This tutorial provides a complete introduction to freud. Rather than attempting to touch on all features in freud, it focuses on common core concepts that will help understand how freud works with data and exposes computations to the user. The tutorial begins by introducing the fundamental concepts of periodic systems as implemented in freud and the concept of Compute classes, which consitute the primary API for performing calculations with freud. The tutorial then discusses the most common calculation performed in freud, finding neighboring points in periodic systems. The package’s neighbor finding tools are tuned for high performance neighbor finding, which is what enables most of other calculations in freud, which typically involve characterizing local environments of points in some way. The next part of the tutorial discusses the role of histograms in freud, focusing on the common features and properties that all histograms share. Finally, the tutorial includes a few more complete demonstrations of using freud that should provide reasonable templates for use with almost any other features in freud.