Analytics and Data Science, B.S.

Science Technology Data as a Abstract Art (analytics)

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. Our 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.

You’ll learn the cutting-edge technical skills you need to manage, distill, and interpret data for industries from finance to healthcare to marketing and advertising. You’ll master programming languages like Python and Ruby so you can derive actionable information from data, and the industry-standard software SAS, making you eligible for certification as a base SAS programmer or a SAS business analyst. Plus, you’ll become fluent in big-data frameworks like Hadoop and MapReduce – valuable skills to any employer. With an emphasis on extracting meaning from data, this program is designed to prepare students for careers in a wide array of industries or for professionally-oriented graduate programs, like UNH's Master of Science in Analytics

Through hands-on learning and real-world experience, you’ll get cutting-edge technical skills and a competitive advantage in a rapidly growing field.



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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 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

First Year - Fall Semester

  • UMST 401 – First Year Seminar:
    The focus of this seminar in not on a specific academic subject or field of study; instead, the focus is on the student. This course is intentionally designed and proactively delivered for the purpose of promoting personal success-in college and in life after college--by fostering the development of skills or strategies that are both applicable and valuable across subjects. The course focuses on the following topics: college expectations and opportunities, campus resources, learning styles and strategiesincluding lecture note-taking, test taking, memory and concentration; life management, goal setting, educational planning, career decision-making, health maintenance, diversity and instructor/student relationships. The course integrates personal growth, academic and career success with problem solving, critical and creative thinking.
  • COMP 425 - Introduction to Programming:
    An introduction to problem solving and object-oriented programming. Emphasis is on programming concepts and techniques and their application to software development. Students learn to write, review, document, share, and demonstrate interactive applications and participate in pair programming, peer-led tutoring, and collaborative learning throughout the course.
  • MATH 425 - Calculus I:
    Calculus of one variable covering limits, derivatives of alerbraic, trigonometric, exponential, and logarthmic functions; applications include curve sketching, max-min problems, reltaed rates, and volume and area problems. 
  • ENG 401 - First Year Writing:
    Training to write more skillfully and to read with more appreciation and discernment. Frequent individual conferences for every student. 
  • Discovery Course

First Year - Spring Semester

  • BUS 400 - Introduction to Business:
    Introduces the study of business: examines the origins and development of American business, its place in a global economy, and its legal and ethical roles in modern society. Includes an overview of the functional areas of business such as finance, marketing, and organizational behavior. Designed for business majors as well as for students considering a major in business.
  • COMP 490 - Statistics in Computing and Engineering:
    An introduction to tools from probability and statistics that are needed by computing and engineering professionals. Exploratory data analysis including graphic data analysis. discrete and continuous probability distributions, inference, linear regression, and analysis of variance, with applications from artifical intelligence, machine learning, data mining, and related topics. Project work and use of statistical software are an integral part of the course.
  • ENGL 401 - First Year Writing, or Inquiry Course:
    Training to write more skillfully and to read with more appreciation and discernment. Frequent individual conferences for every student
  • Foreign Language II

Second Year - Fall Semester

  • COMP 430 - Systems Fundamentals:
    The underlying hardware and software infrastructure upon which applications are constructed is collectively described by the term "computer systems." Computer systems broadly span the subdisciplines of operating systems, parallel and distributed systems, communications networks, and computer architecture. The class will present an integrative view of these fundamental concepts in a unified albeit simplified fashion, providing a common foundation for the different specialized mechanisms and policies appropriate to the particular domain area.
  • DATA 557 - Introduction to Data Science and Analytics:
    An introduction to data science and analytics. The landscape of analytics, including an overview of industries and sectors using analytics or expected to use analytics in the near future. Data generation, data management, data cleaning, and data preparation. Ethical use of data. Focus on visual and exploratory analysis. Project-based, with an emphasis on collaborative, experiential learning
  • MATH 545 – Introduction to Linear Algebra:
  • MATH 645 – Linear Algebra for Applications:
  • Discovery Course

