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- I am interested in the Data Science Master's program, who should I contact?
- I am an international student, who should I contact if I have an inquiry?
- What makes the Data Science major different from other majors such as Computer Science, ITI, Statistics, etc?
- How can I find more about research or independent study opportunities in Data Science in the summer?
- How can I get an SPN (special permission number) for Computer Science courses in the Data Science programs?
- I submited an SPN request via the Computer Science SPN system, and was offered a section but I'd like to switch to a different section. Can you assist me in this matter?
- How is the capstone course 01:198:310 different from other courses?
- Do I need to submit an SPN request to register for the capstone course 01:198:310?
- I registered for my last foundational course next semester. Can I take the capstone course at the same time?
- How can I get a pre-requisite override?
- Does 01:960:401 Basic Statistics for Research fulfill the same requirement as 01:960:291 Statistical Inference for Data Science or 01:960:212 Statistics II?
- I came across Data Science Bootcamp at Rutgers. Are these similar programs?
- I am still taking one foundational course, so technically, I haven’t fulfilled the requirements to take capstone 01:198:310. '...'
- I was unable to attend the open house. Where can I find a recording, if any?
- I am an incoming transfer student from the Rutgers-Newark campus. While at RU-N, I completed a few classes for the Data Science minor. Are the credits transferable/satisfy any of the required courses for the Data Science minor at RU-NB?
- I want to take a course at a community college. Do I need to get preapproval for transfer credits for courses taken outside RU-NB?
- Can I take more than one foundational course simultaneously?
- I need to take two classes at the same time regardless of the overlapping times. Who should I contact?
- How can I make an appointment with a Data Science advisor?
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- Two New Data Science Degrees at Rutgers-New Brunswick
- From “Moneyball” to Medicine, Data Science is Emerging as Hot New Field
- Data Science Student among the 2025 Recipients of the SAS Outstanding Service Award
- Data Science Student 18-Year-Old Senior Is Rutgers’ Youngest 2025 Graduate
- Prospective Students
- Data Science Courses
- 01:160:342 Physical Chemistry: Biochemical Systems
- 01:160:348 Instrumental Analysis
- 01:160:351 Inorganic Chemistry
- 01:160:352 Inorganic Chemistry IIA
- 01:160:353 Inorganic Chemistry IIB
- 01:160:438 Introduction to Computational Chemistry
- 01:198:111 Introduction to Computer Science
- 01:198:112 Data Structures
- 01:198:142 Data 101: Data Literacy
- 01:198:205 Intro to Discrete Structures I
- 01:198:206 Intro to Discrete Structures II
- 01:198:210 Data Management for Data Science
- 01:198:310 Data Science Capstone Project
- 01:198:336 Principles of Information and Data Management
- 01:198:439 Introduction to Data Science
- 01:198:461 Machine Learning Principles
- 01:198:462 Introduction to Deep Learning
- 01:220:102 Intro to Microeconomics
- 01:160:159 General Chemistry for Engineers
- 01:160:161 General Chemistry
- 01:160:163 Honors General Chemistry
- 01:160:165 Extended General Chemistry
- 01:160:171 Introduction to Experimentation
- 01:160:251 Analytical Chemistry
- 01:160:308 Organic Chemistry
- 01:160:309 Organic Chemistry Laboratory
- 01:160:315 Honors Organic Chemistry
- 01:160:327 Physical Chemistry
- 01:160:328 Physical Chemistry
- 01:160:341 Physical Chemistry: Biochemical Systems
- 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
- 01:220:423 Advanced Time Series and Financial Econometrics
- 01:220:424 Machine Learning for Economics
- 01:359:207 Data and Culture
- 01:447:303 Computational Genetics for Big Data
- 01:450:321 Geographic Information Systems
- 01:450:330 Geographical Research methods
- 01:640:135 Calculus I
- 01:640:136 Calculus II
- 01:640:151 Calculus I
- 01:640:152 Calculus II
- 01:640:250 Introductory Linear Algebra
- 01:694:407 Molecular Biology and Biochemistry
- 01:750:345 Computational Astrophysics
- 01:920:360 Computational Social Science
- 01:960:142 Data 101: Data Literacy
- 01:960:212 Statistics II
- 01:960:291 Statistical Inference for Data Science
- 01:960:295 Data Management and Wrangling with R
- 01:960:365 Introduction to Bayesian Data Analysis
- 01:960:384 Intermediate Statistical Analysis
- 01:960:463 Regression Methods
- 01:960:467 Applied Multivariate Analysis
- 01:960:486 Applied Statistical Learning
- 01:960:490 Introduction to Experimental Design
- 04:189:103 Information Technology and Informatics
- 04:189:220 Data in Context
- 04:547:201 Information Technology Fundamentals
- 04:547:221 Fundamentals of Data Curation and Management
- 04:547:321 Information Visualization
- 01:160:TBD Chemical Data Science and Machine Learning Applications
- 11:115:403 General Biochemistry I
- 11:126:485 Functional Genomics
- 14:332:443 Machine Learning for Engineers
- 33:136:385 Statistical Methods in Business
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