Biochemistry is a data-heavy discipline, yet teaching students to work with large datasets is absent from many undergraduate Biochemistry programs. Ensuring that future generations of students are confident in tackling problems using big data first requires that educators become comfortable teaching big data skills. The activity described herein introduces educators to working with big data and a framework for generating sequence similarity networks using JupyterLab and Python. This article reports a session from the virtual international 2021 IUBMB/ASBMB workshop, "Teaching Science with Big Data."