Visit department's website: cds.nyu.edu
Room 1220, 715 Broadway, New York, NY 10003 • 212-998-3283
Professor S.R.S. Varadhan
DIRECTOR OF GRADUATE STUDIES:
Professor Juliana Freire
The program facilities are currently housed in the Center for Data Science. The Center offers a large open area concept plus private areas for study, research, collaboration and presentations. The Center for Data Science will move to a new space specifically designed to facilitate data science discussion and research by 2016. Data science graduates are also provided educational and research computing resources through a network of servers and desktop workstations running Linux and Solaris. In addition, individual research groups have various resources, including a variety of Linux and Windows PCs. Access to the Internet is provided through a T3 connection. Each doctoral student is provided with a personal desktop or laptop. Many other research machines provide for abundant access to a variety of computer architectures. For example, research groups in graphics, multimedia, vision, and motion capture have video and editing facilities, a unique motion-capture laboratory, and access to related facilities at the Tisch School of the Arts. The bioinformatics group has a cluster of fast PCs for computing whole genome sequencing and mapping. The distributed computing group manages a dedicated cluster of PCs and workstations for experiments in robust distributed systems. The Center for Data Science maintains a set of servers for use by students in its courses and for research projects in the center.
Master of Science
Admission to the Master of Science in Data Science requires substantial but specific mathematical competencies, typical of a major in mathematics, statistics, engineering, physics, theoretical economics, and computer science with sufficient mathematical training. In addition, applicants should have some training in programming and basic computer science. To be considered for the program, applicants will be required to have taken: Calculus I, Linear Algebra, Introduction to Computer Science (or equivalent programming course), one of Calculus II, Probability, Statistics or an advanced physics, engineering, or econometrics course with heavy mathematical content. Preference is given to applicants with prior exposure to machine learning, computational statistics, data mining, large-scale scientific computing, operations research (either in an academic or professional context), as well as to applicants with significantly more mathematical and/or computer science training than the minimum requirements listed above. Applicants must submit the following to support your application for admission: GRE scores, TOEFL (All applicants whose native language is not English and who have not received a university degree in an English-speaking country), official college transcripts, and three letters of recommendation.