[NEW] AWS Certified Data Engineer Associate 2023 – Hands On!

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Deal Score+7
[NEW] AWS Certified Data Engineer Associate 2023 - Hands On!

[NEW] AWS Certified Data Engineer Associate 2023 – Hands On!

AWS DEA-C01 certification prep course with exercises. S3, Glue, Kinesis, Redshift, Lambda, Athena, EventBridge, and more

Created by Sundog Education by Frank Kane, Stephane Maarek | AWS Certified Cloud Practitioner,Solutions Architect,Developer, Frank Kane | 21.5 hours on-demand video course

Update - 2023The course is based on the currently available exam guide and practice exam from AWS. This course will be kept updated as new beta and final exams are released by Amazon. Happy learning!

The AWS Certified Data Engineer Associate Exam is one of the most challenging associate-level certification exams you can take from Amazon Web Services, and even among the most challenging overall. Passing it tells employers in no uncertain terms that your knowledge of data pipelines is wide and deep. But, even experienced technologists need to prepare heavily for this exam. This course sets you up for success, by covering all of the data ingestion, transformation, and orchestration technologies on the exam and how they fit together.

Best-selling Udemy instructors Frank Kane and Stéphane Maarek have teamed up to deliver the most comprehensive and hands-on prep course we’ve seen. Together, they’ve taught over 2 million people around the world. This course combines Stéphane’s depth on AWS with Frank’s experience in wrangling massive data sets, gleaned during his 9-year career at Amazon itself.

The world of data engineering on AWS includes a dizzying array of technologies and services. Just a sampling of the topics we cover in-depth are:

  • Streaming and transforming data with Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (MSK)
  • Queuing messages with Simple Queue Service (SQS)
  • Orchestrating data pipelines with Amazon AppFlow, Amazon EventBridge, AWS Step Functions, and Amazon Managed Workflows for Apache Airflow (MWAA)
  • Transitioning from small to big data with the AWS Database Migration Service (DMS), AWS DataSync, Snow Family, Transfer Family, and more
  • Storing massive data lakes with the Simple Storage Service (S3) and managing data lifecycles
  • Optimizing transactional queries with DynamoDB, DocumentDB, Keyspaces, and MemoryDB
  • Tying your big data systems together with AWS Lambda
  • Making unstructured data query-able with AWS Glue, Glue DataBrew, and Lake Formation
  • Processing data at unlimited scale with Elastic MapReduce, including Apache Spark
  • Applying advanced machine learning algorithms at scale with Amazon SageMaker
  • Searching and analyzing petabyte-scale data with Amazon Opensearch (formerly Elasticsearch) Service
  • Querying S3 data lakes with Amazon Athena
  • Hosting massive-scale data warehouses with Redshift and Redshift Spectrum
  • Integrating smaller data with your big data, using the Relational Database Service (RDS)
  • Visualizing your data interactively with Quicksight
  • Keeping your data secure with encryption, KMS, Macie, Secrets Manager, IAM, and more
  • Managing and governing your systems with CloudFormation, CloudTrail, CloudWatch, AWS Config, and more

Throughout the course, you’ll have lots of opportunities to reinforce your learning with hands-on demos and practice questions. We’ll also arm you with some valuable test-taking tips and strategies along the way.

Although this is an associate-level exam, it is one of the more challenging ones. AWS recommends having a few years of both data engineering experience and AWS experience before tackling it. This exam is not intended for AWS beginners.

You want to go into the AWS Certified Data Engineer Associate Exam with confidence, and that’s what this course delivers. Hit the enroll button, and we’re excited to see you in the course… and ultimately to see you get your certification!

What you’ll learn

  • Maximize your odds of passing the AWS Certified Data Engineer – Associate (DEA-C01) exam
  • Design and implement data pipelines with AWS to ingest, store, and transform data
  • Choose and design data stores, data models, data schemas, and data lifecycles.
  • Maintain, operationalize, and orchestrate data pipelines with EventBridge, Airflow, AWS Step Functions,, and more
  • Apply security, governance, and privacy best practices to your AWS data pipelines.
  • Create data lakes with S3, Glue, Redshift and more
  • Process batch and streaming data with Kinesis, EMR, containers, Lambda, and more

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Who this course is for:

  • Technologists seeking certification in data engineering technologies on Amazon Web Services
Josh Smith
Josh Smith

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