Eligible students—those who have completed the Data Analytics course, submitted the capstone project, and ranked in the top 50%—can join our upcoming orientation session to enroll in AWS Academy courses, learn at their own pace, and enjoy six months of full access.
AWS Academy Data Analytics comprise lab exercises to support existing big data lectures and courses
that an institution is teaching or plans to teach. It is designed to help students prepare for entry-level
roles in data analysis and visualization. The course provides institutions with lab exercises that will
teach students how to analyze large data sets, create visual representations of that data, and publish
those representations to dashboards. The course uses a case study approach to provide students with
the opportunity to experience creating a real-world application of big data analysis.
| Lab 1 | Ingesting Data Into Amazon S3 |
| Lab 2 | Querying Amazon S3 Data Using Amazon Athena |
| Lab 3 | Transforming Data Using Amazon S3, AWS Glue, and Amazon Athena |
| Lab 4 | Loading the Amazon Redshift Cluster With Data and Querying |
| Lab 5 | Delivering Insights using Amazon QuickSight |
| Lab 6 | Setting up and Executing a Data Pipeline Job to Load Data into Amazon S3 |
| Lab 7 | Using AWS IoT Analytics for Data Ingestion and Analysis |
| Lab 8 | Streaming Data with AWS Kinesis Firehose, Amazon Elasticsearch Service, and Kibana |