Second Year - Spring Semester

  • COMP 520 - Database Design and Development :
    An introduction to developing database applications with business users. Topics incluce fundamentals of the relational model, structured query language, data modeling and database design and implementation. Students use a variety of database management system tools to model, code, debug, document, and test database applications. Students complete real-world team projects.
  • COMP 525 - Data Structures Fundamentals:
    Data structures and algorithms are fundamental to developing solutions for computational problems. In this course students design and implement data and functional abstractions; analyze and select appropriate data structures to solve computational problems; practice programming and software development techniques to implement computational solutions.
  • ENG 502: Professional and Technical Writing:
    A writing course introducing students to the effective communication of technical information through various workplace documents including resumes, memos, business letters, reports, brochures, etc. Special emphasis on an introduction to professional conventions and genres and to the transferable skills of rhetorical and audience analysis, document design and collaborative work. 
  • Discovery Course

Third Year - Fall Semester

  • MATH - Applied Regression Analysis:
    Applications of behavioral science concepts to work settings. Topics include worker incentives and perceptions toward work, group versus individual decision making, conflict resolution, interpersonal and leadership skills, and the study of other behaviors relevant to effective managing of a business organization.
  • BUS 453 - Leadership for Managers 
    Investigates the role and impact of computer applications on computer information systems in general and specifically as applied to business requirements. Surveys the components of a computer information system; explores computer information systems in areas such as manufacturing, medicine, education, and government; discusses the issues of computerizing information resources. Directs attention to computer information systems in business and identifies the need for and function of formal systems development methodologies.
  • BUS 620 - Organizational  Behavior
  • Discovery Course

Third Year - Spring Semester

  • DATA 674 - Predictive and Prescriptive Analytics I:
    A first course in predictive and prescriptive analytics. Supervised learning models including linear models and CART models. Model assessment and scoring methods, including cross-validation. Regularization and model tuning. Unsupervised learning models including k-means clustering. Project-based, with an emphasis on collaborative, experiential learning. Statistical software will be used and programming required.
  • DATA 690 - Internship Experience:
    A field-based learning experience via placement in a business, non-profit, or government organization using analytics. Under the guidance of a faculty advisor and workplace supervisor, students gain practical experience solving problems and improving operational processes using analytics.
  • UMST 599 - Internship & Career Planning Seminar:
    Occasional offerings dependent on availability and interest of faculty, barring duplication of subject, may be repeated for credit.
  • Discovery Course
  • Discovery Course
  • Elective/Specialization Course

Fourth Year - Fall Semester

  • Data 674 - Predictive and Prescriptive Analytics II:
    A second course in predictive and prescriptive analytics. Time series analysis and model ensembles. Bootstrapping, simulation, optimization. Monte Carlo methods. Project-based, with an emphasis on collaborative experiential learning. Statistical software will be used and programming required.
  • Data 757 - Big Data:
    A first course in large-scale analytics and data science. Characteristics of big data and the emerging software stack for working with massive datasets, including Hadoop and MapReduce. Algorithms for extracting information from massive datasets.
  • Elective/Specialization Course
  • Elective/Specialization Course

Fourth Year - Spring Semester

  • Data 790 - Captsone Project
    A seminar course in which students report on and discuss their business internship experiences. Selected group readings and written and oral student presentations.
  • Elective/Specialization Course
  • Elective/Specialization Course
  • Elective/Specialization Course


Download a copy of the major sheet

Our campus is in the heart of the region’s cultural, economic, entertainment and government activity — putting unlimited internship opportunities at your doorstep.

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

Once you've completed your bachelor's degree, take your education to the next level by pursuing your Master of Science in Analytics at UNH's campus in Durham.

The M.S. in Analytics program provides graduates with “the complete package” — developing the technical and professional skills to help businesses use data effectively to produce real-time results.

Master’s students will hone their skills through case-studies and real-world challenges, becoming highly skilled at efficiently deriving actionable information from data.

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. 

Click on a community college below to see transferable analytics and data science requirements. See the complete list of Pathways. 

Questions? Contact an Admission Counselor for help.

Course Sequence

Interested in a sample course sequence for this program?

Download a copy of the major sheet

Course Schedule

Visit and select "Courses at Manchester" to see our course schedules and descriptions.