AWS Data Engineering Labs

AWS Data Engineering Labs, available at $44.99, has an average rating of 4.25, with 17 lectures, based on 41 reviews, and has 1680 subscribers.

You will learn about Enhance your data engineering skills on AWS with hands-on labs Gain practical experience with essential AWS services like Glue, Lambda, Kinesis, S3, Redshift, and EventBridge Learn how data catalogs, running ETL jobs, and orchestrating workflows solve real-world data engineering problems. Hands-on, as well as sample questions, to aid in your DEA-C01 exam preparation This course is ideal for individuals who are Beginners in AWS Data Engineering It is particularly useful for Beginners in AWS Data Engineering.

Enroll now: AWS Data Engineering Labs

Summary

Title: AWS Data Engineering Labs

Price: $44.99

Average Rating: 4.25

Number of Lectures: 17

Number of Published Lectures: 17

Number of Curriculum Items: 17

Number of Published Curriculum Objects: 17

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Enhance your data engineering skills on AWS with hands-on labs
Gain practical experience with essential AWS services like Glue, Lambda, Kinesis, S3, Redshift, and EventBridge
Learn how data catalogs, running ETL jobs, and orchestrating workflows solve real-world data engineering problems.
Hands-on, as well as sample questions, to aid in your DEA-C01 exam preparation

Who Should Attend

Beginners in AWS Data Engineering

Target Audiences

Beginners in AWS Data Engineering

This hands-on course is designed for individuals familiar with AWS to enhance their skills in data engineering. Students should have a basic understanding of Python, SQL, and database concepts. However, even beginners to data engineering can follow along and learn. The course is minimal on theory, focusing instead on practical aspects of data engineering on AWS. Participants will gain practical experience through a series of labs covering essential AWS services such as Glue, Lambda, Kinesis, S3, Redshift, EventBridge, and more. While the labs provide practical exercises, participants are encouraged to refer to AWS documentation for a full understanding of concepts. This course will also give you practical experience to aid in your preparation for the Data Engineering certification (DEA-C01).

AWS Data Engineering Labs :

Creating a data catalog in Glue and viewing data in Athena
Running an ETL job using Glue
Triggering SNS Notification for S3 Upload Event using EventBridge
Orchestrating Lambda functions with Step Functions State Machine
ETL Workflow Orchestration with AWS Glue Lambda EventBridge Step Functions
Storing and Retrieving Data from a Kinesis Data Stream Using AWS CLI
Kinesis Data Stream Python Boto3 Producer & Consumer
Writing simulated weather data from a Kinesis Stream to S3 with AWS Lambda
Running Spark transformation jobs using Amazon EMR on EC2
Creating a Data Warehouse on S3 data using Amazon Redshift
Also you will find some questions and answers for the DEA-C01 exam.

Prerequisites:

Basic understanding of AWS
Basic knowledge of Python, SQL, Spark and database concepts

Note: Even if you are a beginner to data engineering, you can still follow and learn from this course.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Orchestrating a Data Pipeline using Glue, Athena, EventBridge and Step Functions

Lecture 1: Understanding AWS Glue

Lecture 2: Lab – Creating a data catalog in Glue and viewing data in Athena

Lecture 3: Lab – Running an ETL job using Glue

Lecture 4: Understanding Amazon EventBridge

Lecture 5: Lab – Triggering SNS Notification for S3 Upload Event using EventBridge

Lecture 6: Understanding AWS Step Functions

Lecture 7: Lab – Orchestrating Lambda functions with Step Functions State Machine

Lecture 8: Lab – ETL Workflow Orchestration with AWS Glue Lambda EventBridge Step Functions

Chapter 3: Building streaming Data Pipeline with Kinesis and Lambda

Lecture 1: Understanding Kinesis Data Stream

Lecture 2: Lab – Storing and Retrieving Data from a Kinesis Data Stream Using AWS CLI

Lecture 3: Lab – Kinesis Data Stream Python Boto3 Producer & Consumer

Lecture 4: Lab – Writing simulated weather data from a Kinesis Stream to S3 with AWS Lambda

Chapter 4: Running Big Data workloads using Amazon EMR

Lecture 1: Understanding Amazon EMR

Lecture 2: Lab – Running Spark transformation jobs using Amazon EMR on EC2

Chapter 5: Creating a Data Warehouse on Amazon Redshift

Lecture 1: Understanding Amazon Redshift

Lecture 2: Lab – Creating a Data Warehouse on S3 data using Amazon Redshift

Instructors

FutureX Skills
Empowering Data Engineers and Data Scientists

Rating Distribution

1 stars: 0 votes
2 stars: 1 votes
3 stars: 2 votes
4 stars: 13 votes
5 stars: 25 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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