Aesthetics and Data [Data Science Connector]

When we organize and visualize data, we make it meaningful and communicative. But in so doing, we also give it a form—an aesthetic shape—that did not previously exist. In this course, we will consider aesthetics as a crucial, but often overlooked, component of data science. Our goal will be to develop the basic aesthetic literacy needed to critically consider the ways we present information. The course contains two interrelated units: first, we will study the vocabulary that 20th-century art critics developed to talk about the sensory, emotional, and political qualities of art.

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Calculating Americans: Big Histories of Small Data

The data we collect both reflects our values and shapes them, constraining and defining the questions we ask about our society. This course will use a series of case studies from the history of American data to examine a wide array of political, economic, and cultural issues. We will explore the ways that categories, units of analysis, and practices of instruction and collection both reflect and reshape assumptions about race, gender, labor, and household structure.

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Digital Worlds: An Introduction to Geospatial Technologies

An introduction to the increasingly diverse range of geospatial technologies and tools including but not limited to geographical information systems (GIS). Via a mix of lecture and lab-based instruction, students will develop knowledge and skills in web-mapping and GIS. How these tools are used to represent fundamental geographic concepts, and the wider socioeconomic context of these technologies will also be explored.

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How Does History Count?

In this connector course, we will explore how historical data becomes historical evidence and how recent technological advances affect long-established practices, such as close attention to historical context and contingency. Will the advent of fast computing and big data make history “count” more or lead to unprecedented insights into the study of change over time? During our weekly discussions, we will apply what we learn in lectures and labs to the analysis of selected historical sources and get an understanding of constructing historical datasets.

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Mapping Diasporas: Jewish Culture, Museums, and Digital Humanities

 

How do we “map” culture in motion?

Describing the interaction of places, times, languages, identities, cultural formats, dominant and marginal narratives that characterize cultures in diaspora requires a multidimensionality that traditional maps no longer meet.

In today’s world, we “map” diasporas through digital narratives , and often perform culture as archivists and curators.

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Natural Language Processing

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).

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Sound and Music Computing with CNMAT Technologies

Explores the intersection of music and computers using a combination of scientific, technological, and artistic methodologies. Musical concerns within a computational frame are addressed through the acquisition of basic programming skills for the creation and control of digital sound. Will learn core concepts and techniques of computerbased music composition using the Cycling74/MaxMSP programming environment in combination with associated software tools and programming approaches created by the Center for New Music and Audio Technologies.

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