Shaping the next generation of data revolutionaries
With an explosion of big data initiatives in organizations worldwide, the demand for data-savvy individuals has never been higher. The Analytics and Data Science program is the only on-campus degree of its kind in the region, specifically designed to prepare the next generation of innovative data scientists and analysts.
Your interests inspire what you study, allowing you to focus your education with degree options in:
- Analytics, which centers on the applications of data science in industry. This option can be fully completed at both the Manchester and Durham campuses.
- Data Science, which emphasizes the theoretical, mathematical and computational underpinnings of modern data science. While this option is available on both campuses, it requires some courses currently offered only at the Durham campus.
With the hands-on experience you'll get through applied projects, internships and field work, you’ll gain cutting-edge technical skills and a competitive advantage in this rapidly growing field.
What is analytics and data science?
The analytics and data science field affects nearly all aspects of the economy, society and daily life. The analytics focus of the field benefits from multidisciplinary and interdisciplinary approaches to extract knowledge and insights from large quantities of complex data for practical use in varied domains. Organizations today are increasingly reliant on analytics to make business decisions, which is reflected by the job demand for analytics-minded professionals. The analytics option at UNH emphasizes a broad range of data science applications, preparing students to meet the workforce demand in industry, academia and government.
Why study analytics and data science at UNH Manchester?
The analytics and data science program at UNH Manchester integrates experiential learning, professional development and applied projects, giving you real-world experience at local companies, nonprofits and government agencies. You’ll learn to manage, distill and interpret data for industries from finance to healthcare, marketing and advertising. Applying a strong programming skill set, you will derive actionable information from authentic data sets. With our small class sizes, close interaction with faculty and ties to industry in the bustling Manchester Millyard, the program will prepare you for a wide array of careers or professionally oriented graduate programs.
Potential careers
- Actuary
- Business analyst
- Data engineer
- Data scientist
- Machine learning engineer
- Management analyst
- Market research analyst
- Operations research analyst
- Statistician
- Quantitative analyst
NEW ENGLAND RESIDENTS
Connecticut, Maine, Rhode Island and Vermont do not offer a bachelor's-level analytics program in their public universities, so students from these states can enroll in UNH's program at a reduced tuition rate.
PROGRAM LOCATIONS
Analytics and data science is offered at both the Manchester and Durham campuses.
Curriculum & Requirements
The option in Analytics is intended for students interested in either heading into industry immediately upon graduation, or pursuing graduate work in a professionally oriented program at UNH. The option in Analytics places its emphasis on applications of data science in industry.
This program has been designed to prepare students for professional careers working with data, with an emphasis on the extraction of meaning from data. The program is not targeted to any one industry; rather, it provides a flexible, practical skillset that can be applied widely. This skillset includes elements of computer science, applied mathematics and statistics, communication skills, and business savvy. During the course of the program, students will demonstrate their acquisition of these skills by successfully completing their program coursework, their internship experience, and their capstone project.
For additional information, contact program coordinator Jeremiah Johnson or the UNH Manchester Office of Admissions, (603) 641-4150.
Sample Course Sequence
| First Year | ||
|---|---|---|
| Fall | Credits | |
| COMP 424 or CS 415 |
Applied Computing 1: Foundations of Programming or Introduction to Computer Science I |
4 |
| ENGL 401 | First-Year Writing | 4 |
| MATH 425 | Calculus I | 4 |
| Discovery Course | 4 | |
| Credits | 16 | |
| Spring | ||
| BUS A 1 | 4 | |
| COMP 525 or CS 416 |
Data Structures Fundamentals or Introduction to Computer Science II |
4 |
| DATA 557 or CS 457 |
Introduction to Data Science and Analytics or Introduction to Data Science and Analytics |
4 |
| MATH 426 | Calculus II | 4 |
| Credits | 16 | |
| Second Year | ||
| Fall | ||
| COMP 625 or CS 515 |
Data Structures and Algorithms or Data Structures and Introduction to Algorithms |
4 |
| MATH 645 | Linear Algebra for Applications | 4 |
| Discovery Course | 4 | |
| Elective 2 | 4 | |
| Credits | 16 | |
| Spring | ||
| COMP 430 | Systems Fundamentals | 4 |
| COMP 520 or IT 505 |
Database Design and Development or Integrative Programming |
4 |
| COMP 570 or MATH 539 or MATH 644 |
