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Data Science Minor

Data science empowers students across disciplines to use data to understand the world and solve real-world problems. By combining computation, statistics, and domain expertise, students learn to transform complex data into meaningful insights that inform decisions, research, and innovation.

About the Minor

Data Science empowers students across every major to understand and use data in their fields. By blending computational tools, statistical methods, and domain expertise, you'll learn to transform complex datasets—from genomic sequences to social media patterns, from economic indicators to historical texts—into insights that drive discovery and inform decisions. Whether you're pursuing research, policy, business, healthcare, or social impact, data science skills help you excel.

Data Science Minor by the Numbers

  • 78

    Majors represented by Data Science Minor students across all of Vanderbilt's undergraduate colleges.

  • 90+

    Courses eligible for the Data Science Minor.

  • 22

    Departments contributing courses to the Data Science Minor.

Required Courses

  • Introduction to Data Science (3 hours)

    DS 1000 is an introduction to data science and provides a broad overview of data science applications and techniques. As an introductory course, students are highly encouraged to take DS 1000 early in their academic careers, and should not depend on enrollment in this course in their senior year.

  • Computer Programming (3 hours)
    DS 1100Applied Programming and Problem Solving with Python
    CS 1100Applied Programming and Problem Solving with Python
    CS 2201Program Design and Data Structures (prereq: CS 1101)
    CS 2204Program Design and Data Structures for Scientific Computing (prereq: CS/DS1100 or CS 1104)
  • Introduction to Statistics (3 hours)
    DS 2100Statistics for Data Science
    BME 2400Quantitative Methods I: Statistical Analysis
    BSCI 3270Statistical Methods in Biology
    CE 3300Risk, Reliability, and Resilience Engineering
    ECON 1500Economic Statistics
    ECON 1510Intensive Economic Statistics
    MATH 2810Probability and Statistics for Engineering
    MATH 2821Introduction to Applied Statistics
    PSY 2100Quantitative Methods
    PSY-PC 2110Introduction to Statistical Analysis
    SOC 2100Statistics for Social Scientists
  • Data Science Fundamentals (4 hours)
     DS 3100  Fundamentals of Data Science
     DS 3100L  Fundamentals of Data Science Lab
  • Machine Learning (3 hours)
    DS 3262Applied Machine Learning
    CS 3262Applied Machine Learning
    CS 4262Foundations of Machine Learning
    ECON 3750Econometrics for Big Data
    MATH 3670Mathematical Data Science
  • Elective (3 hours)

    One course from the list of electives below.

    Electives in data science are courses with various combinations of computation, visualization, simulation, statistics, psychometrics, and/or machine learning aimed at understanding and explaining data in the physical, life, or social sciences, engineering, arts, or the humanities, or courses that examine the impact of data on society and its institutions. Students and faculty are encouraged to petition for new courses with data science content to be considered as electives for the minor.

    A. Intermediate / Advanced Programming, Modeling, Simulation

    ASTR 3800Structure Formation in the Universe
    BME 4310Modeling Living Systems for Therapeutic Bioengineering
    BSCI 3271Programming for Biologists
    CHBE 4830Molecular Simulation
    CHEM 5410Molecular Modeling Methods
    CHEM 5420Computational Structural Biochemistry
    EES 4760Agent and Individual Based Computational Modeling
    MATH 3660Mathematical Modeling in Economics
    ME 4271Fundamentals of Robotic Manipulators
    ME 4284Modeling and Simulation of Dynamic Systems
    ME 4263Computational Fluid Dynamics and Multiphysics Modeling
    ME 4275Finite Element Analysis
    PHYS 3790Computational Physics
    PSY 4218Computational Cognitive Modeling
    PSY 4219Scientific Computing for Psychological and Brain Sciences
    PSY 4775Models of Memory
    SC 3250Scientific Computing Toolbox
    SC 3260High Performance Computing

