Data Science Major
Students must also complete the Undergraduate Registration Requirement and the degree requirements of their home school.
NOTE: This Catalog describes Weinberg College BA requirements that pertain to students who matriculated at Northwestern after spring quarter 2023. Refer to the Archives if you are following BA requirements described in the 2018-2019 through 2022-2023 editions.
Requirements for the Data Science Major
- Department Courses (11 units)
- Related Courses (may be double-counted with another major, or with a minor)
- Related courses in mathematics (units vary). MUST be taken EARLY in the program of study; includes prerequisite courses for required department courses.
- Related courses in technical and domain science electives (2 units)
- Related ethics course (1 unit)
For details see course lists, below.
Department Courses
| Course | Title |
|---|---|
| Department Courses (see course descriptions for prerequisites in mathematics) | |
| 4 foundational courses: | |
| Introduction to Programming for Data Science 2 | |
| Introduction to Computer Programming | |
(students who do not take STAT 201-0 are responsible for independently learning content not covered in alternative course) 1 | |
| Introduction to Statistics and Data Science 2 | |
or STAT 210-0 | Introduction to Probability and Statistics |
or STAT 232-0 | Applied Statistics |
or approved introductory statistics course from another department 2 | |
| Statistical Theory & Methods 1 2 | |
or STAT 383-0 | Probability and Statistics for ISP |
or MATH 310-1 | Probability and Stochastic Processes |
or MATH 311-1 | MENU: Probability and Stochastic Processes |
or MATH 314-0 | Probability and Statistics for Econometrics |
or MATH 385-0 | Probability and Statistics for MMSS |
| Probabilistic Systems | |
or IEMS 302-0 | Probability |
(students who do not take STAT 320-1 are responsible for independently learning content not covered in alternative course) 1 | |
| Statistical Theory & Methods 2 | |
| 6 data science core courses: | |
| Data Science 1 with R and Data Science 2 with R and Data Science 3 with R | |
or | |
| Data Science 1 with Python and Data Science 2 with Python and Data Science 3 with Python | |
NOTE! Students may receive credit for only one Data Science sequence: either Data Science with R (301 sequence), or Data Science with Python (303 sequence) | |
| Data Structures and Algorithms for Data Science 2 | |
| Data Structures & Algorithms | |
| Information Management for Data Science 2 | |
| Data Management & Information Processing | |
| Advanced Machine Learning for Data Science | |
| 1 capstone experience course: | |
| Data Science Project | |
- 1
Lists of topics not covered in substitute courses can be found on the department website.
- 2
No more than 3 substitutions for STAT courses permitted
Related Course Requirement
Three types of related courses are required.
Related Courses - mathematics
Mathematics courses (units depend on mathematics sequence taken). MUST be taken EARLY in the program of study; includes prerequisite courses for required department courses.
| Course | Title |
|---|---|
| See course descriptions for prerequisite sequencing of mathematics related courses | |
| Single-Variable Differential Calculus and Single-Variable Integral Calculus | |
| Single-Variable Calculus with Precalculus and Single-Variable Calculus with Precalculus and Single-Variable Calculus with Precalculus | |
| Multivariable Differential Calculus | |
or MATH 228-1 | Multivariable Differential Calculus for Engineering |
or MATH 281-1 | Accelerated Mathematics for ISP: First Year |
or MATH 285-2 | Accelerated Mathematics for MMSS |
or MATH 290-2 | MENU: Linear Algebra and Multivariable Calculus |
or MATH 291-2 | MENU: Intensive Linear Algebra and Multivariable Calculus |
| Honors Calculus for Engineers | |
| Sequences and Series and Multivariable Integral Calculus | |
or STAT 228-0 | Series and Multiple Integrals |
or MATH 235-0 | Series and Multiple Integrals |
| Sequences and Series and Multivariable Integral Calculus for Engineering | |
| Sequences and Series and Accelerated Mathematics for ISP: First Year | |
| Sequences and Series and Accelerated Mathematics for MMSS | |
| Sequences and Series and MENU: Linear Algebra and Multivariable Calculus | |
| Sequences and Series and MENU: Intensive Linear Algebra and Multivariable Calculus | |
| Sequences and Series and Honors Calculus for Engineers | |
| Linear Algebra | |
or MATH 281-3 | Accelerated Mathematics for ISP: First Year |
or MATH 285-1 | Accelerated Mathematics for MMSS |
or MATH 290-1 | MENU: Linear Algebra and Multivariable Calculus |
or MATH 291-1 | MENU: Intensive Linear Algebra and Multivariable Calculus |
| Engineering Analysis I | |
| Honor Engineering Analysis | |
Related Courses - technical and domain science electives (students choose 2 courses; may be from different subject areas)
For updates please refer to department website list of Technical and Domain Science Electives. Some courses may have prerequisites; check course descriptions for details.
