Over the last decade, the scale and scope of data available to social scientists has exploded. In this course, students learn computational methods for the analysis of new types of data, including networks, text, audio, images, and videos. We begin with mechanistic approaches to supervised and unsupervised learning, then move to statistical inference with probabilistic interpretations, paying particular attention to the use and misuse of these models in the social sciences. In addition to problem sets, students will collect and analyze novel data to be presented in a department poster session at the end of the semester.
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