Rensselaer's Education for Working Professionals

Graduate Certificate in Health Analytics

Address:

275 Windsor Street

Hartford, CT 06120

United States

Phone:

1-800-433-4723

Program Information

Degrees Offered:

Graduate Certificate in Health Analytics

Format: Online

Program Description:

The rate of innovation in health industries requires leaders to quickly determine if a particular therapy is working or what factors impact efficacy, given overwhelming data from multiple sources. As a leader, you need data to ensure proper interpretation and decisions. Rensselaer’s Graduate Certificate in Health Analytics prepares you to model operations accurately, differentiate true intelligence from “hunches”, turn unknowns into knowns, and make the best use of data possible.

Certificate Information

  • You can begin the certificate in January, May, or August
  • Each course is 3 credit hours, the certificate is 3 course, 9 credit hours to complete
  • The certificate’s blended online delivery reflects today’s dynamic workplace
  • Practitioner faculty guide the completion of project work that relates to your career objectives
  • The program results in a graduate level Certificate in Health Analytics from Rensselaer Polytechnic Institute.
  • Courses are taken for credit, and successful completion requires a GPA of 3.0 or greater
  • As each of the courses build upon prior courses, courses must be taken in sequence.
  • Students completing the Health Analytics Certificate are not eligible to complete the Business Intelligence (BIH) or Production Analytics (PAH) certificates.
  • Students may choose to complete multiple certificates, or apply certificates to other degree programs, according to each program’s requirements (for eligible programs, see program web)

Course Coverage:

The Health Analytics Certificate requires three courses:

ENGR 6200: Data-Driven Decision Making - Frame questions and resolve problems using data wrangling tools to prepare methods for analysis; employ models using linear/nonlinear multivariate methodologies using R, Python and Excel; validate results and develop algorithms that can be used to make recommendations and forecasts; and, work with stakeholders to scope and frame questions and problems so that actionable results can be achieved.

ENGR 6210: Health Industry Analysis - Use visualization and cluster analysis to gain deeper insights into health industry relationships. Apply data analytics to real-world health care problems and questions, including resource scheduling, therapeutic effectiveness, population intervention studies, demographically-related health trends, and benchmark setting for standard of care dashboards. Students tune and adjust models as underlying assumptions change.

ENGR 6211: Modeling Health Decisions - Working with a faculty member as mentor, develop a big data health industry inquiry model for an issue, question or problem of your choice. Over the semester, frame the question to be analyzed, collect and prepare data for analysis, perform the analysis and present actionable results and recommendations back to the organization.

Accreditation:

Middle States Commission on Higher Education (MSCHE) The Accreditation Board of Engineering and Technology (ABET) The Association to Advance Collegiate Schools of Business (AACSB) The National Architectural Accrediting Board (NAAB)

Facts & Figures

Classification: Specialized Institution—School of engineering and technology

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