Effective predictive modeling projects follow the analytics life cycle – from data and discovery to deployment and decisions. Data scientists use a variety of tools, both commercial and open source, to collaborate and develop enterprise applications of analytics and artificial intelligence.

SAS Viya provides a unified platform to perform all these from one graphical user interface or through programming APIs.

In this virtual hands-on workshop powered by AWS, you’ll load data into memory, prepare input variables for modeling and build complex analytics pipelines to demonstrate powerful machine learning models.

Need to integrate open source models? No problem. We’ll show you how you to do that and deploy any model. Then you can save and package the best-performing model for deployment while keeping the ability to retrain it on new data.

You’ll learn how to:

• Build SAS Viya models using the Python API and the SWAT package.
• Build deep learning models using Viya and the DLPy package.
• Build SAS and open source models using Model Studio in Viya.
• Deploy SAS and open source models using SAS Open Model Manager.