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.
What you'll learn
Manage real-time data streams with Amazon Kinesis and SQS
Build scalable data pipelines
Implement data ingestion strategies
Use Amazon S3, DynamoDB, and Redshift for data storage and processing
Optimize performance and ensure security of data architectures
Analyze and visualize data with Amazon QuickSight, OpenSearch, and Athena
Course objectives
Prepare for the AWS Certified Data Analytics Specialty exam
Develop hands-on skills relevant to data engineering and analytics
Design scalable and secure data architectures on AWS