ASK THE EXPERT WEBINAR SERIES

SAS Models Around the World

Wednesday, 28 May • 8:30 a.m. IST • 11 a.m. SGT • 1 p.m. AEST

About the webinar

SAS models provide a tangible path to infuse AI, machine learning and analytics modernisation across industries in unique and effective ways. They allow organisations to leverage lightweight, scalable capabilities that enhance organisational AI maturity models by embedding proven elements where and when they are needed.

Among other responsibilities, SAS’ AI and machine learning division is tasked with hardening field service expertise into a software product. Join Luis as he shares insights from the journey to garner that expertise, as well as developing software that solves customers’ business problems.

Why attend?

Hear about the value of SAS models.
Learn about SAS models currently available.
Discover some of the planned SAS models.

Don’t miss this opportunity to gain valuable insights into the development of AI-driven solutions and learn how SAS models can help your organisation achieve its goals.

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About the expert

Luis Flynn

Senior Product Marketing Manager, SAS

Lou Flynn is a product leader focused on making data and AI work in the real world. From 2003 to 2019, he helped design and deliver distributed systems for special operations teams in places like Afghanistan, Iraq, and North Africa—solutions built to handle sensitive data and support decisions in high-pressure environments. Today, he draws on that experience to help organizations tackle complex data challenges and drive adoption of AI tools that actually deliver results.

Dan Kelly (Host)

Sr Manager, Applied AI and Modeling, SAS

Dan Kelly currently manages a team of data scientists who turn analytics and subject-matter expertise into software for SAS’ Applied AI and Modeling (AAIM) division. Before this role, he served as an analytical consultant and consulting manager applying creative thinking to large data sets to solve customer business problems using SAS software. His first role at SAS was in front of the classroom teaching data science and statistics; before SAS, he supported the risk and marketing departments at a credit card bank with predictive modeling and experimental design.

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