MINOR

What You’ll Study

Warren Wilson College’s interdisciplinary data science minor prepares you to organize, analyze, and extract information from large data sets using statistics, computer science, and mathematics. You will learn how to gain insight into complex issues through data analysis, creating predictive models, visualizations, explanations, and connections. Data Science is useful across disciplines: Business, Biology, Psychology, Sociology, Environmental Studies, and even the Humanities. You will find applications for your skills no matter your field.

You’ll use statistics in real-world situations to gain insight into complex datasets, and you’ll learn how to present and discuss your results in a professional context. You will learn the programming languages Python and R, spatial analysis procedures on raster and vector data, database management, topology, model design, 3D modeling, web mapping, and project management. You can then focus your learning through higher level Computer Science or Mathematics courses and gain depth through Advanced Data Science or Geographic Information Systems (GIS) courses.

As your studies culminate in a Data Science Capstone Project, you will apply your knowledge and skills to a real-world application area. Working closely with faculty, you could create an application using academic research, complete a project that solves a problem for a community partner, or work on a significant data-driven project on a professional internship with a company or nonprofit organization.

Explore Classes in This Program

GBL 3250

Advanced Geographic Information Systems (GIS)

In this course, you’ll apply concepts and techniques of geographic information science as you view, manipulate, analyze, and disseminate geographic data. You’ll learn about spatial analysis procedures on raster and vector data, database management, topology, model design, 3D modeling, open source GIS, web mapping, and project management. You’ll design and conduct a significant research project to solve a real-world problem for a non-profit organization.

MAT 1411

Applied Statistics

In this introductory course in descriptive and inferential statistics, you’ll use statistics in real-world situations to gain insight into complex datasets, and you’ll learn how to present and discuss your results. You’ll use the R open-source software programming language to learn data visualization and analysis, which is an industry-standard tool for today’s market. You’ll explore examples in this course that cross disciplines and focus on normal distributions, Chi Square procedures, and Analysis of Variance (ANOVA).

MAT 3039

Advanced Topics in Data Science

Using the R programming language, you’ll master advanced methods in data cleansing and visualization, use data analysis to generate hypotheses and intuition about real-world datasets, and employ statistical and computational methods to make predictions based on the data. You’ll become fluent in ways to describe and visualize data in a professional context.

Meet Our Faculty

I love the diverse interests of students, faculty, and staff at Warren Wilson.

Holly Rosson, Ph.D.
Holly Rosson
Holly Rosson, Ph.D.
David Abernathy

Warren Wilson students crave a challenge. I am continually amazed at the enthusiasm with which our students throw themselves into an endeavor, whether it be a physically exhausting service trip or an intellectually stimulating research question. Wilson students tend to say “bring it.”

David Abernathy, Ph.D.
David Abernathy
David Abernathy, Ph.D.
Holly Rosson
Buncombe County map
Fieldwork Profile

Mapping Change

Students and faculty at Warren Wilson contributed a major project for Buncombe County called ‘Mapping Change.’ It used maps to analyze change over a 10-year period of rapid growth in Western North Carolina. The project culminated in an 80-page book, which analyzed the effects of change in terms of land use, demography, water quality, and housing. The data united many different social and ecological problems, illustrating how they connect to one another.

Professor Paul Bartels outlined the findings for the county commissioners in a presentation using maps from the book. Among many other observations, Bartels connected the impact of homes built on steep slopes with sediment erosion, stream pollution, and trout populations. Through Bartels’ presentation to county lawmakers, Warren Wilson students’ work in GIS and Data Science influenced local government.