六合厅开奖现场

Data Science

  • Department Interdisciplinary
  • Academic Division The College
  • Offerings Minor

A student takes notes while working at her computer. A student takes notes while working at her computer.

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

Carolyn Wingrove-Moore

Administrative Assistant

News


Christianson will be working as a research coordinator studying autism in infants and young children.

The scholarship will support Wright鈥檚 future studies in urban sociology.

The Gilman Scholarship Program offers awards of up to $5,000 to U.S. undergraduate students who are Pell Grant recipients.

Moye-Green 鈥23 is the university鈥檚 first Knight-Hennessy Scholar.

Ben Bankston '25

Ben Bankston 鈥25 is finding opportunities at 六合厅开奖现场 to challenge himself in and out of the classroom.

Sahin is 六合厅开奖现场鈥檚 first sophomore to receive the scholarship since 2009.

The professor and pollster will discuss applied sociology methods in her March 19 talk.

Sybil Prince Nelson

Nelson will deliver a lecture on 鈥淲here Math Meets Imagination鈥 on March 19.

Josh Rassin 鈥24 will begin his two-year placement with a startup company following graduation.

Lauren Shelby 鈥23 will be pursuing her master鈥檚 degree at New York University.

Dixon has been awarded a Fulbright English Teaching Assistantship to teach English in Taiwan.

First-year Johnson Scholar to offer preliminary research on foot-limb dominance and neuromuscular asymmetry in pediatric soccer players.

Sample Courses

At 六合厅开奖现场, we believe education and experience go hand-in-hand. You鈥檒l 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鈥檚 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 六合厅开奖现场, students enjoy small classes and close relationships with professors who educate and nurture.

Dan Johnson
Dan Johnson

Dan Johnson

David G. Elmes Term Professor of Cognitive and Behavioral Science

Johnson鈥檚 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.

Jeff Barry
Jeff Barry

Jeff Barry

Associate Professor and Associate University Librarian

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.

Cody Watson
Cody Watson

Cody Watson

Assistant Professor of Computer Science

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.

Justin Davis
Justin Davis

Justin Davis

Assistant Professor of Business Administration

Jonathan Eastwood
Jonathan Eastwood

Jonathan Eastwood

Department Head, Sociology and Anthropology; Professor of Sociology

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.

Bright Frimpong
Bright Frimpong

Bright Frimpong

Assistant Professor of Business Administration

Lingshu Hu
Lingshu Hu

Lingshu Hu

Assistant Professor of Business Administration

With a PhD in journalism focusing on computational methods and a graduate certificate in AI and Machine Learning, Professor Hu鈥檚 primary teaching interests include making data analytics accessible to students in the social sciences and helping students master storytelling skills with data analytics and visualization.

Keri M. Larson
Keri M. Larson

Keri M. Larson

Assistant Professor of Business Administration

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.

Sybil Prince Nelson
Sybil Prince Nelson

Sybil Prince Nelson

Assistant Professor of Mathematics

Prince Nelson 鈥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.

Holly Shablack
Holly Shablack

Holly Shablack

Assistant Professor of Cognitive and Behavioral Science

Shablack鈥檚 courses include Heath Psychology, Introduction to Data Science: Trends over time, and Emotions, Language, and Culture. Her research examines how our language and various socio-cultural factors influence our attitudes, emotions, physical and mental health, and behavior.

Natalia Toporikova
Natalia Toporikova

Natalia Toporikova

Associate Professor of Biology

Professor Toporikova鈥檚 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.

Gregg Whitworth
Gregg Whitworth

Gregg Whitworth

Associate Professor of Biology

Whitworth鈥檚 courses include Data Science: Visualizing and Exploring Big Data and The Molecular Mechanics of Life.

Jeff Barry
Cody Watson
Justin Davis
Jonathan Eastwood
Bright Frimpong
Lingshu Hu
Keri M. Larson
Sybil Prince Nelson
Holly Shablack
Natalia Toporikova
Gregg Whitworth
Dan Johnson