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Fall 2018 Quantitative Methods: Social Sciences GR5067 section 001

Call Number 68461
Day & Time
M 8:10pm-10:00pm
270B International Affairs Building
Points 4
Approvals Required None
Instructor Wayne Lee
Course Description Social scientists need to engage with natural language processing (NLP) approaches that are found in computer science, engineering, AI, tech and in industry. This course will provide an overview of natural language processing as it is applied in a number of domains. The goal is to gain familiarity with a number of critical topics and techniques that use text as data, and then to see how those NLP techniques can be used to produce social science research and insights. This course will be hands-on, with several large-scale exercises. The course will start with an introduction to Python and associated key NLP packages and github. The course will then cover topics like language modeling; part of speech tagging; parsing; information extraction; tokenizing; topic modeling; machine translation; sentiment analysis; summarization; supervised machine learning; and hidden Markov models. Prerequisites are basic probability and statistics, basic linear algebra and calculus. The course will use Python, and so if students have programmed in at least one software language, that will make it easier to keep up with the course.
Web Site Vergil
Department Graduate School of Arts and Sciences
Enrollment 25 students (30 max) as of 11:58PM Monday, December 17, 2018
Subject Quantitative Methods: Social Sciences
Number GR5067
Section 001
Division Graduate School of Arts and Sciences
Open To School of the Arts, Graduate School of Arts and Science, International and Public Affairs, Engineering and Applied Science: Graduate, School of Professional Studies
Campus Morningside
Note QMSS MA Students Priority
Section key 20183QMSS5067G001

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SIS update 12/17/18 23:58    web update 12/18/18 15:05