Statistics in Computing and Engineering or Introduction to Statistical Analysis or Statistics for Engineers and Scientists |
4 |
| Discovery Course | 4 | |
| Credits | 16 | |
| Third Year | ||
| Fall | ||
| BUS B 1 | 4 | |
| DATA 674 | Predictive and Prescriptive Analytics I | 4 |
| MATH 739 | Applied Regression Analysis | 4 |
| Discovery Course | 4 | |
| Credits | 16 | |
| Spring | ||
| DATA 675 or COMP 721 |
Predictive and Prescriptive Analytics II or Big Data for Data Engineers |
4 |
| ENGL 502 | Professional and Technical Writing | 4 |
| UMST 582 | Internship and Career Planning Seminar | 1 |
| Discovery Course | 4 | |
| Discovery Course | 4 | |
| Credits | 17 | |
| Fourth Year | ||
| Fall | ||
| BUS C 1 | 4 | |
| DATA #757 | Mining Massive Datasets | 4 |
| Discovery Course | 4 | |
| Elective | 4 | |
| Credits | 16 | |
| Spring | ||
| DATA #790 or CS 791 or CS 792 |
Capstone Project or Senior Project I or Senior Project II |
4 |
| Discovery Course | 4 | |
| Elective | 4 | |
| Elective | 4 | |
| Credits | 16 | |
| Total Credits | 129 | |
- 1
In consultation with your advisor, select: Introduction to Business, Organizational Behavior, or Organizational Leadership.
- 2
MATH 531 Mathematical Proof strongly encouraged
Degree Requirements
All Major, Option and Elective Requirements as indicated.
*Major GPA requirements as indicated.
Major Requirements
Successful completion of the program entails earning at least 128 credits, meeting the requirements of the University's Discovery program, completing all of the 21 required courses in the major as listed below, including the capstone course, the internship preparedness course, and an internship. In all major courses, the minimum allowable grade is a C-. The minimum overall GPA for graduation is 2.0. Transfer students may transfer up to a maximum of 32 credits to satisfy major requirements (not counting those courses used to satisfy Discovery requirements).
| Code | Title | Credits |
|---|---|---|
| Mathematics | ||
| MATH 425 | Calculus I | 4 |
| MATH 426 | Calculus II | 4 |
| MATH 545 | Introduction to Linear Algebra | 4 |
| or MATH 645 | Linear Algebra for Applications | |
| MATH 739 | Applied Regression Analysis | 4 |
| Computing | ||
| COMP 424 | Applied Computing 1: Foundations of Programming | 4 |
| or CS 415 | Introduction to Computer Science I | |
| COMP 430 | Systems Fundamentals | 4 |
| COMP 520 | Database Design and Development | 4 |
| or IT 505 | Integrative Programming | |
| COMP 525 | Data Structures Fundamentals | 4 |
| or CS 416 | Introduction to Computer Science II | |
| COMP 570 | Statistics in Computing and Engineering | 4 |
| or MATH 539 | Introduction to Statistical Analysis | |
| or MATH 644 | Statistics for Engineers and Scientists | |
| COMP 625 | Data Structures and Algorithms | 4 |
| or CS 515 | Data Structures and Introduction to Algorithms | |
| Business 1 | 12 | |
| Analytics & DATA Courses | ||
| DATA 557 | Introduction to Data Science and Analytics | 4 |
| or CS 457 | Introduction to Data Science and Analytics | |
| DATA 674 | Predictive and Prescriptive Analytics I | 4 |
| DATA 675 | Predictive and Prescriptive Analytics II | 4 |
| DATA #757 | Mining Massive Datasets | 4 |
| or COMP 721 | Big Data for Data Engineers | |
| Project and Professional Practice | ||
| DATA 690 | Internship Experience | 1-4 |
| DATA #790 | Capstone Project | 4 |
| or CS 791 | Senior Project I | |
| or CS 792 | Senior Project II | |
| Other | ||
| ENGL 502 | Professional and Technical Writing | 4 |
| UMST 582 | Internship and Career Planning Seminar | 1 |
| Total Credits | 78-81 | |
- 1
In consultation with your advisor, select:
1 course (4 credits) in Introduction to Business
1 course (4 credits) in Organizational Behavior
1 course (4 credits) in Organizational Leadership
Analytics and Data Science focuses on the extraction of meaning from data through the application of computer science, mathematics and business domain knowledge. Within a few years of obtaining a bachelor's degree in Analytics and Data Science, our alumni will have:
- Engaged in successful career areas of analytics and data science and will already have, or be pursuing, advanced degrees in Analytics, Data Science, Computer Science, Mathematics or related fields
- Applied the full range of core Data Science concepts and techniques to fill the analytics needs of an organization
- Communicated effectively with diverse stakeholders as well as functioned appropriately in a team environment
- Navigated the complex interconnections between data, computing technology, and the goals and constraints of the organization served
- Understood the pervasive and changing role of data in global society, and participated responsibly as both an Analytics and Data Science professional and citizen
Explore Program Details
A GPU computing cluster is under construction, made possible with a recent grant from NVIDIA, the world leader in visual computing. The state-of-the-art cluster will allow students to analyze medical imagery, explore models of speech and leverage GPU computing and CUDA C/C++ in their courses.
