New York University offers a Master of Science in Data Science through the Center for Data Science, with the degree administered by the Graduate School of Arts and Science.
The 36-credit program is taught in person in Manhattan and admits students once a year, in the fall. Machine Learning is a required course for every student. Deep learning, natural language processing, and large language model courses are electives, and students finish with a capstone project.
Last reviewed: October 2026
Quick Facts
| Degree | MS in Data Science |
| School | Center for Data Science, Graduate School of Arts and Science |
| Location | New York, New York |
| Format | Campus, full time or part time |
| Credits | 36 |
| Culminating Experience | Capstone project |
| Minimum GPA | None published |
| GRE | Optional |
| Application Deadline | February 12 (fall entry only) |
| Tuition | $2,426 per credit for 2026–27 |
| Typical Length | Two years full time |
Official MS in Data Science page
Curriculum
NYU does not offer a standalone master’s degree in machine learning or artificial intelligence. The MS in Data Science is the NYU master’s degree in which a machine learning course is required of all students. Computer science master’s degrees are offered separately by the Courant Institute and by the Tandon School of Engineering in Brooklyn.
Students complete 36 graduate credits consisting of:
- 15 credits of required courses, including a 3-credit capstone
- 3 credits of a Data Science elective
- 18 credits of other electives
Required courses must be taken for a letter grade.
Required Courses
- DS-GA 1001 – Introduction to Data Science
- DS-GA 1002 – Probability and Statistics for Data Science
- DS-GA 1003 – Machine Learning
- DS-GA 1004 – Big Data
- DS-GA 1006 – Capstone Project and Presentation
Data Science Elective
Students select one course from:
- DS-GA 1005 – Inference and Representation
- DS-GA 1008 – Deep Learning
- DS-GA 1011 – Fundamentals of Natural Language Processing
- DS-GA 1012 – Large Language Models: Evaluation and Applications
- DS-GA 1013 – Mathematical Tools for Data Science
- DS-GA 1014 – Optimization and Computational Linear Algebra
- DS-GA 1015 – Text as Data
- DS-GA 1016 – Computational Cognitive Modeling
- DS-GA 1017 – Responsible Data Science
- DS-GA 1018 – Probabilistic Time Series Analysis
- DS-GA 1020 – Mathematical Statistics
- DS-GA 1021 – Probability and Statistics 2
Deep Learning and the natural language processing courses are electives rather than required courses. Any course on this list that is not used for the Data Science elective can count toward the other 18 elective credits.
Other Electives
The remaining six courses can come from the list above, from other Center for Data Science courses, or from pre-approved courses in other NYU departments. Center for Data Science options include:
- DS-GA 1007 – Programming for Data Science
- DS-GA 1009 – Practical Training for Data Science
- DS-GA 1010 – Independent Study
- DS-GA 1019 – Advanced Python for Data Science
- DS-GA 3001 – Special Topics in Data Science
Special Topics offerings vary by semester. Examples listed by the center include Reinforcement Learning, Introduction to Computer Vision, Causal Inference in Machine Learning, and Mathematics of Deep Learning.
Industry Concentration and Tracks
Students can follow the Industry Concentration or a track. The Industry Concentration requires DS-GA 1009 and an internship within the first year, plus two electives from a Big Data list or a Natural Language Processing list. The Natural Language Processing list includes:
- DS-GA 1008 – Deep Learning
- DS-GA 1011 – Fundamentals of Natural Language Processing
- DS-GA 1012 – Large Language Models: Evaluation and Applications
- DS-GA 1015 – Text as Data
- CSCI-GA 2590 – Natural Language Processing
The Data Science track has three areas of interest: Big Data, Mathematics and Data, and Natural Language Processing. A separate Biomedical Informatics track is run with the medical school and ends in a biomedicine-based capstone. Concentration and track courses count toward the 36 credits.
Capstone Project
DS-GA 1006 runs for one semester in the final year. Students are matched with NYU research labs or industry partners and usually work in groups of two to four on a real-world problem.
Cost and Tuition
NYU is a private university and charges graduate tuition by the credit, with the same rate for New York residents and nonresidents.
For the 2026–27 academic year, the Bursar lists these rates for all Graduate School of Arts and Science programs:
| Category | Rate |
|---|---|
| Tuition per credit | $2,426 |
| Registration and services fee, per term | $503 |
| Registration and services fee, per credit | $81 |
At 36 credits, tuition comes to about $87,336 before fees. A full-time term of 9 credits is about $21,834 in tuition. The application fee for Data Science is $130.
