Master of Science in Analytics

M.S. in Analytics - Program Overview 

*In Case You Missed It: View our M.S. in Analytics Information Session.

 

May 2017 - May 2018 M.S. Cohort     spa     May 2018 - May 2019 M.S. Cohort

At this time, applications are being accepted on a rolling basis. Completion of applications is strongly encouraged as the program is nearing capacity. Classes begin on May 22, 2017.

 

Applications are being accepted on a rolling basis, with a deadline of January 31, 2018. Classes begin in May 2018, and the program runs mid-May 2018 through Mid-May 2019.

Take the next step. Schedule a tour, apply or get more information today via email: unh.analytics@unh.edu, phone: 603-862-0688 or web links below. 

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 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.

 

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M.S. IN ANALYTICS PROGRAM BROCHURE

MS in Analytics - Program Highlights

  • Interdisciplinary approach with the opportunity to specialize in healthcare, marketing, operations management, or self-design study.
  • Work in analytics teams on projects sponsored by our industry partners.
  • Gain expertise in advanced predictive modeling, market segmentation and text analysis.
  • Master programming languages like Python, SQL, R and SAS, and become fluent in big data frameworks like Hadoop and MapReduce.
  • Intensive, full-time, on-campus program provides a specialized set of skills in just 11 months of study. 

The MS in Analytics program provides a strong link to the professional world through faculty, practicum project sites and job placement. Our students are immersed in the application of skills from beginning to end, and our curriculum remains relevant to the changing uses and technology of analytics.

We support our alumni through continuing education and networking opportunities and events. Students will master programming languages like Python, SQL and R, so that they can derive actionable information from data. Students will also master SAS, the industry-standard software. They will also become fluent in big-data frameworks like Hadoop and MapReduce.

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 elective courses are required.

A schedule could look like this: 
  • Summer:  800, 801, 802, 803 (total: 12 credits)
  • Fall: 900, 901, 911, cluster (total: 12 credits)
  • Spring: 902, 903, 912, cluster (total: 12 credits)

 

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Flow of the MS in Analytics Program

The Master of Science in Analytics at UNH begins in May with a statistics 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

The initial semester, which acts as a Graduate Certificate in Analytics (GCA), 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. After a lunch break, the rest of each academic day is spent collaborating in groups on projects, professional development and networking with industry partners/sponsors.

Fall and Spring

These semesters mirror one another, but build on knowledge moving toward a formal presentation in the practicum course, which acts as an academic yearlong capstone experience. See some Practicum presentations from 2016 here.

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.

Cluster Areas of Focus

The final curriculum objective is to allow for specialization in a more targeted area of interest. These required “cluster” courses will consist of two course options, one taken each semester, that will provide students deeper knowledge of a subject area. Current cluster options are in health, accounting, decision science, finance, marketing, economics, sports, human and technology interface, or a self-design focused.

 

APPLICATION REQUIREMENTS

CAREER PLACEMENT

COMPUTER REQUIREMENTS