Undergraduate Courses
Students in any major at Vanderbilt can help prepare themselves for future education or employment in Data Science with foundational courses in mathematics, statistics, and computation, along with a variety of elective courses. Examples of existing Vanderbilt courses that cover key Data Science topics are listed below.
Computer Programming
At least two semesters of computer programming:
CS 1101 Programming and Problem Solving (with Java)
OR
CS 1104 Programming and Problem Solving (with Python)
and
CS 2201 Program Design and Data Structures
OR
CS 2204 Program Design and Data Structures for Scientific Computing.
Calculus and Linear Algebra
Multivariate calculus and basic linear algebra highly recommended:
MATH 2310 Multivariable Calculus with Matrix Algebra
MATH 2400 Differential Equations with Linear Algebra
MATH 2410 Methods of Linear Algebra
MATH 2501 Multivariable Calculus and Linear Algebra
MATH 2600 Linear Algebra
Probability and Statistics
A variety of introductory courses are offered:
BME 3200 Analysis of Biomedical Data
BSCI 3270 Statistical Methods in Biology
CE 3300 Risk, Reliability, and Resilience Engineering
ECON 1510 Intensive Economic Statistics
MATH 2810 Probability and Statistics for Engineering
MATH 2820 Introduction to Probability and Mathematical Statistic
PSY 2100 Quantitative Methods
PSY-PC 2110 Introduction to Statistical Analysis
SOC 2100 Statistics for Social Scientists
Machine Learning
CS 4262 Foundations of Machine Learning
HOD 3200 Introduction to Data Science
MATH 3670 Mathematical Data Science
NSC 3270 Computational Neuroscience
Electives
Intermediate / Advanced Programming, Modeling, Simulation
CS 3250 Algorithms
CS 3251 Intermediate Software Design
CS 3274 Modeling and Simulation
PSY 8218 Computational Modeling
SC 3250 Scientific Computing Toolbox
SC 3260 High Performance Computing
Intermediate / Advanced Probability, Statistics, and Data Analysis
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
CE 3890 Data Analytics for Engineers
ECON 3035 Econometric Methods
ECON 3330 Economics of Risk
ECON 4050 Topics in Econometrics
HOD 3275 Practical Meta-analysis
MATH 2821 Introduction to Applied Statistics
MATH 3640 Probability
MATH 3641 Mathematical Statistics
MATH 4650 Financial Stochastic Processes
PSY 3891 Bayesian Cognitive Modeling
PSY-PC 3738 Introduction to Item Response Theory
PSY-PC 3743 Factor Analysis
PSY-PC 3749 Applied Nonparametric Statistics
PSY-PC 3746 Multivariate Statistics
PSY-PC 3730 Applied Latent Class and Mixture Modeling
PSY-PC 3737 Structural Equation Modeling
PSY-PC 3732 Latent Growth Curve Modeling
PSY-PC 3727 Modern Robust Statistical Methods
Machine Learning, Visualization, Data Science
ANTH 3261 Introduction to Geographic Information Systems and Remote Sensing
BMIF 6310 Foundations of Bioinformatics
BMIF 7380 Data Privacy in Biomedicine
CS 3265 Introduction to Database Management Systems
CS 4266 Topics in Big Data
CS 4287 Principles of Cloud Computing
CS 4260 Artificial Intelligence
CS 6362 Advanced Machine Learning
DS 3860 Undergraduate Research in Data Science
EECE 4354 Computer Vision
ECON 3750 Econometrics for Big Data
MATH 3130 Fourier Analysis
MATH 3670 Mathematical Data Science
MATH 4620 Linear Optimization
MATH 4630 Nonlinear Optimization
PSY-PC 3751 Exploratory and Graphical Data Analysis