Data Science (BA)
Program Description
The Data Science major provides rigorous training in statistical modeling, machine learning, and data driven reasoning, grounded in computer science and mathematics. Students develop both theoretical understanding and practical skills in programming, data analysis, and modern statistical methods. The curriculum prepares students to design, analyze, and deploy data-driven systems, with attention to ethical considerations and the distinction between causal inference and prediction. Reflecting the interdisciplinary nature of the field, students pair the major with a CAS minor to apply data science methods across domains.
Students may contact cds-undergraduate@nyu.edu with questions.
Honors Program
This major program of study does not currently offer an honors track.
Admissions
New York University's Office of Undergraduate Admissions supports the application process for all undergraduate programs at NYU. For additional information about undergraduate admissions, including application requirements, see How to Apply.
Program Requirements
The major in Data Science requires thirteen 4-credit courses (52 credits) as outlined below. It also requires completion of a CAS minor (applicable only to students pursuing Data Science as a single major and not as part of a joint or double major).
| Course | Title | Credits |
|---|---|---|
| General Education Requirements | ||
| First-Year Seminar | 4 | |
| EXPOS-UA 1 | Writing as Inquiry | 4 |
| Foreign Language | 16 | |
| Physical Science | 4 | |
| Life Science | 4 | |
| Texts and Ideas | 4 | |
| Cultures and Contexts | 4 | |
| Societies and the Social Sciences | 4 | |
| Expressive Culture | 4 | |
| Major Requirements | ||
| Data Science Courses | ||
| DS-UA 111 | Principles of Data Science I (offered every semester) | 4 |
| DS-UA 112 | Principles of Data Science II (offered every semester) | 4 |
| DS-UA 201 | Causal Inference (offered every semester) | 4 |
| DS-UA 202 | Responsible Data Science (offered every spring) | 4 |
| Computer Science Courses | ||
| CSCI-UA 101 | Intro to Computer Science | 4 |
| CSCI-UA 102 | Data Structures | 4 |
| CSCI-UA 473 | Fundamentals of Machine Learning | 4 |
| CSCI-UA 479 | Data Management and Analysis | 4 |
| Mathematics Courses | ||
| Select one of the following: | 4 | |
| Calculus I | ||
| Mathematics for Economics I | ||
| Select one of the following: | 4 | |
| Calculus II | ||
| Mathematics for Economics II | ||
| Select one of the following: | 4 | |
| Calculus III | ||
| Mathematics for Economics III | ||
| MATH-UA 140 | Linear Algebra | 4 |
| or MATH-UA 148 | Honors Linear Algebra | |
| MATH-UA 185 | Probability & Statistics | 4 |
| Advanced Elective Requirement | ||
| Select one of the following: | 4 | |
| Machine Learning for Climate Change | ||
| Advanced Topics in Data Science | ||
| Natural Language Processing | ||
| CAS Minor Requirements | ||
| Complete 16 credits in any CAS minor | 16 | |
| Electives | ||
| Other Elective Credits | 8 | |
| Total Credits | 128 | |
Sample Plan of Study
| 1st Semester/Term | Credits | |
|---|---|---|
| CSCI-UA 2 | Introduction to Computer Programming (No Prior Experience) (Prerequisite for CSCI-UA 101 if students cannot otherwise place into that course; does not count toward the major) | 4 |
| Select one of the following: | 4 | |
| Calculus I | ||
| Mathematics for Economics I | ||
| First-Year Seminar | 4 | |
| Texts and Ideas | 4 | |
| Credits | 16 | |
| 2nd Semester/Term | ||
| CSCI-UA 101 | Intro to Computer Science | 4 |
| EXPOS-UA 1 | Writing as Inquiry | 4 |
| Cultures and Contexts | 4 | |
| Select one of the following: | 4 | |
| Calculus II | ||
| Mathematics for Economics II | ||
| Credits | 16 | |
| 3rd Semester/Term | ||
| DS-UA 111 | Principles of Data Science I | 4 |
| CSCI-UA 102 | Data Structures | 4 |
| Select one of the following: | 4 | |
| Calculus III | ||
| Mathematics for Economics III | ||
| Foreign Language | 4 | |
| Credits | 16 | |
| 4th Semester/Term | ||
| DS-UA 112 | Principles of Data Science II | 4 |
| MATH-UA 185 | Probability & Statistics | 4 |
| CAS Minor Requirement | 4 | |
| Foreign Language | 4 | |
| Credits | 16 | |
| 5th Semester/Term | ||
| CSCI-UA 479 | Data Management and Analysis | 4 |
| DS-UA 201 | Causal Inference | 4 |
| CAS Minor Requirement | 4 | |
| Foreign Language | 4 | |
| Credits | 16 | |
| 6th Semester/Term | ||
| MATH-UA 140 | Linear Algebra | 4 |
| Foreign Language | 4 | |
| Societies and the Social Sciences | 4 | |
| CAS minor requirement | 4 | |
| Credits | 16 | |
| 7th Semester/Term | ||
| CSCI-UA 473 | Fundamentals of Machine Learning | 4 |
| CAS Minor Requirement | 4 | |
| Physical Science | 4 | |
| Expressive Culture | 4 | |
