Data Science

Updated on August 7th. 2026

1. BUSF-SHU 101 Statistics for Business and Economics: BUSF-SHU 101 Statistics for Business and Economics can satisfy the data science major requirements. This ONLY applies to students who started their studies before Fall 2026. For students who started in Fall 2026 or after Fall 2026, BUSF-SHU 101 no longer fulfills the data science major requirements.

2. CSCI-SHU 360 Machine Learning (Refer to Requirements for the Business Tracks)

Students who plan to pursue a double major in Data Science and Business majors with Business Analytics Track, cannot use CSCI-SHU 360 Machine Learning to fulfill Business majors Non-finance/non-marketing elective requirements. 

Please note one course can only be used for two purposes. In this case, CSCI-SHU 360 Machine Learning will be used for the following three purposes, which is not permitted. 1) Business majors: Non-finance/non-marketing elective 2) Business majors:  Business Analytics track requirement 3) Data Science major: Data Analysis requirement 

Note: CSCI-SHU 360 Machine Learning can only fulfill the non-finance elective requirement if students pursue a BA track under a Business major. 

3. Starting in Fall 2026, CSCI-SHU 101 Introduction to Computer Science and Data Science (ICDS) has been renamed to CSCI-SHU 101 Introduction to Computer Science, and a new course, DATS-SHU 201 Introduction to Data Science, has been added. This course will replace the requirement of econometrics for DS majors.

CSCI-SHU 101 Introduction to Computer Science

• Prerequisite: CSCI-SHU 11 Introduction to Computer Programming or placement exam

• Fulfillment: Core AT, CS Required, DS Foundational, CSE Required, ESE Required, and IMB Emerging Media Foundation Course

DATS-SHU 101 Introduction to Data Science

• Prerequisite: CSCI-SHU 11 or placement exam and MATH-SHU 235 or MATH-SHU 238

• Fulfillment: Core AT, DS Foundational, and CS elective

4. Beginning Fall 2026, the Data Science major curriculum has been updated (please refer to the AY 2026-2027 academic bulletin). Students who began their studies at NYU Shanghai before Fall 2026 may choose to follow either the new curriculum or the previous bulletin requirements, whether pursuing Data Science as a primary or secondary major.

Data Science draws from methodologies and tools in several well established fields, including computer science, statistics, applied mathematics, and economics. Data science has applications in just about every academic discipline, including sociology, political science, digital humanities, linguistics, finance, marketing, urban informatics, medical informatics, genomics, image content analysis, and all branches of engineering and the physical sciences.  The importance of data science is expected to accelerate in the coming years, as data from the web, mobile sensors, smartphones, and Internet-connected instruments continues to grow.

What knowledge and skills will students acquire by majoring in Data Science?

Students who complete the major will not only have expertise in computer programming, statistics, and data mining, but also know how to combine these tools to solve contemporary problems in a discipline of their choice, including the social science, physical science, and engineering disciplines. 

What are post-graduation and career opportunities for Data Science students?

Upon graduation, data science majors have numerous career paths. You can go on to graduate school in data science, computer science, social science, business, finance, medicine, law, linguistics, education, and so on. Outside of academe, there are also myriad career paths. Not only can you pursue careers with traditional data-driven computer-science companies and startups such as Google, Facebook, Amazon, and Microsoft, but also with companies in the transportation, energy, medical, and financial sectors. You can also pursue careers in the public sector, including urban planning, law enforcement, and education.

Some NYU Shanghai Data Science courses –such as Machine Learning– integrate Kiwi (see instructions), an AI-driven learning platform developed by a research group at NYU Shanghai. NYU Shanghai students enrolled in these courses can review lecture slides and interact with AI for a personalized learning experience. To access Kiwi, please complete the request form.

Data Science Double Major Guidelines

Students who are interested in pursuing a Data Science major along with a Business major, an Economics major, a Mathematics major, a Neural Science or a Social Science major have the option to double-count more than two courses between the majors. To complete both majors successfully, students would need to complete course requirements for both majors. However, the following courses are allowed to be double counted toward both majors:

Data Science (Concentration in Finance) and Business & Finance
• BUSF-SHU 101 Statistics for Business and Economics
• BUSF-SHU 202 Foundations of Finance
• BUSF-SHU 250 Principles of Financial Accounting
• BUSF-SHU 303 Corporate Finance
• ECON-SHU 3 Microeconomics

Note:  For students who matriculated in Fall 2026 or later, BUSF-SHU 101 no longer fulfills the Data Science major requirements and cannot be double-counted toward both majors.

