Analytics (M.S.)

https://www.unh.edu/analytics/master-science-analytics

These days, big data is a big deal, and it is everywhere - from professional sports to healthcare, and from e-commerce to government sectors. As the use of analytics grows, so does the demand for people who know how to skillfully extract value from massive amounts of data. The University of New Hampshire’s Master of Science in Analytics degree prepares graduates to fill the current gap in the marketplace. Analytics experts are needed - and in just 11 months, you can become one of them. 

The Master of Science in Analytics full-time, three-semester program (summer, fall, spring) at UNH is an applied, interdisciplinary graduate program that offers students in-depth training in quantitative analysis, applications and reasoning, critical thinking and analytics. It has a cohort design and is a full-time program intended to engage students in real-world projects with external partnerships that provide them with unique opportunities to apply their skills, solve real-world analytics problems, and develop connections for employment. Students are able to specialize in areas of health, business, or self-designed focus areas. Professional development, critical thinking, presentation/communication, and leadership skills are integrated into the analytics program-one of the fastest growing fields in the world. Upon completion of the program, students will be prepared to sit for a number of SAS certifications.

  • Intensive, full-time, on-campus program provides a specialized set of skills in just 11 months.
  • Complete analytic projects with industry partners, gaining real-world experience while networking.
  • Work in analytics teams on projects sponsored by industry partners.
  • Gain expertise in advanced predictive modeling, market segmentation and text analysis. 
  • Professional development through teamwork, communication, critical thinking and project work

Please visit the program website for program or Analytics & Data Science information.

Degree Requirements

  • 36 credits completed with a cumulative grade point (GPA) average of 3.0 or higher and grades higher than B­.
  • Passing grade on Practicum Project – Student demonstrates synthesized learning from the curriculum into the analysis of a team project which includes applied skills in data cleaning, data mining, and analysis, professionalization, including presentation skills, conceptual mapping of questions, conveying of data and analytic limitations, and project scoping, as well as communication, messaging, and professional development skills.
  • Satisfactory attendance
  • Acceptable Student Professional Code of Conduct
Required Courses
DATA 800Introduction to Applied Analytic Statistics3
DATA 801Foundations of Data Analytics3
DATA 802Analytical Tools and Foundations3
DATA 803Introduction to Analytics Applications3
DATA 900Data Architecture3
DATA 901Analytics Applications I3
DATA 911Analytics Practicum I3
Cluster Elective I3
DATA 902Analytics Methods3
DATA 903Analytics Applications II3
DATA 912Analytics Practicum II3
Cluster Elective II3
Total Credits36