3.0

credits

Average Course Rating

This course introduces students and researchers from humanities disciplines to ideas and practices from the computational sciences. The course aims to provide the understanding needed for self-sufficient exploration and well-informed criticism of how computational methods relate to traditional scholarship. The semester begins with a history of computational research, then covers three major aspects of computational inquiry for the humanities: 1) representing primary sources, domains, and scholarly knowledge, 2) interacting with such representations via basic computer programming, and 3) introducing data-driven machine learning ("AI") to complement existing humanistic practices. Lectures and labs will also cover specific methods that immediately assist the scholar with practical tasks, such as regular expressions for pattern-based information retrieval and topic modeling for unsupervised primary source exploration. No prior experience with computation or programming is needed, and the course is particularly suited for advanced undergraduate and graduate students pursuing applied research in the humanities.