Data Science (Concentration in Marketing) and Business & Marketing
• BUSF-SHU 101 Statistics for Business and Economics
• BUSF-SHU 202 Foundations of Finance
• BUSF-SHU 250 Principles of Financial Accounting
• ECON-SHU 3 Microeconomics
• MKTG-SHU 1 Intro to Marketing

Note:  For students who matriculated in Fall 2026 or later, BUSF-SHU 101 no longer fulfills the Data Science major requirements and cannot be double-counted toward both majors.

Data Science (Concentration in Economics) and Economics
• ECON-SHU 1 Principles of Macroeconomics
• ECON-SHU 3 Microeconomics
• ECON-SHU 301 Econometrics
• MATH-SHU 140 Linear Algebra
• MATH-SHU 151 Multivariable Calculus
• MATH-SHU 235 Probability and Statistics OR BUSF-SHU 101 Statistics for Business and Economics

Note: Students who take both Linear Algebra and Multivariable Calculus can substitute Mathematics for Economists (Advanced Economics Elective) with these two courses. If the student chooses this option, they would need to take one Additional approved quantitative economics course. MATH-SHU 140 Linear Algebra and MATH-SHU 151 Multivariable Calculus can no longer satisfy Economics major requirements for students admitted in Fall 2026 or later.

Data Science (Concentration in Finance) and Economics
• ECON-SHU 3 Microeconomics
• MATH-SHU 140 Linear Algebra
• MATH-SHU 151 Multivariable Calculus
• MATH-SHU 235 Probability and Statistics OR BUSF-SHU 101 Statistics for Business and Economics

Note: Students who take both Linear Algebra and Multivariable Calculus can substitute Mathematics for Economists (Advanced Economics Elective) with these two courses. If the student chooses this option, they would need to take one Additional approved quantitative economics course. MATH-SHU 140 Linear Algebra and MATH-SHU 151 Multivariable Calculus can no longer satisfy Economics major requirements for students admitted in Fall 2026 or later.
 

Data Science (Concentration in Finance) and Mathematics
• MATH-SHU 140 Linear Algebra
• MATH-SHU 151 Multivariable Calculus
• MATH-SHU 235 Probability and Statistics OR MATH-SHU 238 Honors Theory of Probability

Data Science (Concentration in Mathematics) and Math
• MATH-SHU 140 Linear Algebra
• MATH-SHU 151 Multivariable Calculus
• MATH-SHU 201 Honors Calculus
• MATH-SHU 235 Probability and Statistics OR MATH-SHU 238 Honors Theory of Probability
• MATH-SHU 329 Honors Analysis II OR MATH-SHU 142 Honors Linear Algebra II

Data Science (Concentration in Mathematics) and Honors Math
• MATH-SHU 141 Honors Linear Algebra I
• MATH-SHU 142 Honors Linear Algebra II
• MATH-SHU 238 Honors Theory of Probability
• MATH-SHU 329 Honors Analysis II

Data Science (Concentration in Political Science) and Social Science (Political Science Track)
• SOCS-SHU 150 Introduction to Comparative Politics
• SOCS-SHU 160 Introduction to International Politics
• MATH-SHU 235 Probability and Statistics OR BUSF-SHU 101 Statistics for Business and Economics

Data Science (Concentration in Psychology) and Social Science (Psychology Track)
• PSYC-SHU 101 Introduction to Psychology
• MATH-SHU 235 Probability and Statistics OR BUSF-SHU 101 Statistics for Business and Economics
• SOCS-SHU 350 Empirical Research Practice
• Choose One:
SOCS-SHU 334 Legal Psychology OR PSYC-SHU 234 Developmental Psychology OR PSYC-SHU 352 Psychology of Human Sexuality

Data Science (Concentration in Genomics) and Neural Science
• MATH-SHU 140 Linear Algebra
• MATH-SHU 235 Probability and Statistics
• BIOL-SHU 21 Foundations of Biology I
• BIOL-SHU 22 Foundations of Biology II
• BIOL-SHU 123 Foundations of Biology Lab

Data Science (Concentration in Genomics) and Biology
• MATH-SHU 140 Linear Algebra
• MATH-SHU 235 Probability and Statistics
• BIOL-SHU 21 Foundations of Biology I
• BIOL-SHU 22 Foundations of Biology II
• BIOL-SHU 123 Foundations of Biology Lab
• BIOL-SHU 261 Genomics and Bioinformatics

Note for Data Science (Concentration in Genomics) and Neural Science & Data Science (Concentration
in Genomics) and Biology: Students who take Linear Algebra and Probability and Statistics are not
allowed to take the lower-level Math Tools for Life Science course. Students who have not decided yet to
pursue a double major and take Math Tools for Life Science first are required to take Linear Algebra and
Probability and Statistics.