Anthropology
| Course | Title |
|---|---|
| ANTHRO 322-0 | Introduction to Archaeology Research Design & Methods |
| ANTHRO 324-0 | Archaeological Survey Methods |
| ANTHRO 362-0 | Advanced Methods in Quantitative Analysis |
| ANTHRO 389-0 | Ethnographic Methods and Analysis |
Biological Sciences
| Course | Title |
|---|---|
| BIOL_SCI 323-0 | Bioinformatics: Sequence and Structure Analysis |
| BIOL_SCI 338-0 | Modeling Biological Dynamics |
| BIOL_SCI 341-0 | Population Genetics |
| BIOL_SCI 378-0 | Functional Genomics |
Biomedical Engineering
| Course | Title |
|---|---|
| BMD_ENG 311-0 | Computational Genomics |
| BMD_ENG 312-0 | Biomedical Applications in Machine Learning |
Chemical Engineering
| Course | Title |
|---|---|
| CHEM_ENG 379-0 | Computational Biology: Analysis and Design of Living Systems |
| CHEM_ENG 367-0 | Quantitative Methods in Life Cycle Analysis |
Cognitive Science
| Course | Title |
|---|---|
| COG_SCI 345-0 | Presenting Ideas & Data |
Communication Studies
| Course | Title |
|---|---|
| COMM_ST 352-0 | Social Network Analysis |
| COMM_ST 355-0 | Audience Analysis |
| COMM_ST 358-0 | Algorithms and Society |
| COMM_ST 371-0 | Cultural Analytics |
Computer Engineering
| Course | Title |
|---|---|
| COMP_ENG 329-0 | The Art of Multicore Concurrent Programming |
| COMP_ENG 358-0 | Introduction to Parallel Computing |
| COMP_ENG 365-0 | Internet-of-things Sensors, Systems, And Applications |
| COMP_ENG 368-0 | Programming Massively Parallel Processors with CUDA |
Computer Science
| Course | Title |
|---|---|
| COMP_SCI 325-0 | Artificial Intelligence Programming |
| COMP_SCI 331-0 | Introduction to Computational Photography |
| COMP_SCI 333-0 | Interactive Information Visualization |
| COMP_SCI 336-0 | Design & Analysis of Algorithms |
| COMP_SCI 337-0 | Natural Language Processing: Classical Approaches |
| COMP_SCI 339-0 | Introduction to Database Systems |
| COMP_SCI 341-0 | Social Networks Analysis |
| COMP_SCI 348-0 | Introduction to Artificial Intelligence |
| COMP_SCI 352-0 | Machine Perception of Music & Audio |
Earth and Planetary Science
| Course | Title |
|---|---|
| EARTH 323-0 | Seismology and Earth Structure |
| EARTH 327-0 | Geophysical Time Series Analysis |
| EARTH 340-0 | Physics of Weather & Climate |
| EARTH 343-0 | Earth System Modeling |
| EARTH 353-0 | Mathematical Inverse Methods in Earth and Environmental Sciences |
| EARTH 360-0 | Instrumentation and Field Methods |
| EARTH 361-0 | Scientific Programming in Python |
Economics
| Course | Title |
|---|---|
| ECON 307-0 | Economics of Medical Care |
| ECON 308-0 | Money and Banking |
| ECON 316-0 | Advanced Topics in Macroeconomics |
| ECON 325-0 | Economic Growth & Development |
| ECON 326-0 | The Economics of Developing Countries |
| ECON 327-0 | Economic Development in Africa |
| ECON 336-0 | Analytic Methods for Public Policy Analysis |
| ECON 337-0 | Economics of State and Local Governments |
| ECON 339-0 | Labor Economics |
| ECON 340-0 | Economics of the Family |
| ECON 341-0 | Economics of Education |
| ECON 342-0 | Economics of Gender |
| ECON 349-0 | Industrial Economics |
| ECON 350-0 | Monopoly Competition & Public Policy |
| ECON 351-0 | Law and Economics |
| ECON 354-0 | Issues in Urban and Regional Economics |
| ECON 355-0 | Transportation Economics and Public Policy |
| ECON 358-0 | Economics of Art and Culture |
| ECON 359-0 | Economics of Nonprofit Organizations |
| ECON 360-1 | Foundations of Corporate Finance Theory |
| ECON 360-2 | Investments |
| ECON 361-0 | International Trade |
| ECON 362-0 | International Finance |
| ECON 371-0 | Economics of Energy |
| ECON 372-0 | Environmental Economics |
| or ECON 373-0 | Natural Resource Economics |
| ECON 381-1 | Econometrics |
| ECON 381-2 | Econometrics |
| ECON 383-0 | Applied Econometrics |
Electrical Engineering
| Course | Title |
|---|---|
| ELEC_ENG 328-0 | Information Theory & Learning |
