • Airflow on AWS (MWAA) – Environment Setup & DAG Deployment 24

Start Phase
  • AWS IAM Basics for Data Engineers 12
  • IAM for Data Workflows (S3 / Glue / Athena / Redshift) 16
  • AWS KMS Encryption 14:15

Start Phase
  • Data Mesh on AWS 12.5
  • Streaming Analytics Dashboard 13.1

Start Phase
  • Project 1: Data Lake on AWS 12.5
  • Project 2: Real-time Data Pipeline 14.4

Start your AWS Data Engineer Course journey

Learn at your own pace. Total estimated time 6 hours

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