Overview
In this 8 hr course, dive into advanced AWS data engineering through 15 hands-on labs that simulate real-world challenges. Learn to orchestrate workflows, manage data lakes, and deploy robust pipelines using AWS services like Airflow, Redshift, and Glue.
What I will be able to do after this course
- Understand how to design and implement ETL workflows using AWS Glue and Step Functions.
- Master the use of Airflow and Redshift to build efficient data processing workflows.
- Gain expertise in real-time data streaming using AWS Lambda, Kinesis, and ECS.
- Learn best practices in code deployment and CI/CD using GitHub Actions.
- Build practical experience through hands-on labs covering AWS data engineering techniques.
Course Instructor(s)
Siddharth Raghunath is an experienced data engineer with years of practical expertise in cloud computing and AWS services. He has a proven track record of teaching technical concepts through engaging and hands-on content. Siddharth focuses on providing real-world applicable knowledge and ensures that complex topics are taught in an approachable manner.
Who is it for?
This course is ideal for aspiring data engineers and cloud professionals who want to expand their skillset in AWS data engineering. Participants should have a foundational understanding of Python and AWS or another major cloud platform. If you are seeking to deepen your expertise in scalable data solutions on AWS and build a robust portfolio, this course is for you.
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