enthalten
Updated in May 2025.
This course now features Coursera Coach!
A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.
In this course, you’ll master AWS services essential for passing the AWS Certified Data Analytics Specialty exam. Starting with data collection, you'll use tools like Amazon Kinesis and SQS to manage real-time data streams. Through hands-on labs, you'll build scalable data pipelines and apply data ingestion strategies, gaining practical experience with AWS services that are directly relevant in professional environments.
Next, you’ll dive into data storage and processing with Amazon S3, DynamoDB, and Redshift. Using case studies, you'll implement storage strategies, optimize performance, and ensure security. You’ll simulate real-world scenarios to efficiently manage and query data, preparing you for complex projects. With this knowledge, you’ll be equipped to design scalable, secure data architectures on AWS.
Lastly, you’ll analyze and visualize data with Amazon QuickSight, OpenSearch, and Athena. By course completion, you’ll be ready for the AWS exam and gain hands-on skills to apply in real-world situations. This course is perfect for data engineers, analysts, and IT professionals seeking to enhance their AWS data analytics expertise. A basic understanding of AWS services is recommended.
Praktisches Lernprojekt
Learners will build scalable data pipelines using Amazon Kinesis, SQS, and S3, and apply these skills to solve real-world problems such as populating an S3 data lake from EC2 server data. Through hands-on projects, they will implement AWS services like DynamoDB, Redshift, and QuickSight, simulating authentic scenarios to optimize data storage, processing, and visualization.
