Flexible Online and On-Campus Learning Options

The M.S. degree requires 30 credit hours, consisting of the 3 core courses, 6 elective courses providing a deeper understanding of specific methods, tools, and specific areas of application, 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.