Modern Data Science with SAS® Viya® Workbench: Unified Development with SAS®, Python, and R
3h 35m + Hands-On Practice
Available in:
Modern Data Science with SAS® Viya® Workbench: Unified Development with SAS®, Python, and R
SAS1 : SAS1V2
This course demonstrates how to manage a full data science project using SAS, Python, and R to predict customer churn for a fictitious online personal styling service. With SAS Viya Workbench, you’ll learn how to access, transform, and analyze data from cloud object storage and data lakehouses, then build and compare machine learning models in SAS, Python, and R. By the end, you’ll be prepared to explore data, deploy models, and integrate version control with GitHub — all within a modern cloud environment.
Learn How To
- Perform core tasks in a data science project using SAS, Python, and R to improve workflow efficiency
- Get started with SAS Viya Workbench, SAS’ on-demand cloud computing environment
- Develop SAS, Python, and R code efficiently in Visual Studio Code with the SAS extension
- 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 platforms like Snowflake
- Explore, clean, and prepare data for machine learning models across SAS, Python, and R
- Build, tune, and evaluate predictive models to identify customers most likely to churn
- Deploy machine learning models into production to deliver real-time predictions with 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
- Welcome to the course.
- Using the hands-on lab with this course.
- What's new.
- Validate course environment.
- Predicting customer churn use case introduction.
- What is SAS Viya Workbench?
- Exploring SAS Viya Workbench user interface.
- Connecting SAS Viya Workbench with GitHub.
- Accessing and exploring data.
- Data engineering.
- Machine learning.
- Productionizing the model.
- Accessing and exploring data.
- Data engineering.
- Machine learning.
- Accessing and exploring data.
- Data engineering.
- Machine learning.
- Collaborating with Git.
- Transitioning the model to SAS Viya.
- Appendix - Getting a token for connecting to SAS Viya.
- What you learned in this course.
Live Class Schedule
Duration: 7 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.