Keith J. O'Hara

teaching

ML 101

Data Visualization

Datasets, and their graphical manifestations, are a common mode of argument and persuasion in modern daily life. This class will challenge students to critically engage with the rhetorical function of information visualization. This criticism (i.e. reading) will be complemented and reinforced by creating new visualizations (i.e. writing), a process that is part science, part design and part art. In this short course, students will use a variety of computational platforms including pencil and paper, spreadsheets, software visualization toolkits, and their own small programs to bring datasets to graphical life. The pitfalls and advantages of various methods of presenting numeric, geographic and textual datasets will be constructed and deconstructed.