Data Science

Data Science at NYU Shanghai is designed to create data-driven leaders with a global perspective, a broad education, and the capacity to think creatively. Data science involves using computerized methods to analyze massive amounts of data and to extract knowledge from them. Data science addresses a wide-range of data types, including scientific and economic numerical data, textual data, and image and video data. This new discipline 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.

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. 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.

Degree Requirements – 2017-18 Bulletin

* = offered in Fall ’18 in Shanghai

Prerequisite Courses
CSCI-SHU 101 Introduction to Computer Science* Pre-req: ICP or placement exam
Choose one Statistics course from the following four
MATH-SHU 235 Probability and Statistics* Pre-req: Calculus
MATH-SHU 233 Honors Theory of Probability* Pre-reqs: “Honors Analysis 1” and “Linear Algebra or Honors Linear Algebra 1” 
BUSF-SHU 101 Statistics for Business and Economics*  
BIOL-SHU 42 Biostatistics  

Note: SOCS-SHU 210 Statistics for the Behavioral Sciences does not count towards this requirement.

Programming/Computer Science Courses
CSCI-SHU 210 Data Structures* Pre-req: ICS, or A in ICP, or A- in ICP and enrolled in ICS concurrent to Data Structures
Math Courses
MATH-SHU 123 OR ECON-SHU 5 / ECON-SHU 201 Multivariable Calculus* OR Math for Economists (2 credits or 4 credits)
MATH-SHU 140 OR MATH-SHU 265 OR MATH-SHU 141 Linear Algebra* OR Linear Algebra and Differential Equations* OR Honors Linear Algebra I*
Data Analysis Courses




The Mathematics of Statistics and Data Science*

Pre-req: a prior Stats course

Pre-reqs: Multivariable Calculus, Linear Algebra, and a prior Stats course

CSCI-SHU 360 Machine Learning* Pre-req: a prior Stats course
CSCI-SHU 235 OR INTM-SHU 230-002 Information Visualization OR Generative Language (Note: This course was offered in Fall 2017. Future course offering is dependent on faculty availability.)

Pre-req: Data Structures

Pre-req: None

Data Management Course
CSCI-SHU 213 / CS-UY 3083 Databases* Pre-req: ICS
Concentration Courses
2 domain-area courses
Senior project or another domain-area course

Note: For a concentration in Finance, students need to take all four courses listed below.

Concentration Options
Domain-Area Courses for Concentration in Finance
ECON-SHU 3 Microeconomics*
BUSF-SHU 250 Principles of Financial Accounting*
BUSF-SHU 202 Foundations of Finance*
BUSF-SHU 303 Corporate Finance*
No senior project required. 13 courses total.
Domain-Area Courses for Concentration in Economics
ECON-SHU 3 Microeconomics*
ECON-SHU 1 Macroeconomics*
Senior project or approved quantitative economics course (see course list here, scroll down to "Concentration in Economics courses" section)
Students can take Math for Economists (2 credits or 4 credits) en lieu of Multivariable Calculus.

6 economics courses in program. 12 courses total.

Domain-Area Courses for Concentration in Genomics
BIOL-SHU 21 Foundations of Biology 1 and lab
BIOL-SHU 22 Foundations of Biology 2 and lab*
BIOL-SHU 261 Bioinformatics*
  Senior Project

Foundations of Biology 1 can count as core curriculum course. 12 courses total.

Domain-Area Courses for Concentration in Computer Science
CSCI-SHU 420 Senior Project
Two courses from:
CENG-SHU 202 OR CSCI-UA 201 Computer Architecture OR Computer Systems Organization
CSCI-SHU 215 Operating Systems*
CSCI-SHU 2314 Discrete Mathematics*
CS-UY 2413 / CSCI-UA 310 / CSCI-SHU 220 Algorithms

12 courses total.

Domain-Area Courses for Concentration in Mathematics
Three approved math courses in addition to Multivariable Calculus and Linear Algebra. (See approved math course list here, scroll down to "Concentration in Mathematics courses" section.)
Students who wish to take honors math courses could take:
MATH-SHU 201 Honors Calculus*
MATH-SHU 328 Honors Analysis 1
MATH-SHU 329 Honors Analysis 2*
MATH-SHU 141 Honors Linear Algebra 1*
MATH-SHU 142 Honors Linear Algebra 2
  Senior Project

12 courses total.

Domain-Area Courses for Concentration in Artificial Intelligence
  Senior Project
Two courses from:
CSCI-UA 480 Natural Language Processing
CSCI-SHU 372 / CS-UY 4613 Artificial Intelligence
  Advanced Topics in Machine Learning

12 courses total.

Domain-Area Courses for Concentration in Social Science
Three courses from:
ECON-SHU 3 Microeconomics*
PSYC-SHU 101 Introduction to Psychology*
SOCS-SHU 150 Introduction to Comparative Politics
SOCS-SHU 160 Introduction to International Politics*
SOCS-SHU 141 Methods of Social Research
ECON-SHU 213 Causal Inference in the Social Sciences
SOCS-SHU 318 Ethnographic Methods

12 courses total.

Double Majors

If you are interested in pursuing a Data Science major along with an Economics major, a Computer Science major, a Business major, or a Mathematics major, these are the relevant guidelines:

  • The course requirements need to be satisfied in both majors.
  • More than two courses may be double-counted between the majors but each major must have at least 7 singly-counted courses.
  • The double major must be approved by the faculty and Deans responsible for the two majors. Students should first work with their academic advisor to initiate this process.
  • Double-counted courses cannot also be counted for the core curriculum requirements since each course can only count for at most two requirements.


You can view sample plans on how a major in Data Science and an Economics major, a Computer Science major, a Business major, or a Mathematics major may be completed HERE.

Recommended Fall 2018 Courses

Recommended Fall 2018 Courses for Rising Sophomores

  1. Perspectives on the Humanities
  2. Introduction to Programming / Introduction to Computer Science / Data Structures
  3. Math (Multivariable Calculus, Linear Algebra, or Linear Algebra and Differential Equations) or Statistics course
  4. Chinese Language Course / English for Academic Purposes
Faculty Mentors

Prof. Keith Ross, Dean of Engineering and Computer Science Office: 1415 | Email: | Profile


Prof. Yuxin Chen, Dean of Business Office: 1124 | Email: | Profile

Minor in Data Science: 5 courses
CSCI-SHU 101 Introduction to Computer Science*
CSCI-SHU 210 Data Structures*




The Mathematics of Statistics and Data Science*

CSCI-SHU 360 Machine Learning*
One Statistics course from the following four
MATH-SHU 235 Probability and Statistics*
BUSF-SHU 101 Statistics for Business and Economics*
MATH-SHU 233 Honors Theory of Probability*
BIOL-SHU 42 Biostatistics
Note: Computer Science majors should additionally take Information Visualization OR Databases to earn at least 12 unique credits for the minor.
Undergraduate Research