| Credits | 16 | |
| 8th Semester/Term | ||
| DS-UA 202 | Responsible Data Science | 4 |
| DS-UA 301 | Advanced Topics in Data Science | 4 |
| Life Science | 4 | |
| Other Elective Credits | 4 | |
| Credits | 16 | |
| Total Credits | 128 | |
Learning Outcomes
Upon completion of program requirements, students are expected to:
- Achieve a rigorous understanding of the mathematical, statistical, and computational principles that underpin data science, so that students will have the foundational mastery to pursue of the many applications of data sciences without limitation.
- Understand approaches such as causal inference, machine learning, and data management that are involved in different settings across varied academic and applied contexts.
- Examine the relationship between data science and society by addressing ethical and philosophical issues in modern statistics, data science, and AI, and develop the ability not only to design data models but also to communicate effectively about these models and their outputs.
Policies
Program Policies
Policy on Declaration of Major
Students must complete DS-UA 111 Principles of Data Science I with a grade of C or better before declaring the major in Data Science. This policy applies to all NYU students, not just to those matriculated in CAS.
Students may declare at any time during the academic year using the links below. Any questions or concerns regarding the declaration process should be directed to cds-undergraduate@nyu.edu.
- Data Science Major or Minor
- Joint Major in Computer and Data Science (all NYU students must complete both DS-UA 111 Principles of Data Science I and CSCI-UA 101 Introduction to Computer Science with a grade of C or better before declaring this major)
- Joint Major in Data Science and Mathematics
College of Arts and Science students cannot enter their junior year undeclared and must begin their Data Science (and, if applicable, Computer Science) course sequence no later than the spring semester of their sophomore year, which will allow them to declare the major or minor during the summer before their junior year. The Center for Data Science (CDS) and CAS both advise that students begin their Data Science courses earlier and declare the major in the spring of their sophomore year. Although students may begin their Data Science courses later than this point, there is no guarantee they will finish their major requirements in time to graduate within four years. Students cannot declare any major or joint major with CDS after completion of their junior year.
Other Policies Applying to the Major
- A grade of C or better is necessary in all courses used to fulfill major requirements; courses graded Pass/Fail do not count toward the major.
- Two courses may be double-counted between the Data Science major and another major or another minor (not both).
- The stand-alone major in Data Science requires completion of any minor in CAS (the minor in Computer Science is now accepted for this, as well as the minor in Public Health which is the only permissible non-CAS minor). Students who choose the minor in Computer Science, the joint minor in Mathematics and Computer Science, or the minor in Mathematics may double-count no more than two courses between their chosen minor and the major in Data Science and might need to take additional courses for their minor due to overlap with this major. These students cannot double-count any other courses between the Data Science major and a second major or a second minor.
- Note on the sample plan of study tab: CSCI-UA 2 is listed in the first term of study for students who may need to take it but it does not count toward the major. It is a prerequisite to CSCI-UA 101, which is required for this major. Students can also place into CSCI-UA 101 with a qualifying AP score or by taking a placement examination in the Department of Computer Science.
- Advanced Placement credit (or other advanced standing credit by examination) in Computer Science and Calculus is treated exactly as in the majors and minors in Computer Science and Mathematics. Consult the AP and other tables in the admission section of this Bulletin for course equivalencies.
- Students must check the prerequisites for each course before enrolling.
- CAS students (in any major or minor) are not permitted to take computer science courses in the Tandon School of Engineering.
- Those interested in spending a semester away should work out their schedule with an adviser as early as possible.
NYU Policies
University-wide policies can be found on the New York University Policy pages.
College of Arts and Science Policies
A full list of relevant academic policies can be found on the CAS Academic Policies page.