Our networked world is generating a deluge of data that no human, or group of humans, can process fast enough. This data deluge has the potential to transform the way business, government, science and healthcare are carried out. But too few possess the skills needed to use automated analytical tools and cut through the noise to create knowledge from big data. NYU is changing that by offering academic programs that educate students in the theories, tools, and techniques used to create knowledge from data.


Featured Programs

The following programs feature data science as a foundational element of their curriculum:

NYU Center for Data Science

MS in Data Science

Students in the MS in Data Science must have a strong background in mathematics, computer science, and applied statistics. The degree focuses on development of new methods for data science. The curriculum is 36 credits, half of which are required courses and half of which are electives. Both 3-semester and 4-semester options are offered.

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Center for Urban Science and Progress (CUSP)

MS in Applied Urban Science and Informatics

Students must have a background in mathematics, science, or engineering. The degree focuses on application of big data analytics to urban programs. The curriculum is 30 credits in a 12-month program.

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NYU School of Engineering

MS in Computer Science

Besides our core curriculum in the fundamentals of computer science, you have a wealth of electives to choose from. You can focus on such topics as computer and network security, distributed systems and networking, computer graphics, and web search technology, along with subjects outside the department.

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PhD in Computer Science

Our current research strengths include: Cyber security, Analysis, management, and visualization of data, Computer games, Internet and Web research, and Computer science theory.

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NYU Department of Sociology

MA in Applied Quantitative Research (AQR)

Students must have successfully completed at least one undergraduate statistics or research methods course. The degree focuses on development of a strong foundation in the statistical tools and theoretical perspectives used in the social sciences. The curriculum is 32 credits in a 12-month program.

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NYU Stern School of Business

MBA with a Specialization in Business Analytics

Students are selected based on their combined academic profile, professional achievements, aspirations and personal characteristics. The degree develops people and ideas to transform the challenges of the 21st century into opportunities to create value for business and society. The curriculum is 60 credits over 2 years.

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MS in Business Analytics

Students are required to have a strong record of professional achievement over at least five years of experience and, in addition, successful completion of quantitative undergraduate coursework. The degree equips graduates with the ability to transform data into a powerful and predictive strategic asset, so as to influence decision-making, strategy, and drive better business results. The curriculum is broken into five intensive modules typically spread out over 12 months that rotate between NYU Stern School of Business in NY and NYU Shanghai campus in Shanghai.

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MS in Applied Statistics for Social Science Research (A3SR)

This is a flexible-credit program that provides students with rigorous training in statistical research techniques and their applications in contemporary social, behavioral, and health science research. Strong candidates will enter with some background in math, statistics or computer science.  The program allows students to learn highly marketable data science skills needed to address important social issues.

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NYU Langone Medical Center

PhD in Biostatistics

Biostatistics is a scientific discipline that focuses on study design and collection, analysis, and interpretation of data to improve human health. The Division of Biostatistics is the academic home of faculty who contribute to scientific advances that benefit human health through innovation in methodology, theory, and application of biostatistical methods across the entire spectrum of biomedical research.

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