Health Data Science (M.S.)

Health Data Science (M.S.)

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We have developed a Corporate Partners program for the Health Data Science master's degree and graduate certificate.

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Data science is among the fastest-growing fields across all industries, and healthcare is no exception. The online M.S. in health data science at UNH will prepare you to work with complex healthcare data and enable you to effectively communicate data analysis in clear, objective,and understandable terms for a variety of audiences in visual and written forms. You will learn the statistical foundations of health data science as well as health data architectures and data structures. You will build models and explore visualization and design techniques to best address the complexities of patient care and population health issues.


The online M.S. in health data science program at UNH is designed for working professionals who see that data plays a critical role in patient and population health outcomes and are looking to hone their skills specifically around healthcare data. Courses led by our full-time faculty are asynchronous, meaning you’ll be able to complete your studies at your own pace, on your schedule–with the option to enroll either full or part-time. You’ll also have the support of a student success coach to help you get the most out of the program. Applications are accepted for start dates in the spring or fall.


  • Healthcare data scientist
  • Senior health data scientist
  • Data /information officer
  • Analytics officer
  • Clinical data manager
  • Healthcare data analyst
  • Population health officer
  • Health informatics/data consultant
  • Outcomes research specialist
  • Principal researcher/investigator


Department of Health Management & Policy
Hewitt Hall, 4 Library Way
Durham, NH 03824-3563

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Curriculum & Requirements

The Master of Science in Health Data Science (MSHDS) is offered by the Department of Health Management and Policy within the College of Health and Human Services. The 36 credit, 12 course program is fully online,  starting in either the Fall or Spring semesters. It can be completed full-time or part-time in as few as five semesters or up to three years. The interdisciplinary curriculum is comprised of ten core health data analytics and data science courses and two elective course tracks in Health Care Informatics or Health Systems Research. Additionally, the MS in Health Data Science requires two virtual symposiums that expose students to current content and skills necessary to be an effective health data science practitioner.  

The core courses develop deep quantitative tools, applications and reasoning, critical thinking and translational skills such as visualization, communication and interactive design. Students receive training in a multitude of quantitative tools and algorithms such as machine learning and deep learning, as well as how they are utilized and applied within the health care industry. Primarily using  coding languages of R and Python,  and SQL, students are exposed to computational and analytic environments such as enterprise systems, streaming, and distributed cloud systems.  

The content is practicum driven, with each student applying core tools to address, and complete an industry real-world analytic project, while also having exposure to the processes and professional development of health data science and analytics professionals. Students will have exposure to  methodologies such as LEAN and Agile project management. There will also be exposure to conceptual mapping for health data practitioners such as design thinking.  During the practicum, students will develop skills in project scoping, background, data transfer, and understanding policies and procedures in place via the host or by the type of data being used.  Students will also engage in data mining, modelling and storytelling with outcomes for ultimate presentation back to the host site.  In the final e-term in the Fall, students can choose from several electives and, if they choose, can select an elective track (Health Care Informatics or Health Systems Research).

Graduates will have the skills necessary to function as health data science practitioners in a wide-range of roles, with the ability to adapt as needed in the dynamic, rapidly changing industry. The skills acquired in the HDS Program include  health data acquisition, management, tools in cleansing tools, analytics, and techniques relative to both large and small data types and sources to interpret and present data individually and within teams.


The Master of Science in Health Data Science begins each Fall (August) and Spring (January).  The Fall and Spring semesters consist of two e-terms (each 8-weeks in length) each, followed by one e-term in Summer  Each semester builds in level of mastery.

Foundation of Health Systems, Health Data Stats, Programming and Translation

The initial semester brings together both the Graduate Certificate in Health Data Science (GCHDS) students and the MS students, to learn side by side. Students learn the foundations and function of the US Health System, the basics of statistical and mathematical thinking relative to health data, programming in three languages, and the foundations of data cleaning, visualization, and presentation.  In addition, a number of “soft” skills are introduced such as LEAN project management and Agile training.

