Booting Into AI

Abstract

This tutorial will provide a foundation for faculty members either teaching a course in artificial intelligence for the first time or renewing a course that has been dormant. The growing ubiquity of AI and machine learning dictates that departments offer a course in this area, regardless of whether any such expertise exists locally. Furthermore, there are many possible approaches, from a general overview to a tight focus on a particular application area, either as a single elective or a specialization area within an undergraduate degree. An increasingly wide range of resources is available, but intelligent selection from the plethora of information can be a challenge, particularly in smaller programs where no local expertise is available. The tutorial is in two parts. Part 1 focuses on background knowledge, discussing major divisions within the broad field of AI, research trends and application areas, and commonly used tools. Part 2 addresses classroom implementation, assessment, textbook options, and online resources including code libraries, free-to-use data sets, development environments, and visualization tools. Participants will have the opportunity to brainstorm and discuss options for course focus. Sample syllabi using differing course approaches, sample exams and assignments, and a non-exhaustive list of useful resources will be provided.