On-Demand Webinar

The Data Scientist Learning Journey: Exploring Generative AI

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

Generative AI: It’s more than ChatGPT.

Join this webinar to learn where generative AI fits in the AI landscape and what generative AI can do besides ChatGPT.

Plus, get a more thorough understanding of generative AI, including both the benefits and the risks it poses to society.

You’ll also learn how to make the most of generative AI with SAS and see how SAS provides support for the use of generative AI.

You will learn:

  • The true definition of generative AI.
  • The benefits and risks generative AI poses to society.
  • How to make the most of generative AI with SAS.

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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.


Sharad Saxena
Principal Analytical Training Consultant, SAS

Sharad Saxena is based at the SAS R&D center in Pune, India. Working in the field of statistics and analytics since 2000, he provides education consulting in the area of advanced analytics and machine learning across the globe for a variety of SAS customers in banking, insurance, retail, government, health, agriculture and telecommunications. Saxena earned a bachelor's degree in mathematics with statistics and economics minors, a master's in statistics, and a doctorate in statistics from the School of Studies in Statistics at Vikram University in India. Saxena has more than 35 publications, including research papers in journals such as the Journal of Statistical Planning and Inference, Communications in Statistics – Theory and Methods, Statistica, Statistical Papers, and Vikalpa. He is also a co-author of the book Randomness and Optimal Estimation in Data Sampling.

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