Data Science Minor

Students minoring in data science receive exposure to computational and applied statistical techniques. This minor provides a strong foundation for graduate work and academic preparation in the area.

Requirements for the Minor in Data Science

Students take 2 foundational courses, 4 core courses (the 3 Data Science sequence courses and Data Visualization (STAT 302-0)), and 1 approved elective. For details see course lists, below.

Course Title
Minor Requirements (7 units)
2 foundational courses:
Introduction to Programming for Data Science
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
Introduction to Probability and Statistics
Applied Statistics
or approved introductory statistics course from another department
4 data science core courses:
Data Science 1 with R
and Data Science 2 with R
and Data Science 3 with R
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 Visualization
1 approved elective course (see lists below)

Lists of topics not covered in substitute courses can be found on the department website.

Courses used to fulfill the requirements for the minor in data science may not be used to fulfill the requirements for another major/minor except where permitted by Weinberg College double-counting rules (see FAQ). When necessary (for example when a student plans to complete a major in statistics and a minor in data science), students can consult the Director of Data Science in the Department of Statistics and Data Science about selection of replacement course(s) to satisfy the credit requirements of the data science minor.

Approved Elective Courses for the Data Science Minor

Students choose 1 course from any of the fields below. For updates please refer to department website list of Data Science Minor Approved Electives. Some courses may have prerequisites; check course descriptions for details.


Course Title
ANTHRO 322-0Introduction to Archaeology Research Design & Methods
ANTHRO 324-0Archaeological Survey Methods
ANTHRO 362-0Advanced Methods in Quantitative Analysis
ANTHRO 389-0Ethnographic Methods and Analysis

Biological Sciences

Course Title
BIOL_SCI 323-0Bioinformatics: Sequence and Structure Analysis
BIOL_SCI 338-0Modeling Biological Dynamics
BIOL_SCI 341-0Population Genetics
BIOL_SCI 354-0Quantitative Analysis of Biology
BIOL_SCI 359-0Quantitative Experimentation in Biology
BIOL_SCI 378-0Functional Genomics

Biomedical Engineering

Course Title
BMD_ENG 311-0Computational Genomics

Chemical Engineering

Course Title
CHEM_ENG 379-0Computational Biology: Analysis and Design of Living Systems

Cognitive Science

Course Title
COG_SCI 345-0Presenting Ideas & Data

Communication Studies

Course Title
COMM_ST 352-0Social Network Analysis
COMM_ST 355-0Audience Analysis
COMM_ST 358-0Algorithms and Society
COMM_ST 371-0Cultural Analytics

Computer Engineering

Course Title
COMP_ENG 329-0The Art of Multicore Concurrent Programming
COMP_ENG 358-0Introduction to Parallel Computing
COMP_ENG 365-0Internet-of-things Sensors, Systems, And Applications
COMP_ENG 368-0Programming Massively Parallel Processors with CUDA

Computer Science

Course Title
COMP_SCI 214-0Data Structures & Algorithms
COMP_SCI 217-0Data Management & Information Processing
COMP_SCI 323-0Code Analysis and Transformation
COMP_SCI 325-0Artificial Intelligence Programming
COMP_SCI 331-0Introduction to Computational Photography
COMP_SCI 333-0Interactive Information Visualization
COMP_SCI 335-0Introduction to the Theory of Computation
COMP_SCI 336-0Design & Analysis of Algorithms
COMP_SCI 337-0Natural Language Processing
COMP_SCI 339-0Introduction to Database Systems
COMP_SCI 344-0Design of Computer Problem Solvers
COMP_SCI 345-0Distributed Systems
COMP_SCI 347-0Conversational AI
COMP_SCI 348-0Introduction to Artificial Intelligence
COMP_SCI 349-0Machine Learning
COMP_SCI 351-1Introduction to Computer Graphics
COMP_SCI 351-2Intermediate Computer Graphics
COMP_SCI 352-0Machine Perception of Music & Audio
COMP_SCI 367-0Wireless and Mobile Health: Passive Sensing Data Analytics

Earth and Planetary Science

Course Title
EARTH 323-0Seismology and Earth Structure
EARTH 327-0Geophysical Time Series Analysis
EARTH 340-0Physics of Weather & Climate
EARTH 343-0Earth System Modeling
EARTH 353-0Mathematical Inverse Methods in Earth and Environmental Sciences
EARTH 360-0Instrumentation and Field Methods
EARTH 361-0Scientific Programming in Python
EARTH 362-0Data Analysis for Earth and Planetary Sciences


Course Title
ECON 310-1Microeconomics
ECON 310-2Microeconomics
ECON 311-0Macroeconomics
ECON 329-0Experimental Economics
ECON 330-0Behavioral Economics
ECON 331-0Economics of Risk and Uncertainty
ECON 336-0Analytic Methods for Public Policy Analysis
ECON 380-1Game Theory
ECON 381-1Econometrics
ECON 381-2Econometrics
ECON 383-0Applied Econometrics

Electrical Engineering

Course Title
ELEC_ENG 328-0Information Theory & Learning
ELEC_ENG 331-0Introduction to Computational Photography
ELEC_ENG 332-0Introduction to Computer Vision
ELEC_ENG 335-0Deep Learning Foundations from Scratch
ELEC_ENG 373-0Deep Reinforcement Learning
ELEC_ENG 375-0Machine Learning: Foundations, Applications, and Algorithms

