Natural Language Processing.

Catalog description

This course is an introduction to the topic of natural language processing (NLP) from a computational perspective. The course covers both formal and statistical approaches to NLP. Coursework includes programming, analysis and literature review assignments. Topics include: n-gram models, part-of-speech tagging, hidden Markov models, parsing, semantics, information extraction, question answering, dialogue agents and machine translation. Prerequisites: Algorithms Core Skill and Computing Theory Core Skill and Graduate or blended students in the School of Engineering and Computer Science or instructor approval.