Industry Concentration

CDS offers the Industry Concentration for the MS in Data Science. This concentration is specifically targeted to respond to the needs and inputs from companies and allows MS in Data Science students to apply the knowledge and skills obtained in their coursework to industry during the degree program. It requires more industry-targeted coursework and a Practical Training experience. This concentration has a required internship within the first year of study. International students should consult NYU’s Office of Global Services on how to obtain early CPT status within their first year if in this concentration. 

Data Science is one of the fastest growing fields in the world. Companies need professionals with skills that can help them make better business decisions, and students looking for a career in Data Science have the opportunity to graduate from one of the world’s most prestigious universities. Nyu Data Science Masters focuses on hands-on training in data science fundamentals and provides you with both academic theory and practical skills needed to succeed in this field.

Students in this concentration will be required to take the following courses for the degree as a part of the 36 credit requirement:

• DS-GA 1009 Practical Training for Data Science within the first year of the program (3 credits in fall, spring, or summer)
• 2 electives within the Big Data or Natural Language Processing subject areas (6 credits, see below for more details).

The courses below fall within the Big Data subject area. This list is approved and reviewed annually by the curriculum committee.

• DS-GA 1012: Natural Language Understanding and Computational Semantics
• CS-GY 6313: Information Visualization
• CS-GY 6323 Large-Scale Visual Analytics
• CS-GY 6083 Principles of Database Systems (Engineering School)
• CSCI-GA 2433 Database Systems (Courant Computer Science)
• CS-GY 6093: Advanced Database Systems (Engineering School) 
• CSCI-GA 2434 Advanced Database Systems (Courant Computer Science)

The courses below fall within the Natural Language Processing subject area. This list is approved and reviewed annually by the curriculum committee.

• DS-GA 1011 Natural Language Processing with Representation Learning
• DS-GA 1012 Natural Language Understanding and Computational Semantics
• CSCI-GA 3033 Statistical NLP
• DS-GA 1005 Inference and Representation
• DS-GA 1008 / CSCI-GA 2572 Deep Learning
• DS-GA 1015 Text as Data
• CSCI-GA 2590 Natural Language Processing

TUITION & FEES

The Graduate School of Arts and Science charges tuition on a per-point basis. A student must complete 72 points for the Ph.D. degree and 32-44 points for the master’s degree, depending on the program. A full-time course load is typically 12 points per semester, 24 points per year.

Please refer to the Bursar’s web page for detailed information on tuition and fee rates, methods of payment, and other financial matters.

The Board of Trustees of New York University reserves the right to alter this schedule of fees without notice. All fees must be paid per term at the time of registration in the Office of the Bursar, located at 383 Lafayette Street. Checks and drafts should be drawn to the order of New York University in the exact amount of the tuition and fees required. In the case of overpayment, the balance is refunded upon request by filing a refund application in the Office of the Bursar.

NYU Admission Requirements

Fall 2022 MS Application Now Open! Deadline to apply is January 22, 2022!

The MS Information Session is taking place Tuesday October 26th from 10:00am-11:00am EST.

Please see the “Ready to Apply” section below for more information:

Overview

Admission to NYU’s Master of Science in Data Science is extremely competitive. This speaks both to the popularity of the field of Data Science and to the very high calibre of students who we seek as part of our program.

Without exception, you must submit the following to support your application for admission:

• GRE scores
• TOEFL or IELTS; however, TOEFL is preferred (Required for all applicants whose native language is not English and who have not received a university degree in an English-speaking country)
• Official college transcripts
• Three letters of recommendation (we prefer all letters on letterhead)
• Statement of Academic Purpose

For more information, visit the graduate schools application resource center.

Below, we provide more details about our expectations.

Educational Prerequisites

Successful applicants to the MSDS come from many different undergraduate backgrounds, including degrees in Statistics, Computer Science, Mathematics, Engineering, Economics, Business, Biology, Physics and Psychology. In the 2021 intake cycle, the average GPA was 3.87. Our students’ transcripts usually include As and Bs (only), and we expect stronger grades in more relevant subject matter (see below) from those coming from less selective institutions. Regardless of degree, we require specific and substantial knowledge of certain mathematical competencies, and some training in programming and basic computer science.

To be considered for the program, you will be required to have completed the following (or equivalents):

• Calculus I: limits, derivatives, series, integrals, etc.
• Linear Algebra
• Intro to Computer Science (or an equivalent “CS-101” programming course): We have no set requirements as regards specific languages, but we generally expect serious academic and/or professional experience with Python and/or R at a minimum.
• 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.

Work Experience

Many of our students join us directly from undergraduate, but we also very much welcome evidence of relevant work experience—and clear employment goals once the MSDS is completed—in data science.  Past experience and career aspiration goals can be related to commercial industry, government, academia or some other sector.

Standardized Tests

We require that students submit standardized tests scores for the GRE. There are no exceptions: we do not accept “out of date” scores; nor do we accept scores of other, similar tests; nor do we allow waivers (regardless of previous educational attainment or circumstance).  

In addition to sending your official scores to the Graduate School of Arts and Science please upload a PDF of the unofficial scores, which are made available upon completion of your test, to the “Additional Information Section” of your application.

We wish to emphasize that we have no set minimums for the GREs, and we consider the totality of an application when making a decision about admission. Nonetheless, to the extent that it is helpful to give applicants a sense of things, what follows are the averages for the current cohort of MSDS students:

• Average GRE Verbal: 159.3 (80th percentile)
• Average GRE Quantitative: 167.4 (90th percentile)
• Average GRE Analytical: 4.14 (61st percentile)
• Average TOEFL (where required): 111

We also require evidence of proficiency with English as a second language for certain students who must provide it. For those students, we generally require a TOEFL score of at least 100 overall (and have strong preferences for better scores), and per university guidelines, will not admit those falling below that threshold.

For additional information regarding standardized testing please visit the Graduate School of Arts and Science’s FAQ Page.

Three Letters of Recommendation

Recommendations for admitted students are invariably excellent, with references holding applicants in the highest esteem relative to other students or employees with whom they have interacted in the past several years. References from professors or employers who can comment directly and in a detailed way on the applicant’s case, aptitude for, and attitude to data science projects are treated with the most weight. Though not required, we prefer all letters on letterhead.

For additional information regarding letters of recommendation please visit the Graduate School of Arts and Science’s FAQ Page.

Internal Transfers/Current NYU Students

We do not allow internal transfers from other NYU graduate programs. If you are a current NYU graduate student and you would like to be a part of the NYU Data Science MS program, please note that you are required to submit a new application.

Ready to Apply?

If your background meets the majority of these requirements, and you have a desire to develop the methods to harness the potential of data, then we encourage you to begin the application process. Please proceed to the Graduate School of Arts and Science online application to apply for admission. The Fall 2022 application deadline is January 22, 2022 at 5pm EST.

Prior to starting your application please review the Graduate School of Arts and Science’s general application policies page.

For more questions, email us at datascience-group@nyu.edu.

Deferral Requests

The Center for Data Science will not approve a request for deferral of admission. If an admitted student wishes to delay enrollment, it will be necessary to turn down the offer of admission and reapply for admission the following year. A completely new application will be required. The new application will be considered along with all other applications at that later time. Please email Kathryn Angeles at kangeles@nyu.edu with questions.