This course showcases how to manage a data science project using both SAS and Python to predict customer churn for a fictitious online personal styling service. Using SAS Viya Workbench, you’ll explore how to access, transform, and analyze data from cloud object storage and data lakehouses, then build machine learning models in both SAS and Python. By the end, you’ll be equipped to handle data exploration, model deployment, and integrate version control with GitHub in a modern cloud environment.
Learn How To
Perform essential tasks in a data science project using both SAS and Python to streamline workflows.Get started with SAS’ on-demand cloud computing environment named SAS Viya Workbench.Use Visual Studio Code, a popular open-source code editor developed by Microsoft, and its SAS extension to develop SAS and Python code efficiently.Seamlessly integrate SAS Viya Workbench with GitHub for streamlined version control and team collaboration.Access, transform, and enrich data from diverse sources, including cloud object storage, data lakes, and data lakehouses such as Snowflake.Explore, clean, and prepare data for machine learning models in both SAS and Python.Create, tune, and evaluate predictive models to identify customers most likely to churn.Deploy machine learning models into production environments, making real-time predictions on live data for business impact.Who Should Attend
Data Scientists who begin their journey with SAS
Prerequisites
Before attending this course, you should have experience using computer software. No prior SAS or Python experience is needed.
SAS Products Covered
SAS Viya
Course Outline
Course Overview
Predicting customer churn use case introduction.What you will learn in this course.Introduction to SAS Viya Workbench.Getting Started with SAS Viya WorkbenchExploring SAS Viya Workbench user interface.Connecting SAS Viya Workbench with GitHub.Addressing the Use Case with the SAS LanguageAccessing and exploring data.Data engineering.Machine learning.Productionizing the model.Addressing the Use Case with the Python LanguageAccessing and exploring data.Data engineering.Machine learning.