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.The e-learning version of this course provides access to SAS Viya for Learners, which enables students to use the software to complete the practices.
The e-learning version of this course provides access to SAS Viya for Learners, which enables students to use the software to complete the practices.
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
Kurzy jsou dostupné jako | Délka | | |
e-Learning: |
12 hodin/180 den licence |
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Students should have experience working with data, creating predictive models, and writing open source programs. Some SAS experience is recommended.