Natural Language Processing

3 credits · Undergraduate

This course will focus on using computers to analyze language data for linguistic elements related to cognitive processing. The goal of the course is to provide students with the background and computing skills necessary to independently analyze and assess language features in naturally occurring text. At the lexical level, this will include assessments of words and morphemes for features related to complexity and sentiment. At the syntactic level, analyses will examine part-of-speech tagging, dependency parsing, and phrasal and clausal complexity. At the semantic level, lexical relationships along with cohesion features will be examined. All analyses will be computational, and students will be introduced to the Python programming language and appropriate Python packages. The course will be practice-based, and the final project will require students to analyze language data of interest to their field of research, discuss the data from an analytical language perspective, and model outcomes. No background knowledge in computer programming is necessary to be successful in this course. Pre-requisite : PSY 2100 or PSY-PC 2110 or ECON 1500 or MATH 2810 or a score of 5 on the AP Statistics Exam [3]