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Natural Language Processing
Course Title
Natural Language Processing
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.
Minimum
4
Maximum
4
Grading Basis
Default Letter Grade; P/NP Option
Method of Assessment
Written Exam
Instructors
Bamman
American Cultures Requirement
No
Reading and Composition Requirement
None of the Reading and Composition Requirement
Requirements
Prerequisite
COMPSCI 61B; COMPSCI 70, COMPSCI C100 / STAT C100 / DATA C100, MATH 55, STAT 134 or STAT C140 / DATA C140; strong programming skills.
Repeat Rules
Course is not repeatable for credit.
Credit Restriction Courses. Students will receive no credit for this course if the following the course(s) have already been completed.
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Formats
Lecture
Term
Fall and Spring
Duration (in weeks)
15
Minimum Hours
3
Maximum Hours
3
Outside Work Hours Min
9
Maximum Hours
9