The Catholic University of America
Cultural Heritage Course Study

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Course of Study
Data Science

Data science uses statistical and programming methods to extract knowledge from large amounts of data to support better insight into current trends and support more effective decision-making. Because the amount of data being produced in our society has grown tremendously, effective management and analysis of data sets has become more critical than ever before. It has been predicted that there will be growing demand for data science professionals in a wide variety of domains, including scientific research, government policymaking, and commercial marketing. This course of study prepares students for careers in all these domains as data analysts, data engineers, and data journalists.  In addtion, students could consider taking courses from this course of study to combine with other courses of study such as Cultural Heritage Information Management and Information Organization to become data managers, data librarians, data archivists, and data curators.

Data science is an interdisciplinary field that requires skills in specific subject areas, statistics, systems analysis, and programming. The expected skillsets emphasize the importance of skills such as data/text mining, big data analytics, statistics, data visualization, coding, and machine learning. The data science course of study at the CUA Department of Library and Information Science reflects these needs. In addition to the MSLIS program’s four required core courses, it is highly recommended that each student take the four data science specific courses, and select additional courses from the listed recommended elective courses to fulfil the requirements of the program. The student will consult with his/her advisor to plan a course of study that will best meet the student’s personal and professional needs.


Required Core Courses (4 courses; 12 credits)

  • 551: Organization of Information
  • 553: Information Sources & Services
  • 555: Information Systems in Libraries and Information Centers
  • 557: The Information Professions in Society

Highly Recommended Courses (4 courses; 12 credits)

  • 527: Introduction to Data Science
  • 753: Programming for Web Application
  • 653: Data on the Web
  • Data Visualization [new course, tentatively planned for Spring 2019]

Recommended Elective Courses (4 courses; 12 credits)

  • 637: Government Data and Information
  • 638: E-science and Technology Information
  • 654: Database Management
  • 675: Research Methods in Library and Information Science
  • 850: Digital Humanities
  • 695: Practicum
  • A graduate course on advanced statistics from other Department (e.g., Education, Business Analysis from Business School, Psychology in Human Factors)
  • A graduate course on computing from Computer Science (e.g., CSC584 Introduction to Machine Learning; CSC641 Data Mining)

Relevant Journals or Online Resources

Page updated on May 2018

 Cultural Heritage Course Study

Full List of LIS Courses of Study

Digital Libraries Course Study