AWS Data Engineering Labs
What you'll 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
Requirements
- 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.
Description
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
Understanding PySpark Basics with Databricks
Setting up Databricks on AWS
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 AWS and Data Engineering, you can still follow and learn from this course.
Who this course is for:
- Beginners in AWS Data Engineering
Instructor
- 4.5 Instructor Rating
- 3,790 Reviews
- 64,344 Students
- 8 Courses
Welcome to FutureXSkills, where we specialize in creating high-quality video content to empower Data Engineers and Data Scientists. With over 60,000 students on Udemy, we take pride in offering top-rated courses that use a simplified, step-by-step approach to learning.
Our courses and videos cater to individuals of all levels, from beginners to experts, and are designed to help you deepen your understanding of data engineering and data science concepts.
Our team of experienced instructors and data professionals works tirelessly to create videos that are easy to follow and comprehend. We achieve this by using clear explanations, visual aids, and real-world examples to make complex topics more accessible. Our video content covers a broad range of topics, including Machine Learning and Big Data technologies, and is designed to provide a comprehensive understanding of each topic.