Note: Computer Science and Data Science share many courses, so double-majoring is not allowed. However,
students in Data Science can minor in Computer Science (and vice versa).

Double Major Sample Plans:

• Sample plans (Academic bulletin: 2022-2023)
• Sample plans (Academic bulletin: 2019-2020; 2020-2021; 2021-2022)
• Sample plans (Academic bulletin: 2018-2019)

Declare your secondary major:

• Students need to complete more than half of the courses required for the primary and secondary majors.
• Students should present their four-year plan that demonstrates they can complete all degree requirements to their academic advisor for review.  Create your four-year plan now!

• Center for Data Science and Artificial Intelligence
• Deans' Undergraduate Research Fund (DURF)
• CS, DS, and Engineering Research Night
• Bring your programming and data analysis skills to professors’ ongoing research projects!

Does not satisfy the major requirement. Students majoring in data science are permitted to work on an individual basis under the supervision of a full-time faculty member in the relevant discipline if they have maintained an overall GPA of 3.0 and a GPA of 3.5 in data science and have a study proposal that is approved by the faculty and an academic area head.

Study Away Considerations

• Courses: Before studying abroad, students are recommended to complete Introduction to Computer Science and Data Science, Data Structures, Econometrics, Probability and Statistics, Multivariable Calculus, and Machine Learning. Students who wish to study in New York ideally complete Databases.
• Location: Students planning to study away for two semesters are strongly encouraged to spend the first semester in a location other than New York. Applicants who spend the first semester away in another location will receive priority consideration for New York in their second semester away. Students who elect to spend the spring of their junior year in New York (versus the fall of the junior year) will have more earned credit points, which will enable them to have an earlier registration time and have a better chance of enrolling in high-demand courses.
• Senior Capstone: Students should not plan to study away during senior fall due to the in-person DS Senior Capstone course offering

Study Away Course Registration

Refer to the Fall 2023 Computer Science Pre-requisites and Equivalents for course inforamtion. Please note that students must follow the prerequisites of the school hosting the course. For example, if Shanghai does not require a course for Class X, but New York does, then you will need to have that required course.

Python vs Java

In Shanghai, there are three course sequence ICP, ICDS, Data Structures (all taught in Python). At NYU CAS, there are the same three course sequence but teach ICS and Data Structures in Java. At Tandon, their three-course sequence is ICP, Data Structure, Object Oriented Programming. ICP and Data Structures is taught in Python,  OOP in Java.  

As an NYU Shanghai CS and Data Science major, students can take ICS or Data Structures in Python or Java. However:

• If you are a DS major, we highly recommend you take both ICS and Data Structures in Python. Python is by far the most prominent language in data science, and several of our upper-level DS courses are taught in Python. But if it is difficult to get into a Python class, then you can take these courses in Java.
• For CS majors, either Java or Python is fine. But you should be warned that if you take ICS in Java and then return to NYU Shanghai, you’ll be taking Data Structures in Python, and may be at a disadvantage to those who took ICS in Python.
• All students should be warned that if they take  ICS  in Python, and then take Data Structures in NY in Java, they may be at a disadvantage since this would be their first course using Java, whereas most NY students will already have had ICS in Java. 

In order to comply with accreditation requirements, NYU Shanghai requires all students to complete either a capstone requirement in the form of a senior thesis and/or a required capstone course in the primary major. 

Starting in Fall 2026, the capstone requirement for students pursuing DS as their primary major will be restructured into two options:

Regular Capstone (Course-Extension Option)

• Students will take an additional elective course with a final project and final paper before senior Spring semester as the major pre-capstone course. This course must be taken in Shanghai. DS primary majors may only take courses from the list below that are marked “Yes” in the “Can Be Extended to Capstone” column to fulfill capstone requirements. (See list here).
• Students will enroll in a 0-credit capstone course as a placeholder in the senior Spring semester.
• By enrolling in the 0-credit capstone course, students will extend the final project/paper from the approved pre-capstone course into a more substantial capstone paper and submit it in senior Spring to fulfill the major capstone requirement.

Advanced Capstone (Research-Oriented)

• 4-credit course offered in the Fall semester of senior year
• Application required (details will be shared via email every April/May)
• Enrollment is limited and based on selection

Students who plan to declare Data Science as a secondary major will be required to take a DS capstone equivalent course to substitute for the DS major 4-credit capstone course requirement (courses from study away sites that have been approved as course equivalents to the listed Shanghai electives may also be used as substitutes for the capstone). 

Library Resources：

• NYU Shanghai Library
• NYU Libraries Research Guides
• Writing and Stylistic Guides

Quick Links：

• Academic Resource Center
• Research and Conference
• Dean’s Undergraduate Research Fund
• Global Awards and Fellowships