Program Overview

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.

Course List

The following courses are required for the Data Science Major, B.A.:

• Foundations of Data and Information (two courses):
  • DATA 110: Introduction to Data Science H (3 hours)
  • Select one of the following options: (3 hours)
    • DATA 130: Critical Data Literacy
    • ENGL 480: Digital Humanities History and Methods
    • ENGL 482: Metadata, Mark-up, and Mapping: Understanding the Rhetoric of Digital Humanities
    • INLS 201: Foundations of Information Science
    • SOCI 318: Computational Sociology
• Responsible Data Science (one course):
  • DATA 120: Ethics of AI and Societal Decision Making H (3 hours)
• Computational Thinking (two courses):
  • COMP 110: Introduction to Programming H (3 hours)
  • or COMP 116: Introduction to Scientific Programming
  • DATA 140: Introduction to Data Structures and Management (3 hours)
• Mathematical and Statistical Foundations (four courses):
  • MATH 210: Mathematical Tools for Data Science (3 hours)
  • or MATH 347: Linear Algebra for Applications
  • MATH 231: Calculus of Functions of One Variable I H, F (4 hours)
  • STOR 120: Foundations of Statistics and Data Science H, F (4 hours)
  • STOR 320: Methods and Models of Data Science (3-4 hours)
  • or STOR 455: Methods of Data Analysis
• Communication (select one course from the following options): (3 hours)
  • COMM 113: Public Speaking
  • COMM 171: Argumentation and Debate
  • DATA 150: Communication for Data Scientists
  • ENGL 119: Picture This: Principles of Visual Rhetoric
  • ENGL 303: Scientific and Technical Communication
  • ENGL 411: Composing for Clients: Technical Communication Practicum
  • GEOG 115: Maps: Geographic Information from Babylon to Google
  • GEOG 415: Communicating Important Ideas
  • INLS 541: Information Visualization
  • MEJO 102: Future Vision: Exploring the Visual World
• Four additional courses from a concentration area (see below) (12 hours)

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.

• MEJO 487: Intermediate Interactive Media 1 (3 hours)
• MEJO 570: Data Driven Journalism (3 hours)
• Select one of the following options: (3 hours)
  • GEOG 215: Introduction to Spatial Data Science
  • LING 460: Making Sense of Big Data: Textual Analysis with R
  • POLI 209: Analyzing Public Opinion H
  • STOR 538: Sports Analytics 1
• Select one of the following options: (3 hours)
  • MEJO 459: Community Journalism 1
  • MEJO 553: Advanced Reporting 1
  • MEJO 625: Media Hub H
  • MEJO 630: Business News Wire H

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.

• ECON 370: Economic Applications of Data Science 1 (3 hours)
• ECON 400: Introduction to Data Science and Econometrics 1, H (4 hours)
• ECON 470: Econometrics 1, H (3 hours)
• Select one of the following options: (3 hours)
  • ECON 423: Financial Markets and Economic Fluctuations 1, H
  • ECON 425: Financial Economics 1
  • ECON 445: Industrial Organization 1
  • ECON 450: Health Economics: Problems and Policy 1
  • ECON 480: Labor Economics 1
  • ECON 522: Macroeconomic Analysis of the Labor Market 1
  • ECON 525: Advanced Financial Economics 1
  • ECON 545: Advanced Industrial Organization 1
  • ECON 550: Advanced Health Econometrics 1
  • ECON 551: Economics of Education 1
  • ECON 552: The Economics of Health Care Markets and Policy 1
  • ECON 571: Advanced Econometrics 1
  • ECON 573: Machine Learning and Econometrics 1
  • ECON 575: Applied Time Series Analysis and Forecasting 1
  • ECON 580: Advanced Labor Economics 1

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 course 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.

• LING 401: Introduction to Computational Linguistics 1 (3 hours)
• LING 460: Making Sense of Big Data: Textual Analysis with R (3 hours)
• LING 540: Mathematical Linguistics 1 (3 hours)
• Select one of the following options: (3 hours)
  • LING 225: Busting Language Myths
  • LING 520: Linguistic Phonetics

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.

• Select one of the following options: (3 hours)
  • PLAN 246: Cities of the Past, Present, and Future: Introduction to Planning
  • PLAN 247: Solving Urban Problems
  • PLAN 256: Planning the City: Possibilities, Participants, and Change
  • PLAN 257: Tools for Urbanists
  • PLAN 714: Urban Spatial Structure 1
• PLAN 562: Seminar on The Ethics and Politics of New Urban Analytics (3 hours)
• Select one of the following options: (3 hours)
  • PLAN 372: Introduction to Urban Data Analytics
  • PLAN 672: Urban Data Analytics
• Select one of the following options: (3 hours)
  • PLAN 591: Applied Issues in Geographic Information Systems
  • PLAN 635: Energy Modeling for Environment and Public Health
  • PLAN 636: Urban Transportation Planning
  • PLAN 637: Public Transportation
  • PLAN 671: Development Planning Techniques
  • PLAN 720: Planning Methods 1
  • PLAN 739: Transportation Planning Models 1
  • PLAN 745: Development Impact Assessment 1

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.

• SOCI 251: Research Methods (3 hours)
• Select three of the following options: (9 hours)
  • MNGT 345: Public Policy Toward Business
  • MNGT 380: The Economics of Labor Relations
  • SOCI 121: Population Problems
  • SOCI 172: Introduction to Population Health in the United States
  • SOCI 252: Data Analysis
  • SOCI 277: Societies and Genomics
  • SOCI 302: Fieldwork in Entrepreneurship
  • SOCI 427: The Labor Force
  • SOCI 429: Religion and Society

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.

• Select four of the following options: (12 hours)
  • COMM 83: First-Year Seminar: Networked Societies (first-year students only)
  • COMM 86: First-Year Seminar: Surveillance and Society (first-year students only)
  • COMM 249: Introduction to Communication Technology, Culture, and Society
  • COMM 348: Algorithms and Society
  • COMM 360: Social Media and Society
  • COMM 453: The History of New Media Technology in Everyday Life
  • COMP 380: Technology, Ethics, & Culture H
  • MEJO 242: From Gutenberg to Google: A History of Media
  • HIST 322: Technology and American Culture
  • HIST 328: History of the Computer

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.

• GEOG 215: Introduction to Spatial Data Science (3 hours)
• GEOG 370: Introduction to Geographic Information (3 hours)
• Select two of the following options: (6 hours)
  • GEOG 391: Quantitative Methods in Geography
  • GEOG 410: Modeling of Environmental Systems
  • GEOG 456: Geovisualizing Change
  • GEOG 477: Introduction to Remote Sensing of the Environment
  • GEOG 491: Introduction to GIS
  • GEOG 541: GIS in Public Health
  • GEOG 544: Geographic Information Systems for Impact Evaluation and Health Studies
  • GEOG 555: Cartography of the Global South
  • GEOG 567: Geospatial Data Analysis with Google Earth Engine
  • GEOG 577: Advanced Remote Sensing
  • GEOG 591: Applied Issues in Geographic Information Systems
  • GEOG 592: Geographic Information Science Programming

Department Programs

Major

• Data Science Major, B.A.
• Statistics and Analytics Major, B.S.

Minor

• Data Science Minor
• Statistics and Analytics Minor

Graduate Programs

• M.S. in Statistics, Analytics, and Data Science (STANDS)
• Ph.D. in Statistics and Operations Research

Courses

• Statistics and Operations Research (STOR)