In this course, you learn to use the R and Python APIs to take control of SAS Cloud Analytic Services (CAS) and submit actions from Jupyter Notebook. You learn to upload data into the in-memory distributed environment, analyze data, and create predictive models on CAS using familiar open-source functionality via the SWAT (SAS Wrapper for Analytics Transfer) package.

Learn how to

• Use the R and Python APIs in SAS Viya.
• Submit CAS actions from Jupyter Notebook.
• Move data between the client and the server.
• Manage, alter, and prepare data on the CAS server.
• Create machine learning and deep learning models on the CAS server.
• Use open-source syntax to wrap up CAS actions with functions and loops.

Who should attend

Data scientists with open source experience who want to take advantage of SAS Viya distributed analytics

Formats available	Duration
e-Learning:	12 hours/180 day license	System Requirements

Students should have experience working with data, creating predictive models, and writing open-source programs. Some SAS experience is recommended.

This course addresses SAS Viya, SAS Visual Data Mining and Machine Learning software.