Machine learning in the liberal arts curriculum

Machine learning is typically considered a graduate-level course with an artificial intelligence course as a prerequisite. However, it does not need to be positioned this way, and in the liberal arts curriculum in particular, there are advantages to offering this course to undergraduate students. An undergraduate course in machine learning is easily and naturally structured to introduce research concepts and to work within a research paradigm. It also introduces the use of statistics, reflected both in the machine learning systems studied and in the experimental methodology. Furthermore, it allows for an interdisciplinary perspective, as students can be encouraged to work on problems from other departments in the college. This paper describes the benefits of offering such a course and outlines a course structure and resources for doing so.

• Type: Conference
• Year: 2000
• Where: SIGCSE
• Authors: Clare Bates Congdon
• Keywords: Artificial Intelligence Course, Education, Graduate-level Course, Machine Learning, SIGCSE 2000