With expanded education and research in deep learning, computer vision and speech recognition, students will get the tools and techniques to power the next generation of technological innovation.
Your analytics and data science degree from UNH Manchester will put you at the forefront of one of the fastest growing fields in the country.
The McKinsey Global Institute indicates that by 2018, the U.S. will face a shortage of 140,000 to 190,000 people with the technical skills necessary to work effectively with data. But the demand for qualified analytics professionals is also skyrocketing globally, with the Education Advisory Board documenting a 32 percent increase in demand for college graduates with data analytics skills from 2010 to 2013.
That growing demand translates into high employment rates and starting salaries, particularly for graduates well-versed in SAS software — which is a core component of our program. Whether you envision a career in business, technology, healthcare, sports or beyond, your data analytics skills will allow you to discover new perspectives and solutions, making your work all the more rewarding.
The demand for data-savvy graduates is growing, with the Bureau of Labor Statistics projecting positive growth in many related professions between 2012 and 2024. Not only are your career possibilities vast, but many also come with lucrative salaries.
| Job Title | Projected Growth | Median Salary |
| Actuary | 18% | $97,070 |
| Budget Analyst | 3% | $71,590 |
| Market Research Analyst | 19% | $62,150 |
| Management Analyst | 14% | $81,320 |
| Market Research Analyst | 19% | $62,150 |
| Operations Research Analyst | 30% | $78,630 |
| Statistician | 34% | $80,110 |
Our campus is in the heart of the region’s cultural, economic, entertainment and government activity — putting unlimited internship opportunities at your doorstep.
The program is constructed to incorporate experiential learning into all courses, from start to finish, so we’ve partnered with local businesses to give you the real-world experience that sets you apart. Analytics majors have access to internships at many high-profile organizations in the area, including:
- Dyn
- Fidelity Investments
- Liberty Mutual
- SilverTech
- State of New Hampshire
Put the power of data programming, statistics and predictive modeling to work for you with our online graduate certificate in data science. Designed for busy professionals, our program offers the flexibility you need to continue working while you learn new skills. We teach cutting-edge algorithms, coding languages, statistical modeling and visualization tools through guided, online instruction and applied case studies. Increase your earning potential, advance your career, and make a greater impact within your business or organization with advanced, applicable data analytics and coding. Learn more
In partnership with the New Hampshire community colleges below, we've developed curriculum guides to show you which courses at your community college will transfer into UNH Manchester's analytics and data science program.
See the transferable analytics and data science requirements for these community colleges:
Questions? Contact an admission counselor for help.
- Tariq Abu-Jaber, Burgess Group
- Chuck Bransih, IDEXX
- Tim Chadwick, Dyn
- Jeff Dixon, IDEXX
- John Fitzsimmons, Fidelity
- Mike Fredrickson, EMC
- Ray Hunnicutt, Charter Communications
- Thomas Lambert, State of N.H. - Department of Health and Human Services
- Michael Laracy, Rapid Insights
- Angie McAllister, Pearson
- Enzo Micali, TJX Companies
- Eric Place, Martins Point Health Care
- Eric Poirier, UNUM
- Kevin Powers, EMC
- Jim Przybylowicz, IDEXX
- Christopher Synder, EMC
- Dinsesh Thakur, President/CEO
- William Vorias, Loyalty Builders
The program is jointly administered across both campuses and the degree requirements are identical. The Durham campus is primarily for residential full-time students who can commit to classes throughout the day and week. The Manchester programs are more convenient for students who prefer classes in the evenings or in non-traditional formats. The classes for the analytics option are available on both campuses, while some classes for the data science option are currently available only in Durham.
Program News