| ELEC_ENG 331-0 | Introduction to Computational Photography |
| ELEC_ENG 332-0 | Introduction to Computer Vision |
| ELEC_ENG 335-0 | Deep Learning Foundations from Scratch |
| ELEC_ENG 373-0 | Deep Reinforcement Learning |
| ELEC_ENG 375-0 | Machine Learning: Foundations, Applications, and Algorithms |
Engineering Sciences and Applied Mathematics
| Course | Title |
|---|---|
| ES_APPM 346-0 | Modeling and Computation in Science & Engineering |
| ES_APPM 370-1 | Introduction to Computational Neuroscience |
| ES_APPM 375-1 | Quantitative Biology I: Experiments, Data, Models, and Analysis |
| ES_APPM 375-2 | Quantitative Biology II: Experiments, Data, Models, and Analysis |
Global Health
| Course | Title |
|---|---|
| GBL_HLTH 303-0 | (Re)mixing Qualitative Methods |
| GBL_HLTH 320-0 | Qualitative Research Methods in Global Health |
Industrial Engineering and Management Sciences
| Course | Title |
|---|---|
| IEMS 308-0 | Data Science and Analytics |
| IEMS 313-0 | Foundations of Optimization |
| IEMS 315-0 | Stochastic Models |
| IEMS 317-0 | Discrete Event Systems Simulation |
| IEMS 340-0 | Qualitative Methods in Engineering Systems |
| IEMS 341-0 | Social Networks Analysis |
| IEMS 351-0 | Optimization Methods in Data Science |
Integrated Marketing and Journalism
| Course | Title |
|---|---|
| IMC 302-0 | Research and Data Analytics |
| IMC 307-0 | Digital, Social and Mobile Marketing |
| JOUR 377-0 | Introduction to Data Journalism |
| JOUR 342-2 | Knight Lab: Artificial Intelligence in Media |
Linguistics
| Course | Title |
|---|---|
| LING 334-0 | Introduction to Computational Linguistics |
Mathematics
| Course | Title |
|---|---|
| MATH 306-0 | Combinatorics & Discrete Mathematics |
| MATH 308-0 | Graph Theory |
| MATH 310-2 | Probability and Stochastic Processes |
| MATH 310-3 | Probability and Stochastic Processes |
| MATH 311-2 | MENU: Probability and Stochastic Processes |
| MATH 311-3 | MENU: Probability and Stochastic Processes |
| MATH 366-0 | Mathematical Models in Finance |
| MATH 368-0 | Introduction to Optimization |
| MATH 386-1 | Econometrics for MMSS |
| MATH 386-2 | Econometrics for MMSS |
Music Theory
| Course | Title |
|---|---|
| MUS_THRY 348-0 | Corpus Studies |
Political Science
| Course | Title |
|---|---|
| POLI_SCI 310-0 | Methods of Political Inference |
| POLI_SCI 312-0 | Statistical Research Methods |
Psychology
| Course | Title |
|---|---|
| PSYCH 345-0 | Presenting Ideas & Data |
| PSYCH 369-0 | Psychological Tests & Measures |
| PSYCH 380-0 | Advanced Statistics & Experimental Design |
| PSYCH 387-0 | Consumer Psychology and Marketing Research |
School of Education and Social Policy
| Course | Title |
|---|---|
| SESP 272-0 | Field Research Methods |
| SOC_POL 330-0 | Economics of Social Policy |
| SOC_POL 331-0 | Economics of Inequality and Discrimination |
| SOC_POL 333-0 | Economics of Health, Human Capital, and Happiness |
Sociology
| Course | Title |
|---|---|
| SOCIOL 303-0 | Analysis and Interpretation of Social Data |
| SOCIOL 329-0 | Field Research and Methods of Data Collection |
Statistics and Data Science
| Course | Title |
|---|---|
| STAT 302-0 | Data Visualization |
| STAT 320-3 | Statistical Theory & Methods 3 |
| STAT 328-0 | Causal Inference |
| STAT 344-0 | Statistical Computing |
| STAT 348-0 | Applied Multivariate Analysis |
| STAT 350-0 | Regression Analysis |
| STAT 351-0 | Design and Analysis of Experiments |
| STAT 352-0 | Nonparametric Statistical Methods |
| STAT 353-0 | Advanced Regression |
| STAT 354-0 | Time Series Modeling |
| STAT 356-0 | Hierarchical Linear Models |
| STAT 357-0 | Introduction to Bayesian Statistics |
| STAT 365-0 | Introduction to the Analysis of Financial Data |
Related Courses - ethics elective (students choose 1 course)
For updates please refer to department website list of Ethics Electives. Some courses may have prerequisites; check course descriptions for details.
