Natural Language Processing

Natural Language Processing (NLP) is a rapidly developing field with broad applicability throughout the hard sciences, social sciences, and the humanities. The ability to harness, employ and analyze linguistic and textual data effectively is a highly desirable skill for academic work, in government, and throughout the private sector. This course is intended as a theoretical and methodological introduction to a the most widely used and effective current techniques, strategies and toolkits for natural language processing, with a primary focus on those available in the Python programming language. We will also consider how harnessing large digital corpora and large-scale textual data sources has changed how scholars engage with and evaluate digital archives and textual sources, and what opportunities textual repositories offer for computational approaches to the study of literature, history and a variety of other fields, including law, medicine, business and the social sciences. In addition to evaluating new digital methodologies in the light of traditional approaches to philological analysis, students will gain extensive experience in using Python to conduct textual and linguistic analyses, and by the end of the course, will have developed their own individual projects, thereby gaining a practical understanding of natural language processing workflows along with specific tools and methods for evaluating the results achieved through NLP-based exploratory and analytical strategies.