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.

Lernen Sie, wie Sie / Learn how to

• 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.

Zielgruppe / Who should attend

R users who want to take advantage of SAS Viya distributed analytics for fast and efficient modeling

Verfügbare Schulungsformen / Formats available	Dauer (kann variieren, Details s. Terminliste)
Präsenzkurs:	1.0 Tag
Live Web Class:	7 Stunden	Systemvoraussetzungen

Before taking this course, you should have experience writing R programs for data analytics. There are no SAS prerequisites.

In diesem Kurs wird mit folgenden Software Modulen gearbeitet / This course addresses SAS Viya, SAS Visual Data Mining and Machine Learning Software

SAS Viya and Open Source Integration

• SAS Viya and Cloud Analytic Services (CAS).
• Open source development interfaces.
• Scripting Wrapper for Analytics Transfer (SWAT).
• Fundamentals of the R and Python APIs.

Machine Learning

• Predictive modeling.
• Predictive models.
• Model assessment.