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The deadline to apply for Fall 2018 is June 1.
 


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Welcome to the M.S. Program in Data Analysis and Visualization

Lev Manovich / Cultural Analytics Lab

WHY OUR PROGRAM?

WHY OUR PROGRAM?

Data — its production, curation, analysis, and visualization — impacts every area of modern society. More and more of our everyday decisions are guided by computational processing of big data. Computers recommend what route should we take, what news should we read, whom we should follow on social networks, and what music we should listen to. Our program allows students to better understand how data operates in society and how it can be curated and presented.

WHAT YOU WILL STUDY

AREAS OF STUDY

We offer three areas of study: data analysis, data visualization, and data studies. Across all of these classes, we move from fundamental concepts and methods to more advanced methods. We focus on analyzing real-world datasets and creating effective and engaging visualizations. Coursework will help students understand longer historical trends that drive the adoption of computers, networks, and data analysis in a society, and this will help them to anticipate future trends. Graduates will be able to work in the industry (data analysis, data and information visualization) or to pursue doctoral studies in a range of related disciplines.

A UNIQUE APPROACH

A UNIQUE APPROACH

We combine data analysis and visualization — two practices closely aligned in practice but rarely taught together. We help students gain practical skills in working with data and the theoretical skills to anticipate the future use of data in society, and to understand the possibilities, implications, and limitations of data.

TAKE ADVANTAGE OF NYC

STUDY IN NEW YORK CITY

We are located in the middle of New York City (Fifth Avenue and 34th Street) so students can also learn from the rich cultural and intellectual offerings of New York City, and apply for internships and jobs in leading companies in many fields.

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Photo credit, clockwise from top left: Rachel Ramirez (1, 3).