Jon Reifschneider

Jon Reifschneider is the Director of Masters Studies for the Artificial Intelligence for Product Innovation (AIPI) program in Duke University's Pratt School of Engineering. Prior to joining the Duke faculty, Jon spent 15 years in management roles at data services and analytics companies. Most recently Jon was Senior Vice President and ran the Weather Analytics division at the tech company DTN, where he and his team created predictive analytics systems that are now core to the daily operations of most of the largest transportation, aviation and energy utility organizations across the US. As a member of the DTN executive team, he led his business through a period of substantial expansion and completed the successful sale of the company in 2017. Jon holds a B.S. in Mechanical Engineering from the University of Virginia where he graduated first in his class, a Master of Engineering Management from Duke University, a M.S. in Analytics from Georgia Tech, and a Global MBA from EBS (Germany). He has lived, worked and studied in the US, Luxembourg, Germany and India.

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Managing Machine Learning Projects (Coursera) Coursera
Duke University

Managing Machine Learning Projects (Coursera)

Dive into the practical aspects of managing machine learning projects with this specialized course by Duke University's Pratt School of Engineering. This second part of the AI Product Management Specialization covers essential steps from identifying opportunities to deploying and maintaining ML systems. Gain insights into the data science process, model building, and system design.

Jun 22nd 2026
5-12 Weeks
Human Factors in AI (Coursera) Coursera
Duke University

Human Factors in AI (Coursera)

Embark on a journey to understand the pivotal role of human factors in AI product management. This course, part of the AI Product Management Specialization by Duke University's Pratt School of Engineering, emphasizes the importance of human-centered design and user experience for AI products. Gain insights into making your AI solutions more intuitive and accessible.

Jun 22nd 2026
4 Weeks
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