When we organize and visualize data, we make it meaningful and communicative. But in so doing, we also give it a form—an aesthetic shape—that did not previously exist. In this course, we will consider aesthetics as a crucial, but often overlooked, component of data science. Our goal will be to develop the basic aesthetic literacy needed to critically consider the ways we present information. The course contains two interrelated units: first, we will study the vocabulary that 20th-century art critics developed to talk about the sensory, emotional, and political qualities of art. We will pay close attention to art critics who helped the public perceive meaning in even the most abstract, seemingly disordered art, such as the drip paintings of Jackson Pollock. In the second unit, we will consider how descriptive and critical language borrowed from art theory might be useful in the field of data analysis, both by making us aware of the ways in which data is shaped and manipulated and by helping us to perceive meaning where patterns are absent or not readily perceptible.