Red Hat® OpenShift® Data Science is a cloud service that gives data scientists and developers a powerful artificial intelligence  and machine learning platform for building intelligent applications. Data scientists and developers can collaborate to quickly move from experiment to production in a consistent environment.

Available as an add-on cloud service to Red Hat OpenShift Dedicated and Red Hat OpenShift Service on AWS or as a self-managed software product, OpenShift Data Science allows data scientists to quickly develop, train, and test ML models at an accelerated pace, using the JupyterLab interface. After models are developed, data scientists can use GitHub integration to trigger updated builds of Red Hat OpenShift applications created by developers.

Join Red Hat experts and your Red Hat User Group (RHUG) community in Boise, Idaho, to explore all things related to AI and ML intelligent applications for the edge. During this event, you’ll learn how to use the OpenShift Data Science platform to:

1. Deploy an anomaly detection "containerized web application" (in Red Hat OpenShift) to display time series data that contains an anomaly.
2. Generate synthetic sensor data to mimic real-time data generated by an edge device (which you’ll use in the next step).
3. Deploy a failure prediction "containerized web application" (in Red Hat Openshift) and use the synthetic sensor data to predict the failure of a mechanical device.