The program requires 51-59 credits. Guidance on course sequence requirements can be found here.

Benchmarks

Each track requires a discipline-specific statistics course and 2-3 courses introducing students to the discipline. (See tracks below for specific courses).

Core Courses and Capstone

All students take foundational courses in programming, statistics, mathematics, and data science, as well as upper-level courses in database design, data privacy and security, ethics, data sources and manipulation, data visualization, survey fundamentals, and questionnaire design. Students finish the program by completing a required project-based learning capstone. 

BSOS233: Data Science for the Social Sciences 

An introduction to modern methods of data analysis for social scientists. This course emphasizes teaching students who have no previous coding experience how to analyze data and extract meaning in a social science context. Students will gain critical programming skills and learn inferential thinking through examples and projects with real-world relevance.

INST326 or BSOS326 or GEOG376: Object-Oriented Programming
Python has become the most powerful programming language in advanced statistics and data analytics. It includes expansive packages for data handling and processing, including the latest developments in machine learning, and offers Integrated Development Environments (IDE) for code development, testing, debugging, and graphical representation. In addition, python is deployed on virtually all high performance computing clusters, taking advantage of multi-processing, large memory, and GPU enhanced computing environments. These courses offer a thorough introduction to python, with the option to specialize in either program design (INST326), data science (BSOS326), or geographic information systems (GEOG376).

INST327: Database Design and Modeling
Introduction to databases, the relational model, entity-relationship diagrams, user-oriented database design and normalization, and Structured Query Language (SQL). Through labs, tests, and a project, students develop both theoretical and practical knowledge of relational database systems.

INST366: Privacy, Security and Ethics for Big Data
Evaluates major privacy and security questions raised by big data, Internet of things (IoT), wearables, ubiquitous sensing, social sharing platforms, and other AI-driven systems. Covers history of research ethics and considers how ethical frameworks can and should be applied to digital data.

INST414: Data Science Techniques
An exploration of how to extract insights from large-scale datasets. The course will cover the complete analytical funnel from data extraction and cleaning to data analysis and insights interpretation and visualization. The data analysis component will focus on techniques in both supervised and unsupervised learning to extract information from datasets. Topics will include clustering, classification, and regression techniques. Through homework assignments, a project, exams and in-class activities, students will practice working with these techniques and tools to extract relevant information from structured and unstructured data.

INST447: Data Sources and Manipulation
Examines approaches to locating, acquiring, manipulating, and disseminating data. Imperfection, biases, and other problems in data are examined, and methods for identifying and correcting such problems are introduced. The course covers other topics such as automated collection of large data sets, and extracting, transforming, and reformatting a variety of data and file types.

INST462: Introduction to Data Visualization
Exploration of the theories, methods, and techniques of visualization of information, including the effects of human perception, the aesthetics of information design, the mechanics of visual display, and the semiotics of iconography.

SURV400: Fundamentals of Survey and Data Science
The course introduces the student to a set of principles of survey and data science that are the basis of standard practices in these fields. The course exposes the student to key terminology and concepts of collecting and analyzing data from surveys and other data sources to gain insights and to test hypotheses about the nature of human and social behavior and interaction. It will also present a framework that will allow the student to evaluate the influence of different error sources on the quality of data.

SURV430: Fundamentals of Questionnaire Design
Introduction to the scientific literature on the design, testing and evaluation of survey questionnaires, together with hands-on application of the methods discussed in class.

INST492: Capstone
The capstone provides a platform for students where they can apply a subset of the concepts, methods, and tools they learn as part of the Information Science program to addressing an information problem or fulfilling an information need.

 

Track Courses

Students also take a set of track courses in a discipline that include upper-level method and theory courses, and a set of restricted electives that will allow students to deepen their knowledge of the discipline and apply data science principles to social science research and practice. Additional tracks will be added over time. 