Black Studies
| Course | Title |
|---|---|
| BLK_ST 215-0 | Introduction to Black Social & Political Life |
| BLK_ST 220-0 | Civil Rights and Black Liberation |
Entrepreneurship
| Course | Title |
|---|---|
| ENTREP 360-0 | Leadership, Ethics, and You |
Global Health
| Course | Title |
|---|---|
| GBL_HLTH 302-0 | Global Bioethics |
| GBL_HLTH 324-0 | Volunteerism and the Ethics of Help |
Humanities
| Course | Title |
|---|---|
| HUM 325-5 | Humanities in the Digital Age |
Integrated Marketing and Journalism
| Course | Title |
|---|---|
| IMC 310-0 | IMC Law, Ethics and Technology |
| IMC 311-0 | Data Governance |
| JOUR 303-0 | Framed: Media and the Marginalized |
| JOUR 370-0 | Media Law & Ethics |
Latina and Latino Studies
| Course | Title |
|---|---|
| LATINO 342-0 | Latina and Latino Social Movements |
| LATINO 392-0 | Topics in Latina and Latino Social and Political Issues |
Performance Studies
| Course | Title |
|---|---|
| PERF_ST 306-0 | Performance and Race |
Philosophy
| Course | Title |
|---|---|
| PHIL 220-0 | Introduction to Critical Theory |
| or COMP_LIT 207-0 | Introduction to Critical Theory |
| PHIL 221-0 | Gender, Politics, & Philosophy |
| or GNDR_ST 233-0 | Gender, Politics, and Philosophy |
| PHIL 224-0 | Philosophy, Race, and Racism |
| PHIL 240-0 | Freedom and Responsibility |
| PHIL 262-0 | Ethical Problems and Public Issues |
| PHIL 268-0 | Ethics and the Environment |
| PHIL 269-0 | Bioethics |
| PHIL 273-2 | The Brady Scholars Program: The Good Life |
| PHIL 273-3 | The Brady Scholars Program: The Good Society |
| PHIL 363-0 | Kant's Moral Theory |
| PHIL 364-0 | Business and Professional Ethics |
Political Science
| Course | Title |
|---|---|
| POLI_SCI 302-0 | Subjects, Citizens, Revolutionaries: Early Modern Political Thought |
| POLI_SCI 303-0 | Modernity and Its Discontents |
| POLI_SCI 304-0 | Human Rights Between East and West |
| POLI_SCI 307-0 | Deportation Law and Politics |
| POLI_SCI 309-0 | Political Theories of the Rule of Law |
| or LEGAL_ST 309-0 | Political Theories of the Rule of Law |
| POLI_SCI 347-0 | Ethics in International Relations |
| POLI_SCI 382-0 | Religion, Law, & Politics: Politics of Religious Diversity |
Religious Studies
| Course | Title |
|---|---|
| RELIGION 373-0 | Religion and Bioethics |
Slavic Languages and Literatures
| Course | Title |
|---|---|
| SLAVIC 222-0 | Language, Politics, & Identity |
| or LING 222-0 | Language, Politics, and Identity |
| SLAVIC 260-0 | Economics and the Humanities: Understanding Choice |
Sociology
| Course | Title |
|---|---|
| SOCIOL 220-0 | Health, Biomedicine, Culture, and Society |
| or HUM 220-0 | Health, Biomedicine, Culture, and Society |
| SOCIOL 321-0 | Numbers, Identity & Modernity: How Calculation Shapes Who We Are & What We Know |
Data Science Major with Additional Majors or Minors
The major in Data Science fulfills the Weinberg College requirement of completion of a major, but it also can be completed alongside another major, or with a minor. The general Weinberg College policies apply to such combinations. Below is clarifying text about how this works with certain combinations, and where particular exceptions to general rules are approved.