Engineering Sciences and Applied Mathematics

Course Title
ES_APPM 344-0High Performance Scientific Computing
ES_APPM 346-0Modeling and Computation in Science & Engineering
ES_APPM 370-1Introduction to Computational Neuroscience
ES_APPM 375-1Quantitative Biology I: Experiments, Data, Models, and Analysis
ES_APPM 375-2Quantitative Biology II: Experiments, Data, Models, and Analysis


Course Title
GEOG 341-0Principles of Cartography
GEOG 343-0Geographic Information Systems

Global Health Studies

Course Title
GBL_HLTH 320-0Qualitative Research Methods in Global Health

Industrial Engineering and Management Sciences

Course Title
IEMS 308-0Data Science and Analytics
IEMS 313-0Foundations of Optimization
IEMS 315-0Stochastic Models
IEMS 317-0Discrete Event Systems Simulation
IEMS 340-0Qualitative Methods in Engineering Systems
IEMS 341-0Social Networks Analysis
IEMS 351-0Optimization Methods in Data Science

Integrated Marketing Certificate

Course Title
IMC 302-0Research and Data Analytics
IMC 307-0Digital, Social and Mobile Marketing


Course Title
JOUR 342-1Knight Lab: Studio
JOUR 377-0Knight Lab: Data Analysis & Visualization


Course Title
LING 334-0Introduction to Computational Linguistics


Course Title
MATH 306-0Combinatorics & Discrete Mathematics
MATH 308-0Graph Theory
MATH 310-1Probability and Stochastic Processes
MATH 310-2Probability and Stochastic Processes
MATH 310-3Probability and Stochastic Processes
MATH 311-1MENU: Probability and Stochastic Processes
MATH 311-2MENU: Probability and Stochastic Processes
MATH 311-3MENU: Probability and Stochastic Processes
MATH 314-0Probability and Statistics for Econometrics
MATH 366-0Mathematical Models in Finance
MATH 368-0Introduction to Optimization
MATH 370-0Mathematical Logic
MATH 386-1Econometrics for MMSS
MATH 386-2Econometrics for MMSS

Music Theory

Course Title
MUS_THRY 348-0Corpus Studies

Political Science

Course Title
POLI_SCI 310-0Methods of Political Inference
POLI_SCI 312-0Statistical Research Methods


Course Title
PSYCH 345-0Presenting Ideas & Data
PSYCH 369-0Psychological Tests & Measures
PSYCH 380-0Advanced Statistics & Experimental Design
PSYCH 387-0Consumer Psychology and Marketing Research

School of Education and Social Policy

Course Title
SESP 272-0Field Research Methods
SOC_POL 330-0Economics of Social Policy
SOC_POL 331-0Economics of Inequality and Discrimination
SOC_POL 333-0Economics of Health, Human Capital, and Happiness


Course Title
SOCIOL 303-0Analysis and Interpretation of Social Data
SOCIOL 329-0Field Research and Methods of Data Collection
SOCIOL 335-0Sociology of Rational Decision Making

Statistics and Data Science

Course Title
STAT 320-1Statistical Theory & Methods 1
STAT 320-2Statistical Theory & Methods 2
STAT 320-3Statistical Theory & Methods 3
STAT 328-0Causal Inference
STAT 344-0Statistical Computing
STAT 348-0Applied Multivariate Analysis
STAT 350-0Regression Analysis
STAT 351-0Design and Analysis of Experiments
STAT 352-0Nonparametric Statistical Methods
STAT 353-0Advanced Regression
STAT 354-0Time Series Modeling
STAT 356-0Hierarchical Linear Models
STAT 357-0Introduction to Bayesian Statistics
STAT 365-0Introduction to the Analysis of Financial Data

The Data Science Minor in Relation to Majors

The minor in Data Science can be completed along with any major. The general Weinberg College policies about major/minor pairings apply. Below is clarifying text about how this works with certain majors, and where particular exceptions to general rules are approved.

The Data Science Minor for Students in the Integrated Science Program

Students complete all requirements for the ISP major, and requirements for Data Science minor are modified as follows:

All other Data Science minor requirements must be met.

The Data Science Minor for Students in the Mathematical Methods in the Social Sciences Program

Students will complete all requirements for the MMSS adjunct major, and requirements for Data Science minor are modified as follows:

All other Data Science minor requirements must be met.

The Data Science Minor with the Major in Statistics

Students complete all requirements for Statistics major, and requirements for Data Science minor are modified as follows:

  • STAT 201-0 (or COMP_SCI 110-0) is replaced with another approved course. In most cases, an introductory calculus course that is necessary for the Statistics major will be used as the replacement.
  • STAT 202-0, STAT 210-0, STAT 232-0 or equivalent is replaced with another approved course. In most cases, an introductory calculus course that is necessary for the Statistics major will be used as the replacement.

Note: STAT 301-1,2,3 (Data Science with R), STAT 303-1,2,3 (Data Science with Python), and any 300-level electives being used for the Data Science minor cannot be used to fulfill credit requirements for the Statistics major.

All other Data Science minor requirements must be met.