Course Sequence Requirements

Minimum MATH & STAT (6 credits)

  • STAT100: Elementary Statistics and Probability
  • MATH115: Precalculus

Benchmark I (3 credits)

  • INST126: Introduction to Programming for Information Science or GEOG276: Principles of Python Programming and Geocomputing

Benchmark 2 (6 credits)

  • AASP101: Public Policy and the Black Community
  • AASP210: Intro to Research Design and Analysis in African American Studies

Track I Courses (3 credits)

  • AASP395: Fundamentals of Quantitative Research in Socio-Cultural Perspective

Track II Courses (9 credits)

Choose 9 credits from:

  • AASP301: Applied Policy Analysis and the Black Community
  • AASP310: African Slave Trade
  • AASP313: Black Women in United States History
  • AASP314: The Civil Rights Movement
  • AASP400: Directed Readings in African American Studies
  • AASP402: Classic Readings in African American Studies
  • AASP411: Black Resistance Movements
  • AASP441: Science, Technology, and the Black Community 
  • AASP443: Blacks and the Law
  • AASP449: 

 

For more information about African American Studies courses at the University of Maryland, please visit the 2021 - 2022 Catalog.

Course Sequence Requirements

Minimum MATH & STAT (6 credits)

  • STAT100: Elementary Statistics and Probability
  • MATH115: Precalculus

Benchmark I (3 credits)

  • INST126: Introduction to Programming for Information Science or GEOG276: Principles of Python Programming and Geocomputing

Benchmark 2 (6-7 credits)

  • ANTH210: Introduction to Medical Anthropology and Global Health or ANTH220: Introduction to Biological Anthropology or ANTH240: Introduction to Archaeology
  • INST314: Statistics for Information Science

Track I Courses (3 credits)

  • ANTH310: Method & Theory in Medical Anthropology and Global Health or ANTH322: Method and Theory in Ecological Anthropology or ANTH340: Method and Theory in Archaeology

Track II Courses (9 credits)

Choose 9 credits from one of the following groups:

Group 1 - Health

  • ANTH411: Anthropology of Immigration and Health
  • ANTH412: Hypermarginality and Urban Health
  • ANTH413: Health Disparities in the United States 
  • ANTH415: Advanced Studies in Global Health
  • ANTH416: Anthropology of Global Violence

Group 2 - Heritage

  • ANTH341: Introduction to Zooarchaeology
  • ANTH440: Theory and Practice of Historical Archaeology
  • ANTH441: Archaeology of Diaspora
  • ANTH447: Material Culture Studies in Archaeology
  • ANTH448: Special Topics in Archaeology
  • ANTH451: Environmental Archaeology
  • ANTH464: Anthropology of Cultural Heritage
  • ANTH496: Field Methods in Archaeology

Group 3 - Environment

  • ANTH450: Theory and Practice of Environmental Anthropology
  • ANTH454: Political Ecology
  • ANTH456: Conservation and Indigenous People in South America
  • ANTH462: Amazon Through Film
  • ANTH467: Researching Environment and Culture

Capstone

  • INST492: Integrated Capstone for Social Data Science

 

* ANTH Benchmark course will guide a student's choice of Track I and Track II courses in Health, Heritage, or Environment.

 

For more information about Anthropology courses at the University of Maryland, please visit the 2021 - 2022 Catalog.

Course Sequence Requirement

Minimum MATH & STAT (6 credits)

  • STAT100: Elementary Statistics and Probability
  • MATH120: Elementary Calculus I

Benchmark I (3 credits)

  • INST126: Introduction to Programming for Information Science or GEOG276: Principles of Python Programming and Geocomputing

Benchmark 2 (9 credits)

  • ECON200: Principles of Microeconomics
  • ECON201: Principles of Macroeconomics
  • ECON230: Applied Economic Statistics

Track I Courses (3 credits)

  • ECON305: Intermediate Macroeconomic Theory and Policy or ECON306: Intermediate Microeconomic Theory & Policy

Track II Courses (6 credits)

Choose 6 credits from:

  • ECON305: Intermediate Macroeconomic Theory and Policy or ECON306: Intermediate Microeconomic Theory & Policy
  • ECON311: American Economic History Before the Civil War
  • ECON312: American Economic History After the Civil War
  • ECON315: Economic Development of Underdeveloped Areas
  • ECON317: Global Economic Policies
  • ECON330: Money and Banking
  • ECON340: International Economics

Capstone

  • INST492: Integrated Capstone for Social Data Science

 

** Course may only count as Track I or Track II. It may not double-count.

 

For more information about Economics courses at the University of Maryland, please visit the 2021 - 2022 Catalog.

