Probabilistic modeling is transforming the study of human language, ranging from novel theories of linguistic cognition to sophisticated techniques for statistical analysis of complex, structured linguistic data to practical methods for automated processing of language. Doing cutting-edge research in these areas requires skill with probability and statistics, familiarity with formalisms from computational linguistics, ability to use and develop new computational tools, and comfort with handling complex datasets. This course will cover both theory and application, covering conceptual fundamentals and giving hands-on opportunies for skill building, while covering a number of important topics in this area.  Both maximum-likelihood and Bayesian approaches will be covered.  We'll be using a variety of software packages for the open-source R programming language implementing models we cover.