NEW: Now includes a full-length practice exam.
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NEW: Now includes a full-length practice exam.
NEW: Now includes a full-length practice exam.
The AWS Certified Data Engineer Associate Exam (DEA-C01 or DE1-C01) 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)
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, a full-length practice exam, and additional 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.
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Instructor
My name is Stéphane Maarek, I am passionate about Cloud Computing, and I will be your instructor in this course. I teach about AWS certifications, focusing on helping my students improve their professional proficiencies in AWS.
I have already taught
With AWS becoming the centerpiece of today's modern IT architectures, I have decided it is time for students to learn how to be an AWS Data Analytics Professional. So, let’s kick start the course. You are in good hands.
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Instructor
Hey, I'm Frank Kane, and I'm also co-instructing this course. I spent nine years working for Amazon from the inside as a senior engineer and senior manager, and I'm best known for my top-selling courses in "big data", data analytics, machine learning, AI, Apache Spark, system design, and Elasticsearch.
I've been teaching on Udemy since 2015, where I've reached over 800,000 students all around the world.
I've worked hard to keep this course up to date with the latest developments in AWS data engineering, and to make sure you're prepared for the latest version of this exam. Let's dive in and get you ready.
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This course also comes with:
Lifetime access to all future updates
A responsive instructor in the Q&A Section
Udemy Certificate of Completion Ready for Download
A 30 Day "No Questions Asked" Money Back Guarantee.
Join us in this course if you want to pass the AWS Certified Data Engineer - Associate Exam DEA-C01 and master the AWS platform.
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What's inside
Learning objectives
- 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
- 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
Syllabus
Introduction
Course Overview - Services we will Cover
Get the Course Materials
Udemy 101
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Syllabus
The following three coding exercises allow you to practice solving SQL problems in a hands-on environment!
However, we have heard feedback from some students that Udemy's SQL workspace can be unreliable at times, timing out even on simple queries. If you encounter technical problems, please let Udemy support know. You can visit https://support.udemy.com/hc/en-us/articles/229606768-Learning-With-Coding-Exercises and click on the "Contact Us" button. After some screening from a chatbot, you should be able to file a trouble ticket describing the problem.
Check your learning from our overview of the data engineering fundamentals called out on the AWS exam guide.
Test your knowledge of AWS storage services and how they relate to data engineering pipelines.
Good to know
Save this course
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Activities
Review SQL Syntax
Show steps
Refresh your SQL syntax by completing exercises and reviewing documentation to help you prepare for this course.
Browse courses on
SQL
Show steps
-
Review basic SQL syntax, including SELECT, INSERT, UPDATE, and DELETE statements
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Practice writing SQL queries to retrieve and manipulate data
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Review additional SQL syntax as needed to prepare for the course
Compile a Collection of AWS Data Engineering Tools and Resources
Show steps
Strengthen your knowledge base by gathering and organizing a comprehensive list of AWS data engineering tools and resources that you can refer to throughout your learning journey.
Browse courses on
Resources
Show steps
-
Research and identify AWS data engineering tools
-
Gather information on each tool, including its purpose, benefits, and use cases
-
Create a spreadsheet or document to organize the resources
Build a Data Lake with AWS Lake Formation
Show steps
Enhance your data lake skills by following a guided tutorial on building and managing a data lake using AWS Lake Formation.
Browse courses on
Data Lake
Show steps
-
Set up AWS Lake Formation
-
Create a data lake
-
Add data to the data lake
-
Query data using Athena
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice Data Pipeline Design with AWS CLI
Show steps
Reinforce your understanding of data pipeline design by practicing with the AWS CLI, which is essential for real-world data engineering tasks.
Show steps
-
Set up your AWS CLI environment
-
Create an S3 bucket for data storage
-
Create a DynamoDB table for data storage
-
Use the AWS CLI to copy data from S3 to DynamoDB
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Use the AWS CLI to query data from DynamoDB
Join a Study Group for Data Pipeline Optimization
Show steps
Enhance your understanding by collaborating with peers in a study group dedicated to exploring techniques and best practices for optimizing data pipelines.
Browse courses on
Data Pipeline Optimization
Show steps
-
Find or create a study group
-
Establish a regular meeting schedule
-
Discuss optimization techniques
-
Share knowledge and experience
Design and Implement a Data Pipeline for a Real-World Dataset
Show steps
Apply your knowledge and solidify your understanding by designing and implementing a data pipeline that addresses a real-world business problem.
Show steps
-
Identify a data source
-
Design the data pipeline
-
Implement the data pipeline
-
Evaluate the data pipeline
Mentor Junior Data Engineers on Data Engineering Fundamentals
Show steps
Reinforce your own understanding and solidify your knowledge by guiding and assisting junior data engineers in grasping the fundamentals of data engineering.
Browse courses on
Mentoring
Show steps
-
Identify opportunities to mentor
-
Prepare materials and topics
-
Provide guidance and support
Review SQL Syntax
Show steps
Refresh your SQL syntax by completing exercises and reviewing documentation to help you prepare for this course.
Browse courses on
SQL
Show steps
- Review basic SQL syntax, including SELECT, INSERT, UPDATE, and DELETE statements
- Practice writing SQL queries to retrieve and manipulate data
- Review additional SQL syntax as needed to prepare for the course
Compile a Collection of AWS Data Engineering Tools and Resources
Show steps
Strengthen your knowledge base by gathering and organizing a comprehensive list of AWS data engineering tools and resources that you can refer to throughout your learning journey.
Browse courses on
Resources
Show steps
- Research and identify AWS data engineering tools
- Gather information on each tool, including its purpose, benefits, and use cases
- Create a spreadsheet or document to organize the resources
Build a Data Lake with AWS Lake Formation
Show steps
Enhance your data lake skills by following a guided tutorial on building and managing a data lake using AWS Lake Formation.
Browse courses on
Data Lake
Show steps
- Set up AWS Lake Formation
- Create a data lake
- Add data to the data lake
- Query data using Athena
Practice Data Pipeline Design with AWS CLI
Show steps
Reinforce your understanding of data pipeline design by practicing with the AWS CLI, which is essential for real-world data engineering tasks.
Show steps
- Set up your AWS CLI environment
- Create an S3 bucket for data storage
- Create a DynamoDB table for data storage
- Use the AWS CLI to copy data from S3 to DynamoDB
- Use the AWS CLI to query data from DynamoDB
Join a Study Group for Data Pipeline Optimization
Show steps
Enhance your understanding by collaborating with peers in a study group dedicated to exploring techniques and best practices for optimizing data pipelines.
Browse courses on
Data Pipeline Optimization
Show steps
- Find or create a study group
- Establish a regular meeting schedule
- Discuss optimization techniques
- Share knowledge and experience
Design and Implement a Data Pipeline for a Real-World Dataset
Show steps
Apply your knowledge and solidify your understanding by designing and implementing a data pipeline that addresses a real-world business problem.
Show steps
- Identify a data source
- Design the data pipeline
- Implement the data pipeline
- Evaluate the data pipeline
Mentor Junior Data Engineers on Data Engineering Fundamentals
Show steps
Reinforce your own understanding and solidify your knowledge by guiding and assisting junior data engineers in grasping the fundamentals of data engineering.
Browse courses on
Mentoring
Show steps
- Identify opportunities to mentor
- Prepare materials and topics
- Provide guidance and support
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