The Bachelor of Science in Data Science at Rutgers provides students with a foundation in data literacy, statistical inference, and data management. The program includes courses in calculus, linear algebra, and principles of information and data management. The program has three tracks: Computer Science, Economics, and Chemical Data Science. The Computer Science track includes courses in calculus and computer science, with a deep emphasis on Machine Learning and Artificial Intelligence. The Economics track includes courses in microeconomics and macroeconomics, as well as other advanced economics courses. The Chemical Data Science track is designed to prepare students for advanced studies in chemistry, data science, and chemical data science, in addition to enabling them to move directly into the chemical industry, or advanced studies in these areas.
Students must complete the Foundational courses and choose from one of the BS degree options, along with completing the SAS CORE requirements.
There is no precedence order except for the normal prerequisites for the courses. Information is subject to change. Please consult advisors.
Foundational Courses
- 01:198:142/01:960:142 Data 101: Data Literacy
- 01:960:291 Statistical Inference for Data Science [The 01:960:291. Statistical Inference for Data Science requirement has been expanded to include any of the following: 01:960:212 Statistics II, OR 01:960:384 Intermediate Statistical Analysis (Formerly 960:380), OR 33:136:385 Statistical Methods in Business.]
- Data Management Courses (Choose one):
- 01:640:135/01:640:151 Calculus I*
- 01:640:250 Introductory Linear Algebra
- 04:189:220 Data in Context**
* Computer Science Track and Chemical Data Science Track must take Math 151.
** Update to Data in Context Course Code (30.3.2026)
With the release of the Schedule of Classes, Data in Context is now officially listed under the course code 04:547:225. If you previously completed this requirement under the former course code 04:189:220, you do NOT need to retake the course, your requirement has already been fulfilled. We also anticipate that this course will be offered in the summer. At this time, the course code for the summer offering has not yet been confirmed. Additional updates will be shared as soon as more information becomes available. If you have any questions, please contact the Data Science team at
- New Data in Context Course Code (30.3.2026): With the release of the Schedule of Classes, Data in Context is now officially listed under the course code 04:547:225. If you previously completed this requirement under the former course code 04:189:220, you do NOT need to retake the course, your requirement has already been fulfilled. We also anticipate that this course will be offered in the summer. At this time, the course code for the summer offering has not yet been confirmed. Additional updates will be shared as soon as more information becomes available. If you have any questions, please contact the Data Science team at .
- Important Update: Data Science Major Declaration Change (as of Feb. 26, 2025)
We are excited to announce an important update regarding the prerequisites for declaring the Data Science major! Effective immediately, students can declare the Data Science Major after the successful completion of Data101 and Statistical Inference courses only. The Data Management course is no longer required to declare the Data Science major, but it is still a requirement for the DS degree completion. We understand that the previous requirement may have posed challenges for some students, and we believe this update will encourage more students to pursue their academic goals without unnecessary barriers. We are committed to supporting your educational journey and ensuring you have the best opportunities to succeed. - As of December 2023, the 01:960:291. Statistical Inference for Data Science requirement has been expanded to include any of the following: 01:960:212 Statistics II, OR 01:960:384 Intermediate Statistical Analysis (Formerly 960:380), OR 33:136:385 Statistical Methods in Business.
- The 01:198:336 Principles of Information and Data Management requirement has been dropped for the Statistics, Economics, and Societal Impact tracks of the Data Science major but retained for the Computer Science track.
- We're excited to announce a new track within the BS in Data Science program! Starting in Fall 2024, students can pursue the Chemical Data Science track. This interdisciplinary program, housed within the Rutgers-New Brunswick (RU-NB) School of Arts and Sciences (SAS), is offered jointly by the Department of Computer Science (CS), the Department of Statistics (Stat), and the Department of Chemistry and Chemical Biology (CCB). The Chemical Data Science Bachelor of Science (BS) track is designed to equip students with expertise in chemical science, technical skills, critical thinking, and communication. It also covers essential areas such as computation, statistical inference, and data management. To learn more about the new track, please view the webpage and email us at if you have any questions.
BS in Data Science- Computer Science Track (Code: NB219SJ)
- 01:198:336 Principles of Information and Data Management [01:198:336 - Principles of Information and Data Management requirement has been dropped for the Statistics, Economics, and Societal Impact tracks of the Data Science major but retained for the Computer Science track.]
- 01:640:152 Calculus II
- 01:640:251 Multivariable Calculus
- 01:198:111 Introduction to Computer Science
- 01:198:112 Data Structures
- 01:198:205 Intro to Discrete Structures I
- 01:198:206 Intro to Discrete Structures II
- 01:198:439 Introduction to Data Science
- 01:198:461 Machine Learning Principles or, 01:198:462 Introduction to Deep Learning
- 01:960:463 Regression Methods
- 01:960:486 Applied Statistical Learning
- 04:547:321 Information Visualization
Note: While 01:640:135 fulfills the Calculus requirement, students in the Computer Science and Chemical Data Science tracks are strongly encouraged to take 01:640:151, as transitioning from 01:640:135 to 01:640:152 may require additional preparation.
