Webinar: Information session on Carnegie Mellon University School of Computer Science Executive Education’s Machine Learning: Fundamentals and Algorithms program (Webinar) by Emeritus

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Information session on Carnegie Mellon University School of Computer Science Executive Education’s Machine Learning: Fundamentals and Algorithms program (Webinar)

About

With the paradigm shift in technology trending hard in the direction of machine learning and artificial intelligence, the skills of future-ready technologists, analysts, engineers and data managers also must shift, expand and advance. Machine Learning: Fundamentals and Algorithms, an online program offered by Carnegie Mellon University’s School of Computer Science Executive Education, provides you with the technical knowledge and analytical methods that will prepare you for the next generation of innovation.

Register for this informative webinar to learn more about the upcoming Machine Learning: Fundamentals and Algorithms program from Carnegie Mellon University School of Computer Science Executive Education.

When

Tue, Jul 26, 2022 · 9:00 AM Eastern Time (US & Canada) (GMT -4:00)

WEBINAR ENDED

Agenda

Hear from pioneering thought-leaders
Dive deeper into fascinating topics that are changing the world
Explore how our multifaceted learning approach will help you create lasting impact
...and so much more!

Presenters

Patrick Virtue

Assistant Teaching Professor, Computer Science and Machine Learning, Carnegie Mellon University

Pat Virtue is an Assistant Teaching Professor in the Computer Science and Machine Learning departments at Carnegie Mellon University. He focuses on teaching techniques for artificial intelligence, machine learning, and computer science. His interests include active learning teaching methods, effective instruction for large classes, building inclusive learning environments, and AI/ML curriculum development. Pat completed his graduate work at UC Berkeley in Electrical Engineering and Computer Sciences, and his undergraduate at the University of Notre Dame. Prior to graduate school, he researched and developed volumetric medical image applications as a software engineer at GE Healthcare.

Matt Gormley

Assistant Teaching Professor, Computer Science and Machine Learning, Carnegie Mellon University

As Assistant Teaching Professor in the Machine Learning Department at CMU, Dr. Gormley regularly teaches Introduction to Machine Learning to more than 400 students, one of the largest courses offered at CMU. His research focuses on machine learning for natural language processing. His interests include global optimization, learning under approximations, hybrids of graphical models and neural networks and applications where supervised resources are scarce.

Dr. Gormley earned a BS in Computer Science and Cognitive Science from CMU and an MSE and PhD in Computer Science from Johns Hopkins University.

Jacob Koehler

Course Leader