About this Course
Imagine being the engineer the one who turns raw data into actual business decisions that power dashboards, recommendations, and real-time analytics at scale. The AWS Certified Data Engineer Associate prep Specialization is meant to guide you on that journey, step-by-step, from data foundations to production-ready cloud pipelines. You begin by mastering the foundations—data types, data warehouses and data lakes, data modeling, schema evolution, SQL joins, and performance challenges like data skew. From this foundation, you will progress to storage and databases on AWS, gaining knowledge on how S3, EBS, DynamoDB, RDS,MemoryDB, and Neptune are used with real applications, and then move into compute and serverless tools like Graviton EC2, AWS Lambda & SAM, as well as ECS, ESK, and DMS. In the next section, the focus shifts to building scalable analytics pipelines with Redshift and Redshift ML, Apache Spark, AWS Glue, Athena, EMR, Kinesis, Firehose, MSK, and OpenSearch – just like how it is used by teams working with streaming and large-scale data in production. At the end, you bring it all together with networking, security, monitoring, and cost management via VPC, CloudFront, Macie, CloudWatch, AWS CLI, and SageMaker Data Wrangler. Designed for aspiring data engineers and cloud professionals, this AWS Data Engineer Course stands out for its clear progression and real-world relevance, preparing you for high-demand data engineering roles on AWS
What You'll Learn
- Master data concepts including data types, modeling, and SQL joins
- Learn AWS storage and compute services like S3, DynamoDB, EC2, and Lambda
- Design scalable analytics pipelines using Redshift, Apache Spark, and Kinesis
- Implement monitoring, security, and cost control with AWS tools
Prerequisites
- Basic computer and internet skills
- Ability to follow course instructions in English and complete short exercises
Instructors
LearnKartS