The Data Science Major for Students in the Integrated Science Program
Students complete all requirements for the ISP major, and the requirements for Data Science major are modified as follows:
- Introductory Statistics course requirement (STAT 202-0, STAT 210-0, STAT 232-0 or equivalent) is waived
- MATH 226-0 is waived
- STAT 383-0 Probability and Statistics for ISP counts in place of STAT 320-1
- The 2 related Technical and Domain electives are automatically fulfilled by MATH 381-0 Fourier Analysis and Boundary Value Problems for ISP and EARTH 350-0 Physics of the Earth for ISP
All other data science major course requirements remain the same.
The Data Science Major for Students in the Mathematical Methods in the Social Sciences Program
Students majoring in both Data Science and the adjunct major Mathematical Methods in the Social Sciences (MMSS) need to complete all requirements for the MMSS major, and requirements for Data Science major are modified as follows (for triple major limitations see MMSS Adjunct Major):
- Introductory Statistics course requirement (STAT 202-0, STAT 210-0, STAT 232-0 or equivalent) is waived
- MATH 226-0 is waived
- MATH 385-0 Probability and Statistics for MMSS counts in place of STAT 320-1
- The 2 related Technical and Domain electives are automatically fulfilled by MATH 386-1 Econometrics for MMSS and MATH 386-2 Econometrics for MMSS
All other data science major course requirements remain the same.
The Data Science Major for Students Majoring in Statistics
For students who complete all requirements for Statistics major, the requirements for the Data Science major are modified as follows:
- Introductory Programming course requirement (STAT 201-0 or COMP_SCI 110-0 will be replaced with an additional 300-level STAT approved elective course. Statistics + Data Science majors take 3, 300-level STAT electives from the approved electives list for the Statistics major (see Statistics Major).
- Introductory Statistics course requirement (STAT 202-0, STAT 210-0, STAT 232-0, or equivalent) is waived
- The 2 related Technical and Domain electives are automatically fulfilled by STAT 320-3 Statistical Theory & Methods 3 and STAT 350-0 Regression Analysis
- STAT 320-1 and STAT 320-2 are replaced with 2 elective courses approved by the Director of Undergraduate Studies for Data Science. The 2 elective courses designated as the replacements may not be double counted with any other major/minor.
Note that there can be no double counting between the 300 level elective courses required for the Statistics major and the required Data Science major courses including the elective courses designated as the STAT 320-1 and STAT 320-2 replacements.
All other Data Science major course requirements remain the same.
The Data Science Major for Students Minoring in Statistics
Students complete all requirements for Statistics minor and requirements for Data Science major are modified as follows:
- Introductory Programming course requirement (STAT 201-0 or COMP_SCI 110-0) is replaced with a 300-level STAT elective course from the approved elective list for the Statistics major (see Statistics Major).
- Introductory Statistics course requirement (STAT 202-0, STAT 210-0, STAT 232-0, or equivalent) is waived
- The 2 related Technical and Domain electives are automatically fulfilled by STAT 320-3 Statistical Theory & Methods 3 and STAT 350-0 Regression Analysis
- STAT 320-1 and STAT 320-2 are replaced with 2 elective courses approved by the Director of Undergraduate Studies for Data Science. The 2 elective courses designated as the replacements may not be double counted with any other major/minor.
All other Data Science major course requirements remain the same.
The Data Science Major for Students Completing the Weinberg College Major or Minor in Computer Science
For students who complete all requirements for the Weinberg Computer Science major or minor, the requirements for the Data Science major are modified as follows:
- STAT 304-0 will be replaced with 1 elective course approved by the Director of Undergraduate Studies for Data Science.
All other Data Science major course requirements remain the same.
The Data Science Major for Students Majoring in IEMS or Computer Science (McCormick)
Students complete all requirements for their IEMS or Computer Science (McCormick) major. While none of the requirements for the Data Science major change it is important to note:
- Students are not permitted to use more than 3 courses from outside the Department of Statistics and Data Science to substitute for required Data Science major STAT courses. (see footnote 2)
Honors in Data Science
Majors with strong academic records and an interest in pursuing honors should contact the Director of Undergraduate Studies for Data Science no later than the start of senior year. Accepted students take 2 quarters of STAT 399-0 Independent Study, during which they develop and write a research paper; these enrollments do not count toward the major.
Students whose theses and grades meet department criteria are recommended to the college for graduation with honors. For more information consult the Director of Undergraduate Studies for Data Science and see Honors in the Major.