Key Program Highlights

  • Consists of 12 online courses, 36 credit hours, 2 specialization electives
  • Gain expertise in advanced machine learning, text analytics, programming, visual analytics, and big data framework within the health care industry.
  • Curriculum stays relevant to the ever-changing technology with an ability for the students to choose their specialization (i.e. Health Care Informatics or Health Systems Research)
  • Students from diverse backgrounds – not just technical fields
  • Work hands-on, team-based learning

The MSHDS requires the completion of 36 credits.

Required Courses:
HDS 800Mathematics and Statistics for Health Data Science3
HDS 801The U.S. Healthcare System3
HDS 802Programming in Healthcare Environments3
HDS 803Translation of Health Data3
HDS 804Health Data Systems3
HDS 805Applied Machine Learning in Healthcare3
HDS 806Outcomes Research3
HDS 807Unstructured Health Data3
HDS 808The Successful Healthcare Project3
HDS 811Health Data Science Practice3
Choose two electives:6
Healthcare Informatics Electives
HDS 820
Health Systems Informatics
or HDS 821
Big Data Algorithms in Biological Sciences
or HDS 890
HDS Independent Study
Health Systems Research Electives
HDS 822
AI and Deep Learning in Healthcare
or HDS 823
Advanced Statistics in Healthcare
or HDS 890
HDS Independent Study
Total Credits36

To prepare students to professionally interpret health care data and present findings to the appropriate audiences using appropriate tools and design with the following:

  • Use of ethics, probability, Inference, Data Exploration and Imputation, as well as the ability to design experiments.
  • Use of Databases and storage, including SQL and NoSQL, Mongo DB, AWS.
  • Application programs and to address large and small data with programs such as Python, R, SAS, JMP, Tableau, Power BI, GIS/QGIS, Hadoop, Spark, Hive, Pig.
  • Introductory and advanced Algorithms for text and data mining.
  • Use of cleansing tools, such as Natural Language and use of Neural Networks Natural Language for translation of and processing of data for storytelling.
  • Foundations and advanced of Predictive Modelling using Time Series, Forecasting, Multivariate Techniques,
  • Propensity Score Matching and Clustering using Bayesian, Survival, Survey and psychometry analysis.
  • Cost effectiveness using Econometrics, QALY measurement, Pharmaco-economics, Reimbursement and their relation to structure and operations and strategic decision-making.
  • Policy, Population Health, Epidemiologic Methods, Governance.
  • Project Management approaches with LEAN, Agile.
  • Communication in all forms such as presentations, interviewing, to work in groups and individually.


Applications must be completed by the following deadlines in order to be reviewed for admission. Applications are reviewed on a rolling basis. Note that classes may fill early and students could be referred to the next available start time.

  • Fall: July 1
  • Spring: December 1
  • Summer: N/A
  • Special: N/A

Application fee: $65

Campus: Online

New England Regional: No

Accelerated Masters: Yes (for more details see the accelerated masters information page)

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.


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 upload a copy (PDF) of your official transcript in the application form. International transcripts must be translated into English.

If admitted, you must then request an official transcript be sent directly to our office from the Registrar's Office of each college/university attended. We accept transcripts both electronically and in hard copy:

  • Electronic Transcripts: Please have your institution send the transcript directly to 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.

Transcripts from all previous post-secondary institutions must be submitted and applicants must disclose any previous academic or disciplinary sanctions that resulted in their temporary or permanent separation from a previous post-secondary institution. If it is found that previous academic or disciplinary separations were not disclosed, applicants may face denial and admitted students may face dismissal from their academic program.

Letters of Recommendation: 3 Required

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

Personal Statement

Prepare responses to three program-specific essay questions:

  1. Discuss your educational and career goals and how a master's degree in health data science will help you achieve those goals.
  2. Talk about your programming experience.
  3. If applying to the masters degree, discuss a potential idea for a culminating project or an area of interest you hope to pursue.

Statements must be included with your submitted application.

Important Notes

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


A current resume is required with your submitted application.

International Applicants

Some academic departments recommend that international applicants, living outside of the United States, and planning on pursuing a research based degree, submit our extended inquiry form before submitting a full application. The extended inquiry form will be reviewed by the academic faculty and a department representative will reach out if your background and qualifications are a good fit for the program. 

Prospective international students are required to submit TOEFL, IELTS, or equivalent examination scores. 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.


For program-specific application questions, please contact the UNH Online Student Success Coaches: or 855.250.6699

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