In this course, you learn to use the R API to take control of SAS Cloud Analytic Services (CAS) actions from Jupyter Notebook. You learn to upload data into the in-memory distributed environment, analyze data, and create predictive models in CAS using familiar R functionality via the SWAT (SAS Wrapper for Analytics Transfer) package. You then learn to download results to the client and use native R syntax to compare models.
SAS-ROSI35 | SAS® Viya® and R Integration for Machine Learning
S$1,320 1 day SAS-ROSI35
Course Overview
Who Should Attend
R users who want to take advantage of SAS Viya distributed analytics for fast and efficient modeling
Learning Outcomes
• Use the R API in SAS Viya.
• Submit CAS actions from R.
• Manage, alter, and prepare data on the CAS server.
• Implement and compare machine learning models on the CAS server.
• Move data between the client and server.
• Use R syntax to wrap up CAS actions with functions and loops.
• Promote data to persist in memory.
Course Outline Course Outline (PDF)
Module 1: SAS Viya and Open Source Integration
Module 2: Machine Learning
Class Schedule 2026
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