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Department of Information Science & Systems

Data Analytics and Visualization

M.S. in Data Analytics and Visualization

The M.S. in Data Analytics and Visualization program is transdisciplinary and will enable students from diverse undergraduate backgrounds as well as working professionals in diverse industries to advance their knowledge in data analytics and data visualization. 

Students will learn to manage and manipulate data, design data visualization schemas with end-user experience in mind, and make strategic data-driven decisions to influence organizations and communities by getting hands-on experience with a range of analytical tools. The program offers students the opportunity to take: 1) 9 credits in one of several tracks, 2) work on an experiential project in the track. The goal of the program to engage students and working professionals from a wide variety of industries and backgrounds.

The program is 30 credits and will be delivered on-campus and in an online format (at a later date),  to be completed in 12-months duration. 

This new program is designed for students who have completed a bachelor’s degree program and are interested in furthering their careers within their discipline by picking up the theory, tools, methodologies, and processes for data analytics and data visualization which are in high demand. The program will also meet the needs of working professionals who wish to update or improve their knowledge of data analytics and data visualization and apply best practices into their current roles.  Finally, the program also aims to provide a platform for a growing population of students who are under-represented minorities (URM) to advance their skills necessary for attaining better opportunities in complex and rapidly evolving technological environments. Graduates will be prepared for specialized jobs with focus on an area of emerging technology, involving cutting edge aspects of data analytics and visualization that are fundamentally important and practically relevant to almost all industries. The program will prepare students to enter the local, national, and global workforce as leaders and innovators. 

Program Objectives:

Enterprise Strategy: Graduates will learn data collection and preparation methodologies including identifying relevant data sources, preparing data for analytics, and automating the data preparation process.  They will understand the strengths and limitations on various analytical approaches as well as the environmental, social, and ethical impact these approaches can have on the integrity of operational, tactical and strategic decisions. 

Tools and Methods: Graduates will gain an in-depth understanding of established and state-of-the-art statistical modeling, machine learning, and artificial intelligence techniques, and will gain advanced proficiency in applying state-of-the-art data engineering and software skills to support a variety of analytics applications.

Communication:  Building effective leadership and communication skills which includes developing impactful, practical solutions and understanding the marriage between business and analytics strategy

Experiential Learning: Engage in an experiential learning project working with real data sets provided by our industry partners and demonstrating the ability to curate data, model, analyze, and demonstrate teamwork and project management skills.


  • Total Credit Hours: 30
  • Degree: MS in Data Analytics and Visualization

Courses: 30 credits (15 core credits, 6 core credits electives, 2 professional development courses of 0 credits each, and 9 electives credits to be taken in a track)

  • Core Courses: 12 credits
  • Core Elective Courses 6 credits
  • Elective Track 9 credits
  • Core Track Capstone 3 credits
  • Professional Development 0 credits                         

Estimated Time to Complete the Degree:

One year or 12-months (online or face-to-face). The estimated time can be more flexible for those who study part-time or want to take a traditional approach with a slower pace.

Prerequisites/Admission Requirements:

  1. Minimum GPA and application requirements of the School of Graduate Studies determined by the program director
  2. BS/BA degree in any discipline from an accredited program.

Course Requirements:

Core Courses (12 credits):

One must complete, with a grade of “B” or higher:

  • COSC 615 Data Wrangling for Visualization (3 credits)
  • INSS 694 Data Visualization (3 credits)
  • IEGR 661 Data Engineering and Governance (3 credits)
  • PROJ 600 Project Management (3 credits)

Core Elective Courses (6 credits):

  • Statistics (3 credits) Choose one of: PSYM 560 - Principles and Foundations of Statistical Methods; INSS.586 Quantitative and Statistical Analysis; ECON 513 - Statistical Analysis; SOCI 510 - Social Statistics; OMPH/PUBH 501 - Statistical Methods in Public Health; TRSP 603 - Quantitative Methods in Transportation; EEGR 507 - Applied Probability and Statistical Analysis; IEGR 534 - Engineering Statistics & Modeling; MATH 512 - Probability and Statistics
  • Machine Learning (3 credits) Choose one of: IEGR 555 - Artificial Intelligence Programming; CEGR 636 - Artificial Neural Networks I; EEGR 565 - Machine Learning Applications; INSS 698 – Artificial Intelligence for Decisions

 Electives (9 credits) - Choose one of the Tracks

      • Track in Business and Economics, with graduate courses, in one or more of the following disciplines:
        • Human Resources
        • Marketing
        • Supply Chain
        • FinTech
        • Economics
        • Project Management
        • Information Systems
        • Accounting
        • Hospitality Management
      • Track in Science, with graduate courses in one or more of the following disciplines:
        • Mathematics
        • Biology
        • Chemistry
        • Physics
      • Track in Computer Science, with graduate courses in one or more of the following disciplines:
        • Bioinformatics
        • Advanced Computing
      • Track in Healthcare, with graduate courses in one or more of the following disciplines:
        • Public Health
        • Nursing
      • Track in Engineering, with graduate courses in one or more of the following disciplines:
        • Electrical and Computer Engineering
        • Industrial and Systems Engineering
        • Civil Engineering
        • Urban Transportation
      • Track in City and Regional Planning
      • Track in Social Sciences, with graduate courses in one or more of the following disciplines:
        • Psychometrics
        • Sociology
        • Social Work
        • African-American Studies
        • Museum Studies and Historical Preservation
      • Other Tracks - new gradaute programs offered at Morgan State University

Core Capstone from a Track (3 credits)

  • INSS 699: Data Analytics Capstone Project.

Professional Development (0 credits)

  • BUAD 600 - Design your Life (Semester 1)
  • BUAD 601 - Professional Development Series (Semester 2)