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EGR 190/EGR 590- AI For Everyone |
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Data science, machine learning, and artificial intelligence are making inroads into many aspects of society, with numerous impacts across disparate disciplines with often surprising applications. The ability to understand the capabilities and limitations of these technologies and use them in an appropriate manner is already an important skill and is projected to be increasingly important in the future. The goal of this course is to provide an applied introduction to current techniques in machine learning and how they can be used to make sense of large amounts of data, while allowing students to focus on how machine learning is impacting their discipline of study.
Classes are scheduled on Monday from 4:40-6:10PM in Gross Hall, Room 330. Note that while there are no formal prerequisites for this course, there will be assumptions on the background of the students described below. Most critically, a background in a programming language will be assumed, and Python will be employed in the course.
Matthew Kenney
[email protected]
Assistant Research Professor
Computational Media and Visual Studies
David Carlson, Ph.D
[email protected]
Assistant Professor
Civil and Environmental Engineering, Biostatistics and Bioinformatics, Duke Clinical Research Institute, Computer Science, Electrical and Computer Engineering
Lawrence Carin
[email protected]
James L. Meriam Professor of Electrical and Computer Engineering