The 4 Best AWS Data Engineering Courses and Online Training for 2021

The Best AWS Data Engineering Courses

Solutions Review editors compiled this list of the best AWS data engineering courses and online training to use when growing your skills.

SR FindsThe first major cloud computing provider, Amazon Web Services (AWS) combines over 100 distinct services that cover a wide breadth of cloud capabilities. AWS focuses heavily on infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) offerings, with an emphasis on providing virtual infrastructures and development tools, including storage, computing, database, mobility, and management services. Data engineering is the process of designing and building pipelines that transport and transform data into a usable state for data workers to utilize.

With this in mind, we’ve compiled this list of the best AWS data engineering courses and online training to consider if you’re looking to grow your big data skills for work or play. This is not an exhaustive list, but one that features the best AWS data engineering courses and training from trusted online platforms. This list of the best AWS data engineering courses below includes links to the modules and our take on each.

The Best AWS Data Engineering Courses

TITLE: Cloud Data Engineering

OUR TAKE: By the end of this Duke University course, you will be able to develop Data Engineering applications and use software development best practices to create data engineering applications.

Platform: Coursera

Description: In this course, you will learn how to apply data engineering to real-world projects using the cloud computing concepts introduced in the first two courses of this specialization.  This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering.

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TITLE: Streaming Data with AWS Kinesis and Lambda

OUR TAKE: By the end of this training you’ll know how to create live ElasticSearch dashboards with AWS QuickSight and CloudWatch. The module features four different chapters, 22 videos, and 56 exercises.

Platform: DataCamp

Description: In this course, you’ll learn how to leverage powerful technologies by helping a fictional data engineer named Cody. Using Amazon Kinesis and Firehose, you’ll learn how to ingest data from millions of sources before using Kinesis Analytics to analyze data as it moves through the stream. You’ll also spin up serverless functions in AWS Lambda that will conditionally trigger actions based on the data received.

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TITLE: Developing Stream Processing Applications with AWS Kinesis

OUR TAKE: In this intermediate-level AWS training Pluralsight, you will learn how to build modern stream processing applications using AWS Kinesis and stream processing services. It should take roughly 4 hours to complete.

Platform: Pluralsight

Description: First, you’ll discover how it works, how to scale it up and down, and how to write applications using it. Next, you’ll learn how to use a variety of tools to work with it, such as Kinesis Client Library, Kinesis Connector Library, Apache Flink, and AWS Lambda.

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TITLE: Processing Data on AWS

OUR TAKE: This course will teach you the fundamentals of data processing with AWS. This training is designed for an intermediate audience and features nearly 2 hours of content.

Platform: Pluralsight

Description: First, you’ll explore data processing with Lambda and Glue. Next, you’ll discover the basics of the Hadoop ecosystem and how to use it with AWS EMR. Finally, you’ll learn how to automate data processing using AWS Data Pipeline. When you’re finished with this course, you’ll have the skills and knowledge of the AWS services needed to process large amounts of data.

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