Analytics (M.S.)

Analytics (M.S.)

students at whiteboard

The M.S. in Analytics (& Data Science) program provides a strong link to the professional world through faculty, practicum projects and job placement training. 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.

Why get a master’s degree in analytics?

Put the power of applied analytics and cutting-edge applied data science to work for you with a Master of Science in Analytics one-year STEM degree. Our interdisciplinary program is designed for professionals who want to learn the latest analytics tools and techniques with the ability to specialize in a field of interest. Students will study programming in three languages, data visualization, machine learning, deep learning neural networks and unstructured methods like text analytics and natural language processing through hands-on training and applied case studies. Advance your career and make a greater impact with analytics and data science skills.

Why choose UNH for your analytics degree?

Our programs take a multidisciplinary approach that incorporates experiential education, professional development, projects and work experience under the direction of faculty experts. We partner with international, national and local businesses to provide the resume-building experience that will propel your career. You’ll learn the cutting-edge technical skills you need to manage, distill and interpret data for industries from finance to healthcare to sports and marketing. Our graduates have gone on to careers at many high-profile organizations. This full-time program is offered on the Durham, N.H., campus, just 20 minutes from New Hampshire’s Seacoast, an hour from Boston and Portland, Maine, and less than two hours from the White Mountains.

Potential careers

  • Business analyst
  • Consultant
  • Data engineer
  • Data officer
  • Data scientist
  • Healthcare analyst
  • Management analyst
  • Market research analyst
  • Quantitative analyst

Contact

Lyin Schramm

Academic Department Coordinator
Phone: (603) 862-0803
Office: Analytics & Data Science, 10 Pettee Brook Lane Suite 1, Durham, NH 03824

UNH Analytics & Data Science
10 Pettee Brook Lane, Suite 1   
Durham, NH  03824
Phone: (603)862-0688 
TTY Users: dial 7-1-1 or 1-800-735-2964 (Relay N.H.)
E-mail: unh.analytics@unh.edu

 

 

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Curriculum & Requirements

The curriculum for the one-­year interdisciplinary, full-­time M.S. in Analytics program begins in May on the Durham, NH campus. The 36-­credit program is comprised of ten core analytics and data science courses and two cluster electives.  

Electives can be taken in many areas of applied focus such as, but not limited to, health care, business, environmental sciences, sports management, and others.

The program rests primarily on the coding languages of R and Python, but also SAS and SQL.   Students receive training in a multitude of quantitative tools and algorithms such as machine learning and deep learning. They also get exposed to computational and analytic environments such as enterprise systems to streaming and distributed cloud systems.   A sample of the module-based curriculum map, that stays relevant to changing technology may be seen here

The practicum courses are designed to instruct on two primary areas of content. One is to apply the core tools to a real-world project. The second is to provide useful exposure to the processes and professional development of the student in the role of analytics professional. Students will have the opportunity to learn methodologies such as LEAN and Agile project management.  Students will also be exposed to conceptual mapping for data practitioners such as design thinking.  They will do this both within projects should they or the host choose, or as added learning. View Practicum projects here.

Flow of the MS in Analytics Program

The Master of Science in Analytics begins each May.  Each of the three semesters build in level of mastery. 

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. In the summer, students learn the basics of statistical and mathematical thinking, programming in three languages, and the foundations of data cleaning, visualization, and presentation.  Each day, students will begin with instruction and spend the remainder of the day working on homework and project assignments, culminating in a team project around a social justice issue.  In addition, a number of “soft” skills are introduced such as LEAN project management and Agile training.  And finally, students are exposed to a host of industry partners and perspectives on the rapidly changing world of analytics and data science through our guest speaker series.

Fall and Spring (Intermediate and Advanced Analytics and Data Science)

These semesters mirror one another, yet build in tools and applications.  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 gained in summer, they work toward the completion of the capstone practicum in spring.  The Fall semester is spent on project scoping, background, data transfer, and understanding policies and procedures in place via the host or by the type of data being used. In Spring students are engaged in data mining, modelling and storytelling with outcomes for ultimate presentation back to the host site.

Students will also receive opportunities to further develop professional skills and certifications around LEAN should they choose. 

Cluster Areas of Focus

The Cluster Course electives consists of two required courses, taken in the fall and spring semesters. 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.

Key Program Highlights

  • Consists of 12 courses, 36 credit hours, 2 specialization electives
  • 1-year STEM masters or a 3-month certificate option
  • Gain expertise in advanced machine learning, text analytics, programming, visual analytics, and big data framework.
  • Curriculum stays relevant to the ever changing technology with an ability for the students to choose their specialization (i.e. Health/Business/Sports)
  • Students from diverse backgrounds – not just technical fields
  • Work hands-on, team-based learning

Sample Degree Plan

Plan of Study Grid
First Year
SummerCredits
DATA 800 Introduction to Applied Analytic Statistics 3
DATA 801 Foundations of Data Analytics 3
DATA 802 Analytical Tools and Foundations 3
DATA 803 Introduction to Analytics Applications 3
 Credits12
Fall
DATA 900 Data Architecture 3
DATA 901 Analytics Applications I 3
DATA 911 Analytics Practicum I 3
Cluster Elective I 3
 Credits12
Spring
DATA 902 Analytics Methods 3
DATA 903 Analytics Applications II 3
DATA 912 Analytics Practicum II 3
Cluster Elective II 3
 Credits12
 Total Credits36

