2025-2026

Computational and Applied Data Science, Master of Science

School of Informatics, Computing and Cyber Systems

Steve Sanghi College of Engineering

The data science market is growing at a rapid rate. Institutions ranging from healthcare to finance, government, and research are looking to hire data scientists. The Computational and Applied Data Science Master of Science program, offered by the School of Informatics, Computing, and Cyber Systems, provides opportunities for focused study in Data Science. Students will learn foundational and advanced techniques for data capture and cleaning, data warehousing and staging, data modeling and analytics, and data visualization. The program features a multidisciplinary curriculum that builds on the foundations of computer science, statistics, and database management, with real-world "Big Data" applications in bio-, eco-, and health-informatics.

  • To receive a master's degree at Northern Arizona University, you must complete a planned group of courses from one or more subject areas, consisting of at least 30 units of graduate-level courses. Many master's degree programs require more than 30 units.

    You must additionally complete:

    • All requirements for your specific academic plan(s). This may include a thesis.
    • All graduate work with a cumulative grade point average of at least 3.0.
    • All work toward the master's degree must be completed within six consecutive years. The six years begins with the semester and year of admission to the program.

     

    Individual degree programs may exceed the baseline University Policy for a master's degree. The program-specific requirements are provided on the Details tab below.

    Read the full policy here.

In addition to University Requirements:

  • Complete individual plan requirements.

You may be able to use some courses to meet more than one requirement. Contact your faculty mentor for details.

Minimum Units for Completion 30
Additional Admission Requirements Additional admission requirements over and above admission to NAU are recommended.
Research Individualized research may be required by chosen emphasis or offered as an option.
Some online/blended coursework Required
Progression Plan Link View Program of Study

Purpose Statement

The Data Science market is growing rapidly, with data playing an ever-increasing role in our society, controlling our social media consumption, informing our individual healthcare decisions and nationwide healthcare policies, helping set prices and financial policies, and much more. The Data Science discipline helps properly collect, store, manage, and analyze the petabytes of data collected by our modern world. It is at the root of most decisions U.S. companies, both large and small, make. At the same time, there is a shortage of workers with the skills to conduct data modeling, analytics, and visualization. According to the Bureau of Labor Statistics, the need for Data Scientists is projected to grow by 36 percent (much faster than average) within the next decade. 
 

The School of Informatics, Computing and Cyber Systems' new academic program will address this critical need in training Data Scientists and Data Analysts. The Master of Science in Computational and Applied Data Science is designed to educate data science analysts, engineers, and leaders. This program is designed for students with a STEM undergraduate degree or demonstrated strong preparation in STEM-related disciplines. This degree program teaches students to collect, manage, analyze, and visualize data to make informed decisions. Students will learn data science theory, work with real-world "Big Data", and use the latest tools to interpret and visualize their findings. The program features a multidisciplinary curriculum that builds on the foundation of computer science, statistics, and database management, with applications in bio-, eco-, and health-informatics.

Student Learning Outcomes

  • Identify, apply, and compare common data discovery, capture, and cleaning methods.
  • Design, implement, and evaluate database solutions for data warehousing, staging, and processing that are appropriate to the given data type, scale, and security expectations.
  • Explain, contrast, and implement data mining, machine learning, statistical modeling, or other quantitative analytic methods appropriate for complex data, including but not limited to spatial, time-series, and survey data.
  • Effectively communicate complex data science concepts and analytical results through common and state-of-the-art data visualization, business intelligence, or data reporting methods.

Graduate Admission Information

  • The NAU graduate online application is required for all programs. Admission to many graduate programs is on a competitive basis, and programs may have higher standards than those established by the Office of Graduate and Professional Studies.

    Admission requirements include the following:

    • Transcripts.
    • Undergraduate degree from a regionally accredited institution with a 3.0 GPA on a 4.0 scale ("A" = 4.0), or the equivalent.


    Visit the NAU Graduate Admissions website for additional information about graduate school application deadlines, eligibility for study, and admissions policies.

    Ready to apply? Begin your application now.

    International applicants have additional admission requirements. Please see the International Graduate Admissions Policy.

Additional Admission Requirements

  • Individual program admission requirements over and above admission to NAU are required.

    • A Bachelor's degree in STEM or a related field.
    • Essay/Letter of Intent/Personal Statement*
    • Recommendation(s)/Reference(s)*
Master's Requirements

  • This Master's degree requires 30 units.


    Take the following 30 units:

Additional Information

  • Some courses may have prerequisites. For prerequisite information, click on the course or see your advisor.

  • Program Fee Information

  • Program fees are established by the Arizona Board of Regents (ABOR). A program fee has been approved for this program. See program fee details. Program fees are subject to change and updated July 1 for the next academic year.