Spring course descriptions

During Add-Drop period, take a look at the undergraduate course offerings related to digital humanities. Some of these courses offer the opportunity to develop technical skill sets applicable to digital humanities research in computer science and linguistics, while others probe into the media-dominated era we live in that allowed for the rise of digital humanities as a discipline. All of the following courses are eligible as electives for the digital track of the Humanities certificate program ( https://humstudies.princeton.edu/certificate/#plan).

COS 424: Fundamentals of Machine Learning, Xiaoyan Li and Barbara Engelhardt

This course examines different theoretical and practical approaches to analyzing large data sets. The skills developed can be applied to digital humanities research, as well as many business-related and scientific problems.


COS 401: Introduction to Machine Translation, Srinivas Bangalore

This course combines computational and linguistic perspectives on machine translation with hands-on projects for implementing speech and text translation components.


COS 435: Information Retrieval, Discovery and Delivery, Andrea S. LaPaugh

A complementary course to the Fundamentals of Machine Learning, this course examines methods for gathering, organizing and searching through large digital collections. The course looks at the applications of these methods to social networks and multimedia collections.


ANT 347: Anthropology of Media, Jeffrey D. Himpele

This course examines the relationships between media, social forces and cultural values. Student-directed projects make use of media through digital humanities-friendly tools such as data visualization and mapping.


GER 517: Modernism and Modernity – Digital Cultures, Claus Pias

This course examines the rise of digital culture, and the impact of new media on cultural domains.


LIN 201: Introduction to Language and Linguistics – Laura Kalin

This survey of the fundamental areas of linguistics offers a useful baseline for digital textual analysis.


LIN 355: Field Methods in Linguistics, Florian A. Lionnet

Expanding upon the basics of LIN 201, this course delves into the practices of linguistic fieldwork. The course focuses on practical linguistic data collection using recording equipment, linguistic analysis software, and metadata archiving.


SML 201: Introduction to Data Science, Yan Huang

Incorporating machine learning, statistics, and computing, this course looks at data as a research tool. The course covers data gathering and exploring, as well as creating tools based on such data.


AMS 331: The Artist-Citizen: Socially Engaged Art in the 21st Century, Katie Pearl

Looking at artists that bring communities and networks closer through performance, this course offers the option of multimedia projects and final performances.


COM 402: Radical Poetics, Radical Translation, Karen R. Emmerich

This course looks at translations of poetry that challenge the limits of what is translatable, and offers students the opportunity to complete their own creative projects.


SOC 204: Social Networks, Matthew J. Salganik

The first half of this course covers central theories on network formation and spread, while the second half examines applications and examples of everything from online filter bubbles to the HIV/AIDS epidemic.


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