Prepare For an Exciting Career

The Master of Science in Data Analytics online program is designed for working professionals and students requiring scheduling flexibility.

At the Catholic University of America, the Data Analytics program is offered fully online to meet the diverse needs of students. The online format also features a capstone practicum projects that emphasize real-world data challenges, ensuring graduates are workforce-ready.

30

Credits to complete the degree

$1,385

Per credit hour

3

Semesters to complete the degree

  

 

What to Expect

This program meets workforce expectations by equipping graduates with essential skills and competencies, including:

  • Applying Advanced Analytical & Machine Learning Techniques - Graduates will be able to design, implement, and evaluate predictive and prescriptive models using advanced statistical methods and machine learning algorithms to both structured and unstructured datasets.
  • Utilizing Modern Tools & Technologies - Graduates will demonstrate proficiency in Python programming, data visualization platforms (e.g., Tableau), database systems (e.g., SQL), and cloud-based analytics environments to build scalable, data-driven solutions.
  • Leading End-to-End Data Analytics Projects - Graduates will manage full-cycle analytics projects, from problem scoping and data collection to model development and validation and stakeholder communication.
  • Critically Interpreting & Communicating Insights - Graduates will effectively present analytical results through written, visual, and oral formats tailored to technical and non-technical audiences, highlighting key assumptions, limitations, ethical considerations, and actionable insights.
The MSDA - Online offers the same rigorous curriculum and learning outcomes as the on-campus program but delivered through asynchronous and synchronous online formats. The online option enables students to balance their studies with professional and personal commitments while providing access to comprehensive remote support services.

  • Admissions Requirements

    • A bachelor’s degree
    • A completed online application
    • Official transcripts from previous colleges/universities
    • Students for whom English is a second language are required to submit Language Proficiency scores.

  • Curriculum

    The M.S. degree requires 30 credit hours, consisting of the 3 core courses, 6 elective courses, and a 3-credit capstone practicum selected from an approved set of challenge areas developed in partnership with industry, government, and civic organizations.

    Core Requirements (courses offered in both spring and fall semester)
    • DA 501: Introduction to Data Science and Python
    • DA 514: Applied Statistics and Data Analysis
    • DA 515: Introduction to Machine Learning
    Data Analysis Program Electives (courses offered either in spring or fall semester)
    • Introduction to Computer Vision
    • Introduction to Artificial Intelligence
    • Introduction to Neural Network
    • Introduction to Deep Learning 
    • Practices for Big Data
    • Business Data Analytics
    • Applications of Data Analytics and Development
    • Introduction to Database Management
    • Pattern Recognition
    • Data Visualization
    • Information Retrieval and Analysis
    • Internet of Things
    • Introduction to System Analysis
    • Introduction to Data Mining
    • Web Design and Programming
    • Data on the Web
    • Cloud Computing
    • Introduction to Information Privacy and Security
    • Healthcare Data Analytics
    • Introduction to Medical Image Computing
    • Government Data and Information
    • Data Ethics
    • Others
    Data Science and Analytics Practicum (DA 591)
    CUA and its industry partners are establishing focus areas that students will address in the practicum. The areas are selected to highlight the power of data and analysis in their solutions. In their final semester, students select one of the issue areas and a method of execution. Students currently working can choose issue areas related to the established set, but which are tailored to their work environment and use data sets supplied by their employer. Students will work throughout the semester in a professional project-like manner. They will submit project proposals, plan of action milestone charts, and time lines as part of the practicum. Students will have scheduled reviews at various points that will be held in conjunction with the industry partners. At the end of the semester, each student will give a 30-minute presentation on their project to a panel made up of CUA faculty and industry partners. Depending on the scope of the project, teams can be formed to address multiple aspects of the available data.