Data Science Major, B.A.
The bachelor of arts (B.A.) in data science provides students with high-level development of competencies in mathematics, statistics, computational foundations, ethics, and communication. The curriculum aims to go beyond basic competencies, providing opportunities to integrate analytic techniques across a broad variety of coursework, and allow students to customize the application of data science knowledge according to discipline-specific domain specializations.
Student Learning Outcomes
Upon completion of the data science program, students should be able to:
- Understand data sources and constructs, including the conceptual and technical foundations of representing, organizing, retrieving, and using data and information
- Understand and implement ethical practices in data collection, management, analysis, and reporting, including privacy, security, and governance of data
- Build and understand algorithms for analyzing data and accurate numerical modeling for problems
- Use appropriate data analytics and statistical techniques to discover new relationships, deliver insights into research problems or organizational processes, and support decision-making
- Convey data analyses through written and oral communication skills as well as visualization techniques
Requirements
In addition to the program requirements, students must
- earn a minimum final cumulative GPA of 2.000
- complete a minimum of 45 academic credit hours earned from UNC–Chapel Hill courses
- take at least half of their major core requirements (courses and credit hours) at UNC–Chapel Hill
- earn a minimum cumulative GPA of 2.000 in the major core requirements. Some programs may require higher standards for major or specific courses.
For more information, please consult the degree requirements section of the catalog.
| Code | Title | Hours |
|---|---|---|
| Core Requirements | ||
| DATA 110 |  Introduction to Data Science | 3 |
| DATA 120 | Ethics of Data Science and Artificial Intelligence | 3 |
| DATA 140 | Introduction to Data Structures and Management | 3 |
| Select one of the following options: | 3 | |
| Critical Data Literacy | ||
| Digital Humanities History and Methods | ||
| Metadata, Mark-up, and Mapping: Understanding the Rhetoric of Digital Humanities | ||
| Foundations of Information Science | ||
| Computational Sociology | ||
| Communications (select one): | 3 | |
| Public Speaking | ||
| Argumentation and Debate | ||
| Communication for Data Scientists | ||
| Picture This: Principles of Visual Rhetoric | ||
| Scientific and Technical Communication | ||
| Writing for Clients: Technical Communication Practicum | ||
| Maps: Geographic Information from Babylon to Google | ||
| Communicating Important Ideas | ||
| Information Visualization | ||
| Future Vision: Exploring the Visual World | ||
| STOR 320 | Introduction to Data Science | 4 |
| or STOR 455 | Methods of Data Analysis | |
| Four additional courses from a specialization area (see below) | 12 | |
| Additional Requirements | ||
| COMP 110 | Introduction to Programming and Data Science H | 3-4 |
| or COMP 116 | Introduction to Scientific Programming | |
| or STOR 120 | Foundations of Statistics and Data Science | |
| MATH 210 | Mathematical Tools for Data Science | 3 |
| MATH 231 | Calculus of Functions of One Variable I H, F | 4 |
| Total Hours | 41-42 | |
| H | Honors version available. An honors course fulfills the same requirements as the nonhonors version of that course. Enrollment and GPA restrictions may apply. |
| F | FY-Launch class sections may be available. A FY-Launch section fulfills the same requirements as a standard section of that course, but also fulfills the FY-SEMINAR/FY-LAUNCH First-Year Foundations requirement. Students can search for FY-Launch sections in ConnectCarolina using the FY-LAUNCH attribute. |
Specializations
Sociology
The sociology specialization enables students to understand how data, the analysis of data, and social scientific methodological approaches can be used to study people in society, including interpersonal dynamics, inequality, social structures, and cultural systems.
| Code | Title | Hours |
|---|---|---|
| SOCI 251 | Research Methods | 3 |
| Select three courses from the following list: | 9 | |
| Public Policy Toward Business | ||
| The Economics of Labor Relations | ||
| Population Problems | ||
| Introduction to Population Health in the United States | ||
| Data Analysis | ||
| Societies and Genomics | ||
| Fieldwork in Entrepreneurship | ||
| The Labor Force | ||
| Religion and Society | ||
| Total Hours | 12 | |
Data and Society
This specialization equips students to understand the social, cultural, historical, and political dimensions and impacts of data-driven technologies. Students will learn critical capacities to engage with and evaluate contemporary technologies, understand their histories, and map their social impacts.
| Code | Title | Hours |
|---|---|---|
| Select four courses from the following list: | 12 | |
| First-Year Seminar: Networked Societies (first-year students only) | ||
| First-Year Seminar: Surveillance and Society (fist-year students only) | ||
| Introduction to Communication Technology, Culture, and Society | ||
| Algorithms and Society | ||
| Social Media and Society | ||
| The History of New Media Technology in Everyday Life | ||
| Technology, Ethics, & Culture H | ||
| From Gutenberg to Google: A History of Media | ||
| Technology and American Culture | ||
| History of the Computer | ||
| Total Hours | 12 | |
| H | Honors version available. An honors course fulfills the same requirements as the nonhonors version of that course. Enrollment and GPA restrictions may apply. |
Geographic Information Science
This specialization equips students to understand fundamentals of GIScience concepts and build expert knowledge in the use of geospatial technologies such as GIS, remote sensing, spatial analysis and modeling, database development and management, programming, Web GIS, and geovisualization.
| Code | Title | Hours |
|---|---|---|
| GEOG 215 | Introduction to Spatial Data Science | 3 |
| GEOG 370 | Introduction to Geographic Information | 3 |
| Select two courses from the following list: | 6 | |
| Quantitative Methods in Geography | ||
| Modeling of Environmental Systems | ||
| Geovisualizing Change | ||
| Introduction to Remote Sensing of the Environment | ||
| Introduction to GIS | ||
| GIS in Public Health | ||
| Geographic Information Systems for Impact Evaluation and Health Studies | ||
| Cartography of the Global South | ||
| Geospatial Data Analysis with Google Earth Engine | ||
| Advanced Remote Sensing | ||
| Applied Issues in Geographic Information Systems | ||
| Geographic Information Science Programming | ||
| Total Hours | 12 | |
Department Programs
Major
Minor
Graduate Programs
Department of Statistics and Operations Research
318 Hanes Hall, CB# 3260
(919) 843-6024
Chair
Vladas Pipiras
