This course introduces data-driven computational pragmatics, an empirical approach to pragmatics which uses large amounts of linguistic data with only computational annotations to learn models describing pragmatic phenomena. Data-driven computational pragmatics offers two important advantages: (1) experiments which require no direct human intervention can be run on massive amounts of linguistic data; (2) subtle pragmatic phenomena which are below the level of consciousness of individual analysts can be detected and described. This course introduces the practice of and the interpretation of results from data-driven computational pragmatics by presenting case studies of approaches to four pragmatic phenomena: entity recognition and coreference resolution, inferences and reasoning, figurative language, and the pragmatic meaning which results from stylistic variation.