Natural Language Processing

Info
259

4 units

Course Description

This course introduces students to natural language processing and exposes them to the variety of methods available for reasoning about text in computational systems. NLP is deeply interdisciplinary, drawing on both linguistics and computer science, and helps drive much contemporary work in text analysis (as used in computational social science, the digital humanities, and computational journalism). We will focus on major algorithms used in NLP for various applications (part-of-speech tagging, parsing, coreference resolution, machine translation) and on the linguistic phenomena those algorithms attempt to model. Students will implement algorithms and create linguistically annotated data on which those algorithms depend.

(In Fall 2017 this course was offered for 3 units.)

Prerequisites

COMPSCI 61B; COMPSCI 70, COMPSCI C100 / STAT C100 / DATA C100, MATH 55, STAT 134 or STAT C140 / DATA C140; strong programming skills.

Requirements Satisfied

MIMS: Technology Requirement
Ph.D. Breadth — Engineering and Design
Ph.D. Major/Minor Areas — Artificial Intelligence, Machine Learning, and Data Science
Ph.D. Major/Minor Areas — Information Organization and Retrieval
Ph.D. Major/Minor Areas — Information Systems Design
Applied Data Science Certificate — Elective
Last updated: October 17, 2024