Qualitative Findings from an Online Course on Machine Learning

Abstract

This is a full paper in the Innovate Practice category. It reports experiences while teaching a largely online course about Machine Learning at two separate Universities. We targeted our course for a much wider than usual audience -- as “Computer Science (CS) for All,” with undergraduate non-CS majors learning the same material alongside CS majors. We discuss why the majority of the students appreciated the flexibility of online classes designed for this wide group, and how they welcomed the opportunity to learn together about a “hot” topic such as Machine Learning. We explain our handling of challenges coordinating diverse and remote teams working with realistic big data of their own interest. Moreover, we describe how we engaged students in stimulating discussions about their readings and team projects, and how we balanced keeping everyone on the same pace while providing opportunities for learning ahead. Finally, we explain how we were able to attract the non-CS majors to take a CS special topics course and how we plan to use their constructive suggestions to improve future offerings of this course.