Packt
1 week to complete at 10 hours a week
This course provides hands-on experience with essential AWS data engineering tools and techniques. You'll work on real-world projects using services like Redshift, DynamoDB, Athena, Glue, Kinesis, and Step Functions to build data pipelines, automate workflows, and process data at scale.
The course is designed for learners with foundational knowledge of data engineering concepts and basic AWS services. You should be comfortable with programming, particularly in Python, as well as have some familiarity with data processing concepts. Understanding of cloud computing and AWS basics would be helpful, but the course also covers the essential tools and services needed for successful completion.
The course covers a wide range of data engineering topics, including batch and real-time data processing, building data lakes and lakehouses, automating workflows, and implementing event-driven architectures. You'll gain hands-on experience with AWS services like Airflow, Redshift, DynamoDB, Glue, Kinesis, Step Functions, and more to design, build, and manage complex data pipelines.
Packt is an established global technical learning content provider, founded in Birmingham, UK, with over twenty years of experience delivering premium, rich content from groundbreaking authors on a wide range of emerging and popular technologies. This course is designed to provide practical, hands-on knowledge to help you succeed in the field of AWS data engineering.
After completing this course, you will have the skills to tackle complex data engineering tasks and deploy cloud-based solutions confidently. You'll be able to design, build, and manage scalable data pipelines, automate workflows, and process data at scale using a variety of AWS services. This course will prepare you for a career as an AWS data engineer or cloud data engineer.
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