Natural Language Processing

Catalog description

In this course, students will be introduced to the field of natural language processing (NLP), providing them with a comprehensive understanding of the diverse methods employed to analyze text within computational systems. As NLP is inherently interdisciplinary, the course draws from both linguistics and computer science, and we explore text analysis methods applicable in a variety of fields such as computational social science, digital humanities, and computational journalism. The course will place a strong emphasis on core NLP algorithms utilized across various practical applications, including part-of-speech tagging, parsing, semantic labeling, and machine translation. Additionally, we will explore the linguistic phenomena that these algorithms aim to capture and model. Students will actively engage in implementing these algorithms. Satisfies a requirement for the Computer Science major and minor. Satisfies a requirement for the Data Science Interdisciplinary minor. Prerequisites & Notes CSC 221 and CSC/MAT 220, or permission of the instructor.