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Data Science Minor Requirements

Introduction to Data Science (3 hours)

 DS 1000   Data Science: How Data Shape Our World

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.

Students who are currently enrolled in or have already taken DS 3100 or PSCI 2300 may also request substitutions which will be considered on a case-by-case basis. Please fill out the DS 1000 substitution form here for consideration. Email if you have questions and for substitution approvals.

Computer Programming (3 hours)

One of the following (see also What Programming Course To Take?):

 DS 1100   Applied Programming and Problem Solving with Python
 CS 1100   Applied Programming and Problem Solving with Python
 CS 2201   Program Design and Data Structures (prereq: CS 1101)
 CS 2204    Program Design and Data Structures for Scientific Computing (prereq: CS 1104)

Introduction to Statistics (3 hours)

One of the following:

 DS 2100   Statistics for Data Science
 BME 2400   Quantitative Methods I: Statistical Analysis
 BSCI 3270   Statistical Methods in Biology
 CE 3300   Risk, Reliability, and Resilience Engineering
 ECON 1500   Economic Statistics
 ECON 1510   Intensive Economic Statistics
 MATH 2810   Probability and Statistics for Engineering
 MATH 2821   Introduction to Applied Statistics
 PSY 2100   Quantitative Methods
 PSY-PC 2110   Introduction to Statistical Analysis
 SOC 2100   Statistics for Social Scientists

Data Science Fundamentals (4 hours)

 DS 3100   Fundamentals of Data Science

Machine Learning (3 hours)

One of the following:

 DS 3262   Applied Machine Learning
 CS 3262   Applied Machine Learning
 CS 4262   Foundations of Machine Learning
 ECON 3750   Econometrics for Big Data
 MATH 3670   Mathematical 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 3800   Structure Formation in the Universe
 BME 4310   Modeling Living Systems for Therapeutic Bioengineering
 CHEM 5410   Molecular Modeling Methods
 CHEM 5420   Computational Structural Biochemistry
 EES 4760   Agent and Individual Based Computational Modeling
 MATH 3660 Mathematical Modeling in Economics
 ME 4271   Fundamentals of Robotic Manipulators
 ME 4284   Modeling and Simulation of Dynamic Systems
 ME 4263   Computational Fluid Dynamics and Multiphysics Modeling
 ME 4275   Finite Element Analysis
 PHYS 3790   Computational Physics
 PSY 4218   Computational Cognitive Modeling
 PSY 4219   Scientific Computing for Psychological and Brain Sciences
 PSY 4775   Models of Memory
 SC 3250   Scientific Computing Toolbox
 SC 3260   High Performance Computing

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


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

C. Machine Learning, Visualization, Data Science


ANTH 3050 Selected Topics: A.I. and Material Culture (Offered Fall 2023)
ANTH 3261 Introduction to Geographic Information Systems and Remote Sensing
ANTH 3867 Digital Archaeology
ASTR 8080 Data Mining in Large Astronomical Surveys
BME 3890 Computational Genomics
BME 4420 Quantitative and Functional Imaging
BMIF 6310 Foundations of Bioinformatics
BMIF 6315 Methodological Foundations of Biomedical Informatics
BMIF 7380 Data Privacy in Biomedicine
BSCI 3272 Genome Science
CS 3265 Introduction to Database Management Systems
CS 3891 Special Topics: Social Network Analysis
CS 3892 Projects in Machine Learning
CS 4260 Artificial Intelligence
CS 4266 Topics in Big Data
CS 6362 Advanced Machine Learning
CS 8395 Visual Analytics & Machine Learning
CS 8395 Special Topics – Selected Topics in Deep Learning
DS 3891
Special Topics in Data Science – Intro to Generative Artificial
EECE 3891 Statistical Machine Learning
EECE 4354 Computer Vision
ECON 3750 Econometrics for Big Data
HUM 1610 Selected Topics – AI and Society (Offered Fall 2023)
MATH 3130 Fourier Analysis
MATH 3670 Mathematical Data Science
MATH 4620 Linear Optimization
MATH 4630 Nonlinear Optimization
MHS 3890 Special Topics – Introduction to Data Visualization
NSC 3270 Computational Neuroscience
PSY-PC 3751 Exploratory and Graphical Data Analysis

D. Research Hours in Data Science

DS 3850 Undergraduate Research in Data Science

The minor in Data Science is jointly administered by the Blair School of Music, the College of Arts and Science, Peabody College of Education and Human Development, and the School of Engineering; it is an official minor within each of the four schools.

Students electing the undergraduate minor in Data Science must follow academic regulations regarding minors in their home school, including but not limited to regulations regarding unique hours. Additional credit hours in Data Science that must be earned because of college-specific regulations regarding unique hours must be earned by taking additional courses chosen from the list of electives.

If you have questions about the Data Science Minor or Immersion opportunities in data science, please email us at