    B. Intermediate / Advanced Probability, Statistics, and Data Analysis

    ASTR 8070Astrostatistics
    BIOS 6311Principles of Modern Biostatistics
    BIOS 6312Modern Regression Analysis
    BIOS 6341Fundamentals of Probability
    BIOS 6342Contemporary Statistical Inference
    BIOS 7362Advanced Statistical Inference and Statistical Learning
    BIOS 8366Advanced Statistical Computing
    BME 4420Quantitative and Functional Imaging
    BSCI 5890Special Topics in Biological Sciences: Big Data for Biologists (Offered Spring 2024)
    CE 4320Data Analytics for Engineers
    CSET 3410Telling Stories with Data
    ECON 3032Applied Econometrics
    ECON 3035Econometric Methods
    ECON 3330Economics of Risk
    ECON 4050Topics in Econometrics
    EES 3310Global Climate Change
    MATH 3640Probability
    MATH 3641Mathematical Statistics
    MATH 4650Financial Stochastic Processes
    MHS 3120Medicine, Technology, and Society
    PPS 3200Research Methods for Public Policy Analysis
    PPS 3250Advanced Quantitative Methods for Public Policy
    PSCI 2310Understanding Policy Data: Analysis and Interpretation
    PSCI 3249American Public Opinion and American Politics
    PSCI 3893Selected Topics in American Government – Media & Data in American Politics
    PSY 4220Bayesian Cognitive Modeling
    PSY 4720Experimental Methods in Behavioral Neuroscience
    PSY-PC 2120Statistical Analysis
    PSY-PC 3722Psychometric Methods
    PSY-PC 3724Psychometrics
    PSY-PC 3738Introduction to Item Response Theory
    PSY-PC 3743Factor Analysis
    PSY-PC 3749Applied Nonparametric Statistics
    PSY-GS 8867Multivariate Statistics (formerly PSY-PC 3746)
    PSY-PC 3737Structural Equation Modeling
    PSY-PC 3732Latent Growth Curve Modeling
    PSY-PC 3727Modern Robust Statistical Methods
    PSY-PC 7878Statistical Consulting

    C. Machine Learning, Visualization, Data Science

    ANTH 3050Artificial Intelligence and Material Culture
    ANTH 3261Introduction to Geographic Information Systems and Remote Sensing
    ANTH 3867Digital Archaeology
    ASTR 8080Data Mining in Large Astronomical Surveys
    BME 3890Computational Genomics
    BME 4420Quantitative and Functional Imaging
    BMIF 6310Foundations of Bioinformatics
    BMIF 6315Methodological Foundations of Biomedical Informatics
    BMIF 7380Data Privacy in Biomedicine
    BSCI 3272Genome Science
    CS 3265Introduction to Database Management Systems
    CS 3891Special Topics: Social Network Analysis
    CS 3892Projects in Machine Learning
    CS 4260Artificial Intelligence
    CS 4266Topics in Big Data
    CS 4267Deep Learning
    CS 6362Advanced Machine Learning
    CS 8395Visual Analytics & Machine Learning
    CS 8395Special Topics – Selected Topics in Deep Learning
    DS 3891Special Topics in Data Science – Intro to Generative Artificial
    DS 3891Special Topics in Data Science – Technical Consulting in DS
    ECE 4363Applied Statistical Machine Learning
    ECE 4354Computer Vision
    ECON 3750Econometrics for Big Data
    HIST 1354Digital Methods for History Research
    HIST 1590Artificial Intelligence and Society
    MATH 3130Fourier Analysis
    MATH 3670Mathematical Data Science
    MATH 4620Linear Optimization
    MATH 4630Nonlinear Optimization
    MHS 3015Applied AI for Health Sciences
    MHS 3890Special Topics – Introduction to Data Visualization
    MTEC 2350Artificial Intelligence and the Creative Musician
    NSC 3270Computational Neuroscience
    PSY-PC 3751Exploratory and Graphical Data Analysis
    PSY-PC 7500-03Special Topics Psychology and Human Development-Neural Network Models of Cog Dev (Offered Spring 2024)
    SOC 3242AI in Social Systems
    ULAW 2542Introduction to Artificial Intelligence in the Legal Profession

    D. Research Hours in Data Science

    DS 3850Undergraduate Research in Data Science

Please refer to the current undergraduate catalog for full requirements. If any discrepancy exists between the requirements below and those listed in the undergraduate catalog, requirements in the catalog always prevail.

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