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 | ||
| Foundations of Data and Information (two courses): | ||
| DATA 110 |  Introduction to Data Science H | 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 | ||
| Responsible Data Science (one course): | ||
| DATA 120 | Ethics of AI and Societal Decision Making H | 3 |
| Computational Thinking (two courses): | ||
| COMP 110 | Introduction to Programming H | 3 |
| or COMP 116 | Introduction to Scientific Programming | |
| DATA 140 | Introduction to Data Structures and Management | 3 |
| Mathematical and Statistical Foundations (four courses): | ||
| MATH 210 | Mathematical Tools for Data Science | 3 |
| or MATH 347 | Linear Algebra for Applications | |
| MATH 231 | Calculus of Functions of One Variable I H, F | 4 |
| STOR 120 | Foundations of Statistics and Data Science H, F | 4 |
| STOR 320 | Methods and Models of Data Science | 3-4 |
| or STOR 455 | Methods of Data Analysis | |
| Communication (select one course from the following options): | 3 | |
| Public Speaking | ||
| Argumentation and Debate | ||
| Communication for Data Scientists | ||
| Picture This: Principles of Visual Rhetoric | ||
| Scientific and Technical Communication | ||
| Composing for Clients: Technical Communication Practicum | ||
| Maps: Geographic Information from Babylon to Google | ||
| Communicating Important Ideas | ||
| Information Visualization | ||
| Future Vision: Exploring the Visual World | ||
| Four additional courses from a concentration area (see below) | 12 | |
| Total Hours | 44-45 | |
| 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. |
Concentrations
Data Journalism
This concentration equips students to understand how to employ data science to find and tell hidden stories that inform the public discourse, civic life and democracy. Students will learn how to acquire, clean, analyze and present data in multiple media simply and clearly for a general audience of citizens. The concentration combines foundational data science competencies with multimedia web development, data visualization and news reporting skills and ethics to prepare students to meet the increasingly complex and quantitative needs required by professional journalists.
| Code | Title | Hours |
|---|---|---|
| MEJO 487 | Intermediate Interactive Media 1 | 3 |
| MEJO 570 | Data Driven Journalism | 3 |
| Select one of the following options: | 3 | |
| Introduction to Spatial Data Science | ||
| Making Sense of Big Data: Textual Analysis with R | ||
| Analyzing Public Opinion H | ||
| Sports Analytics 1 | ||
| Select one of the following options: | 3 | |
| Community Journalism 1 | ||
| Advanced Reporting 1 | ||
| Media Hub H | ||
| Business News Wire H | ||
| 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. |
- 1
Course requires a prerequisite(s) not otherwise counting in the major. Please review prerequisite information carefully when planning your course selection.
Economic Analysis
This concentration prepares students for careers in quantitatively focused occupations at the intersection of economics and data science. The courses offer a rigorous foundation for econometric and data-science methodologies commonly used in economic analysis, as well as requiring an understanding of the application of these methods in at least one field within economics.
| Code | Title | Hours |
|---|---|---|
| ECON 370 | Economic Applications of Data Science 1 | 3 |
| ECON 400 | Introduction to Data Science and Econometrics 1, H | 4 |
| ECON 470 | Econometrics 1, H | 3 |
| Select one of the following options: | 3 | |
| Financial Markets and Economic Fluctuations 1, H | ||
| Financial Economics 1 | ||
| Industrial Organization 1 | ||
| Health Economics: Problems and Policy 1 | ||
| Labor Economics 1 | ||
| Macroeconomic Analysis of the Labor Market 1 | ||
| Advanced Financial Economics 1 | ||
| Advanced Industrial Organization 1 | ||
| Advanced Health Econometrics 1 | ||
| Economics of Education 1 | ||
| The Economics of Health Care Markets and Policy 1 | ||
| Advanced Econometrics 1 | ||
| Machine Learning and Econometrics 1 | ||
| Applied Time Series Analysis and Forecasting 1 | ||
| Advanced Labor Economics 1 | ||
| Total Hours | 13 | |
| H | Honors version available. An honors course fulfills the same requirements as the nonhonors version of that course. Enrollment and GPA restrictions may apply. |
- 1
Course requires a prerequisite(s) not otherwise counting in the major. Please review prerequisite information carefully when planning your course selection.
Quantitative Language Science
This concentration explores how data-science methods including statistical, mathematical, and computational methods are applied to study theoretical language science/linguistics, and natural language processing. This courses will familiarize students with linguistic concepts in the context of data-science methodology and help prepare them for jobs or for further study in computational linguistics and AI.
| Code | Title | Hours |
|---|---|---|
| LING 401 | Introduction to Computational Linguistics 1 | 3 |
| LING 460 | Making Sense of Big Data: Textual Analysis with R | 3 |
| LING 540 | Mathematical Linguistics 1 | 3 |
| Select one of the following options: | 3 | |
| Busting Language Myths | ||
| Linguistic Phonetics | ||
| Total Hours | 12 | |
- 1
Course requires a prerequisite(s) not otherwise counting in the major. Please review prerequisite information carefully when planning your course selection.
Urban Data Analytics
This concentration equips students with the skills necessary to apply data science tools for the public good, specifically to improve the quality of life of people in human settlements.
| Code | Title | Hours |
|---|---|---|
| Select one of the following options: | 3 | |
| Cities of the Past, Present, and Future: Introduction to Planning | ||
| Solving Urban Problems | ||
| Planning the City: Possibilities, Participants, and Change | ||
| Tools for Urbanists | ||
| Urban Spatial Structure 1 | ||
| PLAN 562 | Seminar on The Ethics and Politics of New Urban Analytics | 3 |
| Select one of the following options: | 3 | |
| Introduction to Urban Data Analytics | ||
| Urban Data Analytics | ||
| Select one of the following options: | 3 | |
| Applied Issues in Geographic Information Systems | ||
| Energy Modeling for Environment and Public Health | ||
| Urban Transportation Planning | ||
| Public Transportation | ||
| Development Planning Techniques | ||
| Planning Methods 1 | ||
| Transportation Planning Models 1 | ||
| Development Impact Assessment 1 | ||
| Total Hours | 12 | |
- 1
Courses at the 700-level require permission of the instructor for undergraduate students to enroll.
Sociology
The sociology concentration 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 of the following options: | 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 concentration 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 of the following options: | 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 concentration 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 of the following options: | 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
- M.S. in Statistics, Analytics, and Data Science (STANDS)
- Ph.D. in Statistics and Operations Research
Courses
Department of Statistics and Operations Research
318 Hanes Hall, CB# 3260
(919) 843-6024