Course Sequence Requirements

Minimum MATH & STAT (6 credits)

  • STAT100: Elementary Statistics and Probability
  • MATH120: Elementary Calculus I

Benchmark I (3 credits)

  • INST126: Introduction to Programming for Information Science or GEOG276: Principles of Python Programming and Geocomputing

Benchmark 2 (6 credits)

  • GEOG202: Introduction to Human Geography
  • GEOG306: Introduction to Quantitative Methods for the Geographical Environmental Sciences

Track I Courses (3 credits)

  • GEOG373: Geographic Information Systems

Track II Courses (9 credits)

Choose 9 credits, including 6 credits from 400-level, from:

  • GEOG330: As the World Turns: Society and Sustainability in a Time of Great Change
  • GEOG331: Introduction to Human Dimensions of Global Change
  • GEOG332: Economic Geography
  • GEOG333: The Social Geography of Metropolitan Areas in Global Perspective
  • GEOG335: Population Geography
  • GEOG415: Land Use, Climate Change, and Sustainability
  • GEOG416: Conceptualizing and Modeling Human-Environmental Interactions
  • GEOG421: Changing Geographies of China 
  • GEOG422: Changing Geographies of Sub-Saharan Africa
  • GEOG432: Spatial Econometrics
  • GEOG470: Spatial Data Algorithms
  • GEOG473: Geographic Information Systems and Spatial Analysis
  • GEOG475: Computer Cartography
  • GEOG477: Mobile GIS Development

Capstone

  • INST492: Integrated Capstone for Social Data Science

 

For more information about Geographical Sciences & GIS courses at the University of Maryland, please visit the 2021 - 2022 Catalog.

Course Sequence Requirements

Minimum MATH & STAT (6 credits)

  • STAT100: Elementary Statistics and Probability
  • MATH115: Precalculus

Benchmark I (3 credits)

  • INST126: Introduction to Programming for Information Science or GEOG276: Principles of Python Programming and Geocomputing

Benchmark 2 (9 credits)

  • GVPT170: American Government
  • GVPT200: International Political Relations
  • GVPT201: Scope and Methods for Political Science Research

Track I Courses (3 credits)

  • GVPT320: Advanced Empirical Research

Track II Courses (6 credits)

Choose 6 credits from any 300- or 400-level course

Capstone

  • INST492: Integrated Capstone for Social Data Science

For more information about Government & Politics & International Relations courses at the University of Maryland, please visit the 2021 - 2022 Catalog.

Course Sequence Requirements

Minimum MATH & STAT (6 credits)

  • STAT100: Elementary Statistics and Probability
  • MATH120: Elementary Calculus I

Benchmark I (3 credits)

  • INST126: Introduction to Programming for Information Science or GEOG276: Principles of Python Programming and Geocomputing

Benchmark 2 (6 credits)

  • PSYC100: Introduction to Psychology
  • PSYC200: Statistical Methods in Psychology

Track I Courses (3 credits)

  • PSYC300: Research Methods in Psychology Laboratory

Track II Courses (9 credits)

Choose 9 credits from:

  • PSYC330: Child Psychopathology
  • PSYC332: Psychology of Human Sexuality
  • PSYC334: Psychology of Interpersonal Relationships
  • PSYC336: Psychology of Women
  • PSYC341: Introduction to Memory and Cognition
  • PSYC344: Health Psychology
  • PSYC353: Adult Psychopathology
  • PSYC354: Multicultural Psychology in the U.S.
  • PSYC355: Developmental Psychology
  • PSYC356: Psychology of Adolescence
  • PSYC361: Survey of Industrial and Organizational Psychology
  • PSYC362: Introduction to Negotiation
  • PSYC416: Development of Attachment in Infancy and Childhood: Theory, Research, Methods, and Clinical Implications
  • PSYC417: Data Science for Psychology and Neuroscience Majors
  • PSYC420: Experimental Psychology: Social Psychology Laboratory
  • PSYC424: Communication and Persuasion
  • PSYC425: Psychology and Law
  • PSYC432: Counseling Psychology: Theories, Research, and Practice
  • PSYC435: Temperament, Personality, and Psychopathology
  • PSYC436: Introduction to Clinical Psychology: From Science to Practice
  • PSYC437: The Assessment and Treatment of Addictive Behaviors
  • PSYC440: Experimental Psychology: Cognitive Processes and Legal Applications
  • PSYC450: Applying Psychology to the Workplace: Industrial Organizational Psychology Laboratory
  • PSYC456: Research Methods in Developmental Psychology Laboratory
  • PSYC460: Psychological Foundations of Personnel Selection and Training 

Capstone

  • INST492: Integrated Capstone for Social Data Science

 

For more information about Psychology courses at the University of Maryland, please visit the 2021 - 2022 Catalog.