BS in Data Science- Economics Track (Code: NB219EJ)
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- 01:640:136/152 Calculus II
- 04:547:321 Information Visualization
- 01:220:102 Intro to Microeconomics
- 01:220:103 Intro to Macroeconomics
- 01:220:320 Intermediate Microeconomics Analysis
- 01:220:321 Intermediate Macroeconomic Analysis
- 01:220:322 Econometrics
- 01:220:421 Economic Forecasting and Big Data
- 01:220:422 Advanced Econometrics for Microeconomic Data or, 01:220:423 Advanced Time Series and Financial Econometrics
- 01:220:424 Machine Learning for Economics
BS in Data Science- Chemical Data Science Track (Code: NB219CJ)
- 01:640:152 Calculus II
- 01:198:111 Introduction to Computer Science
- 01:160:171 Introduction to Experimentation
- 01:960:365 Introduction to Bayesian Data Analysis OR 01:960:463 Regression Methods
- 01:160:487/542 Special Topics in Physical Chemistry: Chemical Data Science
- Choose one of the following four courses:
- Choose one of the following four courses:
- Choose one of the following two courses:
- Choose one of the following two courses:
- Choose at least 9 credits of the following nine courses:
- 01:160:251 Analytical Chemistry (3)
- 01:160:309 Organic Chemistry Laboratory (2.5)
- 01:160:348 Instrumental Analysis (3)
- 01:160:351 Inorganic Chemistry (3)
- 01:160:352 Inorganic Chemistry IIA (7-week course) (1.5)
- 01:160:353 Inorganic Chemistry IIB (7-week course) (1.5)
- Either 01:160:327 Physical Chemistry (4) OR 01:160:341 Physical Chemistry: Biochemical Systems (3) **
- Either 01:160:328 Physical Chemistry (4) OR 01:160:342 Physical Chemistry: Biochemical Systems (3) OR 01:160:438 Introduction to Computational Chemistry (3)**
- Either 01:694:407 Molecular Biology and Biochemistry (3) OR 11:115:403 General Biochemistry I (4)**
- ** Students cannot select both courses to fulfill the 9 credits; they are only allowed to choose one.
New Capstone Course for BS in Data Science, Chemical Data Science Track – Spring 2026
The Chemistry Department is offering a new Chemical Data Science (CDS) capstone course in Spring 2026: CHEM 487/542, Special Topics in Physical Chemistry: Chemical Data Science. The course will be taught by Professor Chong Sun. This capstone is designed specifically for students pursuing BS in Data Science, Chemical Data Science track. The course introduces the fundamentals of data science and AI/ML, with an emphasis on applications in chemistry, biology, and materials science. The course combines lectures and hands-on sessions. Lectures provide foundational knowledge applicable across a wide range of scientific problems, while hands-on sessions focus on practical applications, such as chemical reaction prediction, drug discovery, and materials design, etc. By completing this course, students will develop practical AI/ML skills, complete a capstone project in Chemical Data Science, and be prepared for future research or industrial applications involving data science in areas such as inorganic and organic chemistry, biochemistry, medical science, and materials science.
Students who are interested or who have questions about the course are encouraged to contact Professor Sun directly at .
Note: While 01:640:135 fulfills the Calculus requirement, students in the Computer Science and Chemical Data Science tracks are strongly encouraged to take 01:640:151, as transitioning from 01:640:135 to 01:640:152 may require additional preparation.
Curriculum Sheets (BS in Data Science)
BS- Chemical Data Science Track
Declaration of Major
Requirements: To declare the Data Science Major, students must successfully complete these two foundational courses: Data 101 and Statistical Inference (or one of its equivalents).
School of Arts and Science (SAS) & School of Communication and Information (SC&I) students can add Data Science to MyMajor https://mymajor.sas.rutgers.edu
Other Rutgers- New Brunswick Students (non-SAS) students: For students in other schools, it is essential to complete the required forms corresponding to your school to officially include the Data Science major in your academic journey. Here are the links to the respective forms:
- School of Environmental and Biological Science (SEBS): Students must complete the SEBS form to request a non-SEBS second major to declare the major: https://sebs.wufoo.com/forms/declaration-for-2nd-nonsebs-major/
- School of Engineering (SOE): https://soe.rutgers.edu/academic-advising-and-policies/forms
- Rutgers Business School (RBS): https://forms.office.com/r/90QXFCd1UB