Natural Language Processing (NLP) Techniques

Catalog description

Natural language processing (NLP) is the study of the complexities of analyzing linguistic information both in text and voice. Students examine the complexities of language phenomena and how to handle those using current NLP tools and scripting techniques. The course covers topics such as tokenization, sentence structure, grammars, parsing, machine translation, and sentiment analysis. Students discuss and examine how data selection and sampling across genres affects NLP systems, including learning how to leverage social media data along with more formal language sources for English and multilingual data. Students must achieve a minimum grade of B-. Prerequisite: DATA 566 with a minimum grade of B-.