Practical Machine Learning for Liberal Arts Undergraduates
Abstract
Liberal arts education provides students with many interdisciplinary problem-solving skills, but utilizing high-level computational tools like machine learning (ML) remains largely inaccessible without a significant background in computer science. We present a course to bridge that gap: a full-semester undergraduate course that teaches the concepts of ML and deep learning with emphasis on real-world application and ethical considerations. The course is low-code, exploring concepts and applications through a collection of visual tools. Early outcomes show that after this course students are equipped to learn code-based systems, feel empowered to understand and identify misunderstandings in popular AI discourse, and can design ML-based solutions for data-oriented problems in their fields.
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Published In
April 2023
212 pages
Publisher
Consortium for Computing Sciences in Colleges
Evansville, IN, United States
Publication History
Published: 01 April 2023
Published in JCSC Volume 38, Issue 8
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