On-Demand Webinar

The Data Scientist Learning Journey: Essential Ingredients for Turning Data Into Action

This webinar series is designed for individuals who want to elevate their data science skills using SAS® and keep pace with the most innovative technology.

The Data Scientist Learning Journey

About the webinar

Join us for practical tips for turning data into action by communicating its value across your organization.

As a data scientist, you understand the power of data to solve business problems.

But turning insights into action across the organization is often the missing ingredient for success.

Whether you’re an experienced data scientist or just starting your career, join SAS experts to learn how to stand out by communicating the value of your work.

This webinar will discuss practical tips for building an efficient data pipeline, making data accessible across the organization, and more.

Why attend?

  • Learn how to make insights quick, convenient, consistent and customizable.
  • Discover practical ways to turn data into action.
  • Explore how to communicate the importance of insights in various business areas.

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About the Experts

Catherine Truxillo
Director of Analytical Education, SAS

Catherine Truxillo has written or co-written SAS training courses for advanced statistical methods, including: multivariate statistics, linear and generalized linear mixed models, multilevel models, structural equation models, imputation methods for missing data, statistical process control, design and analysis of experiments, and cluster analysis. She also teaches SAS courses using SAS/IML®, SAS® Enterprise Guide®, SAS® Enterprise Miner, SAS Forecast Studio and JMP® software.

Aurora Peddycord-Liu, PhD
Senior Analytical Training Consultant, SAS

Aurora Peddycord-Liu started the learning data science team in the SAS Education department. Her responsibilities include creating data resources that connect with business goals and scaling insights through dashboards, analytics algorithms and experiments. Peddycord-Liu holds a PhD in computer sciences from North Carolina State University, where she won a departmental outstanding research award and had two best student paper nominations.