The Center for Data Science offers a limited number of competitive tuition scholarships that cover part of tuition for up to two years. All applicants are considered automatically. Rates can change each year, so students should confirm current costs with the Bursar.
View NYU tuition and fee rates
Admission Requirements
Applicants need a bachelor’s degree and substantial mathematical preparation. NYU does not publish a minimum GPA for this program. The center reports an average GPA of 3.81 for its 2024 intake and describes admission as highly competitive.
Applicants must have completed these prerequisites, or equivalents:
- Calculus I
- Linear Algebra
- Introduction to Computer Science or an equivalent programming course
- one of Calculus II, Probability, Statistics, or an advanced physics, engineering, or econometrics course with heavy mathematical content
Serious experience with Python or R is generally expected. Prior exposure to machine learning, computational statistics, data mining, or operations research is preferred. Work experience is not required.
Application Materials
Applicants submit:
- Graduate School of Arts and Science online application and $130 application fee
- transcripts
- three letters of recommendation
- Statement of Academic Purpose of no more than two double-spaced pages
- proof of English proficiency when required
The GRE is optional, and the GMAT is not accepted. A Personal History Statement is also optional. For applicants who need an English test, the center recommends a TOEFL score of at least 100 or an IELTS band score of at least 7.0.
Application Deadlines
| Entry Term | Deadline |
|---|---|
| Fall | February 12 |
The program admits students for fall only and has no spring admission. Applications must be submitted online by 5 p.m. Eastern Time, and test scores must arrive by the deadline. The center does not approve deferrals, so admitted students who want to delay must reapply the following year.
Program Format
The MS in Data Science is taught in person at the Center for Data Science at 60 Fifth Avenue in Manhattan. It is not offered online.
Full-time students take 9 credits per semester and finish in four semesters. Part-time students take fewer than 9 credits, and the center advises students with full-time jobs to take 6 or fewer. All students must complete the degree within five years and stay enrolled each fall and spring.
Required courses are scheduled in the evening when possible, but this is not guaranteed. Electives are offered during the day and in the evening.
The center describes the program as STEM-eligible. International students can use Curricular Practical Training for paid internships for credit.
Who Is This Program Best For?
NYU’s MS in Data Science is a strong option for students with a quantitative background who want machine learning taught together with probability, statistics, and large-scale data systems in New York City.
It may be especially appealing to students interested in:
- machine learning as a required part of the degree
- deep learning and large language models
- natural language processing and text as data
- big data systems
- a first-year internship through the Industry Concentration
- a capstone with a research lab or industry partner
The program is in person only, starts only in the fall, and takes two years at a full-time pace. Deep learning and natural language processing are electives, the degree ends in a capstone, and tuition is charged at a private university rate. Students who want online study, spring entry, a shorter program, a degree focused only on artificial intelligence, or public university pricing may want to compare other New York schools.
Official New York University Program Links
- MS in Data Science program page
- Curriculum
- Industry Concentration
- NYU Bulletin entry
- Admissions requirements
- Graduate School of Arts and Science deadlines and requirements
- Admissions FAQ
- Tuition and fee rates
Related Machine Learning Programs in New York
Students can also compare New York University with other master’s programs in machine learning, artificial intelligence, and related fields offered in New York.
- Binghamton University – Binghamton
- City College of New York – New York
- Clarkson University – Potsdam
- Columbia University – New York
- Cornell University – Ithaca
- Fordham University – New York
- Hofstra University – Hempstead
- Long Island University – Brooklyn
- Manhattanville University – Purchase
- Marist University – Poughkeepsie
- Mercy University – Dobbs Ferry
- Pace University – New York
- Rensselaer Polytechnic Institute – Troy
- Rochester Institute of Technology – Rochester
- St. John’s University – Queens
- Stony Brook University – Stony Brook
- SUNY Buffalo State University – Buffalo
- SUNY New Paltz – New Paltz
- SUNY Oswego – Syracuse
- SUNY Polytechnic Institute – Utica
- Syracuse University – Syracuse
- University at Albany – Albany
- University at Buffalo – Buffalo
- University of Rochester – Rochester
- Utica University – Utica
- Yeshiva University – New York