The world of data engineering is continuously evolving, and staying ahead requires constant learning and adaptation. Recognizing this, a new course on Udemy, titled “AWS Data Engineering Labs“, aims to equip learners with the latest skills and knowledge in the field of data engineering on AWS. Published on March 24, 2024, this course offers a hands-on learning experience designed to enhance data engineering skills through practical labs covering essential AWS services.
What You’ll Learn
Participants will dive into data engineering labs on AWS, engaging with services such as AWS Glue, Athena, Lambda, Kinesis, S3, Redshift, EventBridge, EMR, and Step Functions. The course is structured to:
- Enhance data engineering skills on AWS with hands-on labs.
- Provide practical experience with AWS services like Glue, Lambda, Kinesis, S3, Redshift, and EventBridge.
- Teach how data catalogs, ETL jobs, and workflow orchestrations solve real-world data engineering problems.
- Offer hands-on and sample questions to aid in DEA-C01 exam preparation.
Requirements
This course is tailored for individuals with:
- A basic understanding of AWS.
- Fundamental knowledge of Python, SQL, Spark, and database concepts.
Notably, the course is designed to be accessible even to beginners in data engineering, making it an excellent starting point for those looking to enter the field.
Course Description
“AWS Data Engineering Labs” focuses on practical aspects of data engineering, minimizing theoretical discussions to concentrate on real-world application. The course provides a series of labs that guide participants through the use of various AWS services crucial for data engineering tasks. It covers creating a data catalog in Glue, orchestrating workflows with Step Functions, running Spark transformation jobs using Amazon EMR, and much more.
The course’s pragmatic approach is complemented by encouraging participants to consult AWS documentation for a deeper understanding of the concepts covered. Additionally, it includes questions and answers that are beneficial for those preparing for the Data Engineering certification (DEA-C01).
Course Sections
The course is structured into 6 sections with 19 lectures, totaling 1 hour and 57 minutes of content. Highlights include:
- Introduction to AWS Glue and Amazon EventBridge.
- Labs on running ETL jobs using Glue and triggering notifications for S3 uploads using EventBridge.
- Understanding and applying AWS Step Functions and Kinesis Data Stream.
- Creating a Data Warehouse using Amazon Redshift.
Who Should Enroll
This course is ideal for beginners in AWS Data Engineering and those seeking to solidify their knowledge and practical skills in the field. With its focus on practical labs and essential AWS services, the course serves both beginners and professional data engineers looking to update their skills.
Reviews
Learners have praised the course for its precise and focused content, clear explanations, and the practical utility of the covered topics. Reviews highlight the course’s effectiveness in delivering valuable knowledge for both beginners and professionals in the data engineering domain.
In conclusion, “AWS Data Engineering Labs” stands out as an essential resource for anyone looking to enhance their data engineering skills on AWS. With its hands-on approach and comprehensive coverage of AWS services, it is poised to become a key tool in the toolbox of aspiring and established data engineers alike.
