Data Science

Degree Type
Department
Academic Division The College
Offerings Minor
We live in a world increasingly driven by data. Data science is a rapidly expanding, multidisciplinary field that draws on statistics, computer science and math, with applications in a wide variety of academic disciplines and industries. We extract meaning from data to learn more about the world and society.

Data Science 

The data science minor allows students to complement discipline-specific skills and knowledge with a deeper understanding of how to analyze and extract meaning from data to learn more about the world, society and their discipline. We prepare students to be excellent data analysts in their major disciplines and to be prepared to effectively work with data after graduation. Students:

  • Collect and analyze data in a reproducible and ethically responsible manner
  • Obtain data through searching, scraping, mining or experimental methods
  • Parse, transform and generate wide-ranging data sets for analysis
  • Statistically analyze data to summarize, draw inferences and make predictions
  • Identify patterns and relationships in datasets using visualization and algorithms
  • Communicate data methods and conclusions to diverse audiences

Students trained in data science can apply their skills in a wide variety of ways including serving as central operations manager at Uber (Holley Beasley ’15), working as executive vice president at Microstrategy (Rich Cober ’96), and serving as head of industry at Google (Ames McArdle ’02).   

DataCon

W&L hosts DataCon, where people from all corners of industry come to discuss the impacts of data science on industry and the world. Students from all over the university, from biology to sociology to business, participate in the Data Science Program to learn from each other and discover how to ethically learn from data.  

Dan Johnson

Program Head
E: datascience@wlu.edu

Carolyn Wingrove-Moore

Administrative Assistant
P: 540-458-8151
E: wingrove-moorec@wlu.edu

News

All News

Sample Courses

At W&L, we believe education and experience go hand-in-hand. You'll be encouraged to dive in, explore and discover connections that will broaden your perspective.
BIOL 185

Exploring & Visualizing Big Data

In this course, students learn to use R, a popular open-source programming language and data analysis environment, to interactively explore data. Case studies are drawn from across the sciences and medicine. Topics include data visualization, machine learning, image analysis, geospatial analysis, and statistical inference on large data sets. We also emphasize best practices in coding, data handling, and adherence to the principles of reproducible research.

SOAN 265

Exploring Social Networks

In this introduction to network analysis, students learn some of the major network analysis literature in sociology and related fields and develop their skills as network analysts in laboratory sessions. Social science, humanities, business and public health applications are emphasized.

CBSC 240

Intro to Data Science: Mind Analytics

Psychological tests promise to match you with your soul mate, reveal the hidden depths of your personality and attitudes, and predict your success in college. How would you determine if these promises are being kept? Students build data-science skills while teaming on how to assess a test’s reliability and validity, including tests of abilities, personality, attitudes, and more. No programming experience is required while we use R, a popular open-source programming language, to learn data management, data visualization, model-comparison metrics, and statistical inference in a reproducible and ethically responsible manner.

BUS 314

Intro to Data Science for Business

This course covers organizational concerns related to data science such as artificial intelligence, machine learning, predictive algorithms, Big Data, cloud computing, security and privacy, and the digitization of products and processes. Through readings, students develop a strong conceptual understanding of concepts prior to developing technical proficiency in some of them. Assignments focus on how organizations can improve decision making and create new business opportunities using data science.

DCI 102

Data in the Humanities

This course introduces students to the creation and visualization of data in humanities research. The community and set of practices that is digital humanities encourages fluency in media beyond the printed word such as text mining, digital curation, data visualization, and spatial analysis. Readings and discussions of theory complement hands-on application of digital methods and computational thinking. While the objects of our study come primarily from the humanities, the methods of analysis are widely applicable to the social and natural sciences.

CSCI 256

Modeling & Simulation

This course covers standard practices and applications of modeling and simulation. We explore ways to model complex systems that incorporate disciplines of biology, chemistry and physics. Students learn critical-thinking skills when reading, comprehending and analyzing real-world systems for which they then create models.

Meet the Faculty

At W&L, students enjoy small classes and close relationships with professors who educate and nurture.
Dan Johnson David G. Elmes Term Professor of Cognitive and Behavioral Science
P: 540-458-8629 E: johnsondr@wlu.edu
Johnson’s courses include Psychology Mythbusters and Introduction to Data Science: Mind Analytics. His lab uses computational models and empirical data to investigate the mechanisms underlying creativity processes like the generation of novel ideas. In the Computational Cognition and Creativity Lab, he and students use computational models and empirical data to investigate the mechanisms underlying creativity processes like the generation and selection of novel ideas.
Curriculum Vitae
Robert M. Ballenger Professor of Business Administration
P: 540-458-8438 E: ballengerb@wlu.edu
Ballenger is a 1976 W&L alumnus who teaches courses in accounting information systems, data analytics and multimedia design. He previously worked for Unisys Corporation and served as the executive vice president of ServNET Technologies.
Curriculum Vitae
Jeff Barry Associate Professor and Associate University Librarian
P: 540-458-8641 E: barryj@wlu.edu
Barry teaches courses listed under digital culture and information, journalism and writing. His research interests include digital storytelling, the evolution of literary magazines and social network analysis.
Jonathan Eastwood Department Head, Sociology and Anthropology; Professor of Sociology
P: 540-458-8777 E: eastwoodj@wlu.edu
Professor Eastwood is a social theorist who also has a strong interest in quantitative methods. He teaches seminars on classical and contemporary theory as well as a series of courses that train students how to use quantitative and computational tools to answer sociological questions.
Keri M. Larson Assistant Professor of Business Administration
P: 540-458-8601 E: larsonk@wlu.edu
Larson teaches courses that help students learn to understand and use data in areas of management. She has researched the analytics of unstructured textual data to support organizational decision making.
Curriculum Vitae
Sybil Prince Nelson Assistant Professor of Mathematics
P: 540-458-4881 E: sprincenelson@wlu.edu
Prince Nelson '01 teaches courses in calculus, probability and statistics. Her research is focused on creating tree-based models for classifying and predicting outcomes from complex data.
Natalia Toporikova Associate Professor of Biology
P: 540-458-5809 E: toporikovan@wlu.edu
Professor Toporikova's courses include Biological Clocks and Rhythms, The Architecture of Living Systems, Dynamics of Biological Systems and Pregnancy: A Kiss in Time? In her research, she applies methods of computational modeling to study a wide range of biological systems. Some recent projects include neural control of breathing, pregnancy initiation in rats, and daily circadian cycle.
Cody Watson Assistant Professor of Computer Science
P: 540-458-4872 E: cwatson@wlu.edu
Watson teaches applications of deep learning in software engineering and the progression of software 2.0. Has recently been exploring the applications of software methodologies to deep learning-based solutions.
Gregg Whitworth Associate Professor of Biology
P: 540-458-8895 E: whitworthg@wlu.edu
Whitworth's courses include Data Science: Visualizing and Exploring Big Data and The Molecular Mechanics of Life.