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Course Description

Introduction to computational methods as applied to Humanities data. Data preparation, natural language processing, probability and statistics, visualization, machine learning, and prediction. Datasets for demonstrations and projects include texts, geographical, archaeological, and numerical data. Lab session and report each week and requires hands-on computing. The class will focus on Classical studies problems when taught by a Classics faculty member and on other areas of the Humanities when taught by others. Graduate students will demonstrate originality in their research by acquiring and preparing their own data and executing thorough cross-checking and assessment of their results. Graduate students taking the class as part of the MA in Digital Tools for PreModern Studies will need to integrate a language component to their research by operating on Latin, Greek, or other texts in an approved language. Satisfies the A&S Humanities distribution requirement. No prerequisites.