This article describes a pilot undergraduate course designed to introduce the fundamentals of machine learning (ML) and generative artificial intelligence (AI) in an accessible and practical way to students from diverse disciplines. Emerging from cross-departmental collaboration, the course aims to demystify AI and equip students, particularly those from nontechnical fields, with essential ML and signal processing (SP) concepts, while helping them understand their applications and practice as end users. The article outlines the course content, student outcomes, and considerations for evaluating its effectiveness and potential areas for improvement.
Butler et al. (Thu,) studied this question.