As institutions grapple with the challenges of keeping students from contracting COVID-19, classroom scheduling and space analysis have become central to assigning courses to physical classrooms. One question institutional leaders ask is whether some courses create a higher risk of exposure based on the number of students who are directly or indirectly connected through their classes. These complex relationships between students and courses can be understood as a "two-mode" network connecting two types of nodes (i.e., course and student). In a "two-mode" network students are connected to courses and courses are connected to students. This relationship can provide insights into the number of connections each student has through classes, how subgroups of students are connected, and the various ways students are connected to each other directly or indirectly. Using student course registration data from Elon University for fall 2020, the authors show how they were able to analyze the structure of a two-mode student-course network. The goal of the analysis is to inform which courses are central in the network and how they are grouped, which can then inform the assignment of classroom space and the recommended mode of delivery (i.e., face-to-face, remote learning, or hybrid) for each class.