On-Demand Webinar

The Data Scientist Learning Journey: On Your Mark – From Start to Data Science Project in Two Months

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

Whether you want to add to your portfolio or make an impact in your role, completing a successful data science project can help you get there.

Hear how Kevin Benton, Statistical Training and Technical Services Intern at SAS, completed data engineering, created a new feature, built a monitoring dashboard, and automated a pipeline for updating a key system – all in two months. He’ll share his process and the SAS tricks he learned along the way.

Join us to gain the knowledge you need to bring your project over the finish line, plus a toolkit of resources to help.

Why attend?

  • Learn how you can complete your own data science project in two months.
  • Discover SAS resources to get you started, including e-learning.
  • Hear how teaming up with others can help.

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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.


Kevin Benton
Statistical Training and Technical Services Intern, SAS

Kevin Benton joined the Learning Data Science team in May 2022 and has worked on data science and data visualization projects. Benton enjoys delivering valuable insights that drive better decisions through his data science work. He holds bachelor’s and master’s degrees from Elizabeth City State University and is pursuing his doctorate in Computational Data Science and Engineering at North Carolina A&T State University.