 

Course Sequence Requirements

Minimum MATH & STAT (6 credits)

  • STAT100: Elementary Statistics and Probability
  • MATH115: Precalculus

Benchmark I (3 credits)

  • INST126: Introduction to Programming for Information Science or GEOG276: Principles of Python Programming and Geocomputing

Benchmark 2 (6 credits)

  • SOCY100: Introduction to Sociology
  • SOCY201: Introductory Statistics for Sociology

Track I Courses (3 credits)

  • SOCY202: Introduction to Research Methods in Sociology

Track II Courses (9 credits)

Choose 9 credits from:

  • SOCY325: The Sociology of Gender
  • SOCY335: Sociology of Health and Illness
  • SOCY401: Intermediate Statistics for Sociologists
  • SOCY405: Scarcity and Modern Society
  • SOCY406: Globalization
  • SOCY407: Explaining Social Change: Historical and Comparative Methods
  • SOCY410: Social Demography
  • SOCY411: Demographic Techniques
  • SOCY412: Family Demography
  • SOCY413: Sociology of Aging
  • SOCY415: Environmental Sociology
  • SOCY420: Qualitative Research Methods in Sociology
  • SOCY430: Social Structure and Identity
  • SOCY431: Principles of Organizations
  • SOCY432: Social Movements
  • SOCY441: Social Stratification and Inequality
  • SOCY442: The Black Middle Class
  • SOCY444: Sociology of Children
  • SOCY445: Sex and Love in Modern Society
  • SOCY457: Sociology of Law
  • SOCY464: Military Sociology
  • SOCY465: The Sociology of War
  • SOCY467: Sociology of Education
  • SOCY480: Researching the Middle East
  • SOCY490: Experimental Research Practicum
  • SOCY491: Experimental Research Design

Capstone

  • INST492: Integrated Capstone for Social Data Science

 

For more information about Sociology courses at the University of Maryland, please visit the 2021 - 2022 Catalog.

Course Sequence Requirements

Minimum MATH & STAT (6 credits)

  • STAT100: Elementary Statistics and Probability
  • MATH120: Elementary Calculus I

Benchmark I (3 credits)

  • INST126: Introduction to Programming for Information Science or GEOG276: Principles of Python Programming and Geocomputing

Benchmark 2 (9 credits)

  • SPHL100: Foundations of Public Health
  • EPIB301: Epidemiology for Public Health Practice
  • EPIB315: Biostatistics for Public Health Practice

Track I Courses (3 credits)

  • HLTH200

Track II Courses (9 credits)

Choose 9 credits from:

  • EPIB330: Introduction to Infectious Disease Epidemiology
  • EPIB400: Obesity: An Epidemiologic Perspective
  • EPIB463:  Introduction to Biostatistical Programming
  • FMSC310: Maternal, Child and Family Health
  • FMSC332: Children in Families
  • FMSC460: Violence in Families 
  • HLSA300: Introduction to Health Policy and Services
  • HLSA465: Redesigning Mental Health Services
  • HLSA484: Redesigning Health Care: Developing a Clinic to Meet Community Needs
  • HLTH424: Lesbian, Gay, Bisexual & Transgender Health
  • HLTH434: Introduction to Public Health Informatics
  • HLTH377: Human Sexuality
  • KNES400: The Foundations of Public Health in Kinesiology
  • KNES401: Zip Code: Prediction of Physical Activity & Health 
  • MIEH240: Global Health Projects: Addressing Health Needs with a focus on Reciprocity and Relationships
  • MIEH400: Introduction to Global Health
  • PHSC401: History of Public Health
  • PHSC412: Food, Policy, and Public Health

Capstone

  • INST492: Integrated Capstone for Social Data Science

 

Courses for the Public Health Track are spread over several departments. For more information, visit the the respective department's 2021 - 2022 Catalog page.

EPIB - Epidemiology and Biostatistics

FMSC - Family Science

HLSA - Health Services Administration

HLTH - Health

KNES - Kinesiology

MIEH - Maryland Institute for Applied Environmental Health

PHSC - Public Health Science