DATA 350 - Natural Language Processing

Credits: (3)
This course focuses on the rapidly advancing AI subfield of Natural Language Processing (NLP), and its role in analyzing massive quantities of unstructured text-heavy data. Topics will be selected from text classification, stemming and lemmatization, sentiment analysis, locality-sensitive hasting, topic modeling, language modeling and part-of-speech identification, word and sentence embedding, text summarization, and text generation. Prerequisite(s): CMSCI 125 Introduction to Computer Science II (3) or DATA 200 Introduction to Data Science (3)