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
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
DATA 902Analytics Methods3
DATA 903Analytics Applications II3
DATA 912Analytics Practicum II3
Cluster Elective I3
Cluster Elective II3
Total Credits36

Deadlines

Applications must be completed by the following deadlines in order to be reviewed for admission:

  • Fall: N/A
  • Spring: N/A
  • Summer: April 30
  • Special: N/A

Application fee: $65

Campus: Durham

New England Regional: ME RI VT

Accelerated Masters Eligible: No

New Hampshire Residents

Students claiming in-state residency must also submit a Proof of Residence form. This form is not required to complete your application, but you will need to submit it after you are offered admission or you will not be able to register for classes.

Transcripts

If you attended UNH after September 1, 1991, and have indicated so on your online application, we will retrieve your transcript internally; this includes UNH-Durham, UNH-Manchester and UNH Non-Degree work. 

If you did not attend UNH, or attended prior to September 1, 1991, then you must request one official transcript be sent directly to our office from the Registrar's Office of each college/university attended. International transcripts must be translated into English. We accept transcripts both electronically and in hard copy:

  • Electronic Transcripts: Please have your institution send the transcript directly to grad.school@unh.edu. Please note that we can only accept copies sent directly from the institution.
  • Paper Transcripts: Please send hard copies of transcripts to: UNH Graduate School, Thompson Hall- 105 Main Street, Durham, NH 03824. You may request transcripts be sent to us directly from the institution or you may send them yourself as long as they remain sealed in the original university envelope.

Letters of recommendation: 3 required

Recommendation letters submitted by relatives or friends, as well as letters older than one year, will not be accepted.

References should be substantial and should include academic and professional references.

Personal Statement

Prepare responses to three program-specific essay questions.

Statements must be included with your submitted application.

Resume

A current resume is required with your submitted application.

Department Requirements

You must have obtained a minimum GPA of 3.0 in earning your Bachelor's (or Master's) degree and have completed at least one statistics course for credit. An interview with an Analytics program faculty member is required. Please note that this program’s core courses are held in-person.

Important Notes

All applicants are encouraged to contact programs directly to discuss program specific application questions.

International Applicants

Prospective international students are strongly encouraged to complete our international pre-application process and are required to submit TOEFL, IELTS, or equivalent examination scores. Please note that English Language Exams may be waived if English is your first language. If you wish to request a waiver, then please visit our Test Scores webpage for more information.

  • I received my bachelor's degree in Business Administration from Paul College at UNH in 2018. While I was in Paul I focused on finance and marketing. I first became interested in analytics after taking Marketing Analytics my senior year.
    I received my bachelor's degree in Business Administration from Paul College at UNH in 2018. While I was in Paul I focused on finance and marketing. I first became interested in analytics after taking Marketing Analytics my senior year.
  • I received my Bachelor of Science from UNH in Health Management and Policy in 2015. I then started my career in the insurance industry which led to a analyst role in I.T. This position allowed me to see first-hand the importance of data-driven decision making, as I was the liaison between business...
    I received my Bachelor of Science from UNH in Health Management and Policy in 2015. I then started my career in the insurance industry which led to a analyst role in I.T. This position allowed me to see first-hand the importance of data-driven decision making, as I was the liaison between business...
  • My background is in biological oceanography. I have a B.A. in biology from Cornell University, an M.S. in marine and atmospheric science from SUNY Stony Brook, and a Ph.D. in biological oceanography from the joint program between MIT and the Woods Hole Oceanographic Institution. I worked as a...
    My background is in biological oceanography. I have a B.A. in biology from Cornell University, an M.S. in marine and atmospheric science from SUNY Stony Brook, and a Ph.D. in biological oceanography from the joint program between MIT and the Woods Hole Oceanographic Institution. I worked as a...
  • Alissa Andrews, M.S. in Analytics '16 went on to work as a Data Analyst for Liberty Mutual Insurance following graduation. She earned her Bachelor Degrees in Economics and International Relations from Mount Allison University in NB, Canada in May of 2015. She is from New Hampshire and grew up on ...
    Alissa Andrews, M.S. in Analytics '16 went on to work as a Data Analyst for Liberty Mutual Insurance following graduation. She earned her Bachelor Degrees in Economics and International Relations from Mount Allison University in NB, Canada in May of 2015. She is from New Hampshire and grew up on ...
  • Analytics Project   During the program, I worked with a major food producer in our area to understand their supply chain, as well as a large insurance provider to predict profitability. Both of these provided indispensable experience partnering with industry to solve real-world challenges. A third...
    Analytics Project   During the program, I worked with a major food producer in our area to understand their supply chain, as well as a large insurance provider to predict profitability. Both of these provided indispensable experience partnering with industry to solve real-world challenges. A third...

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