*In Case You Missed It: View our M.S. in Analytics Information Session.
|May 2018 - May 2019
|spa||May 2019 - May 2020
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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 STEM degree prepares graduates to fill the current gap in the marketplace. Analytics and data science experts are needed - and in just 1 year, you can become one of them.
The Master of Science in Analytics is a full-time, three-semester program (Begins in May - summer, fall, spring) at UNH is an 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 big data 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.
"I feel that my prospects to land a great job and one I will enjoy are greatly increasing, especially so with the decision science part of the program. Honestly, I couldn't have picked a better program." - Derek, class of '16.
MS in Analytics - Curriculum Overview
The MS Analytics - Program requires 36 credits. There are three, 12-credit semesters. Courses are 3 credits each. Two cluster course electives are required. The core Analytics curriculum is taught daily from 9am to 1pm.
View detailed course descriptions here.
The Master of Science in Analytics at UNH begins in May with a statistics and linear algebra primer and continues through the summer, fall and spring semesters. This program will also be practicum-driven throughout the fall and spring semesters, with students working in teams to complete an industry or government sponsored real-world analytic problem.
Summer (Beginner Analytics)
The initial semester, brings together both the Graduate Certificate in Analytics (GCA) students and the M.S. students, to learn side by side. The summer semester provides students a measurable and consistent foundation in statistics and an overview of analytic foundations, tools and an exposure to their application. The session is an intense introduction to the field of analytics where students are using provided data to sample tools and techniques, get exposure to the field and engage in some high level hands on manipulation and presentation.
Each day, students will begin with instruction in such topics as data exploration, programming and data management, multivariate and logistic regression or data mining and spend the remainder of the day working on homework and project assignments.
Fall and Spring (Intermediate and Advanced Analytics and data science)
These semesters mirror one another. Students spend their mornings in class and in the afternoon collaborating in groups on projects, professional development and networking with industry partners/sponsors. Building on the knowledge the gained from the summer they work toward a formal presentation in a practicum course, which acts as an academic yearlong capstone experience.
Both semesters consist of two analytics core courses and a practicum course. The core courses begin in the fall with data architecture and an intermediate exposure to Analytics Applications I. In the spring semester, students begin more advanced work in analytic methods and Analytics Applications II.
The practicum courses (Practicum I and II) are designed to instruct on two primary areas of content. One is to apply the core tools to the project the team is working on. The second is the professional nature of the presentation back to the sponsor and the professional development of the student in the role of analytics professional. Students will receive training on presentation skills, conceptual mapping of questions, conveying of data and analytic limitations and project scoping, as well as communication, messaging, and professional development skills such as resume writing, online presence and exposure to the industry of analytics and data science. They will also be paired with a faculty mentor to help counsel and instruct them during the project. See some Practicum presentations here.
Cluster Areas of Focus
The Cluster Course electives consists of two required courses, taken in the fall and spring semesters. See Clusters listed in the Sample Curriculum Map.
The final curriculum objective is to allow for specialization in a targeted area of student interest to provide students with a deeper knowledge in the subject area of their choice.
Current cluster options include health, accounting, decision science, finance, marketing, economics, sports, human & technology interface, or self-designed focus.
For questions, a program overview or site tour,
Contact Lyin Schramm, Admissions Coordinator
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