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Graduate Certificate in Health Data Analysis, Online (Z140)


The Graduate Certificate in Health Data Analysis, Online (Z140) is offered through the Department of Epidemiology and Biostatistics in the School of Public Health. The program bridges the gap between the limited quantitative skills of prospective employees and the advanced quantitative skills required in the health care sector by offering a formalized curriculum that emphasizes quantitative skills specifically required in the health care sector.

Mentoring and advising are an essential part of the program. Students meet with faculty and the academic program director to ensure that educational goals and career learning and development goals are met. Students with specific academic questions may contact Professor Jamie Trevitt, via email: jtrevitt@umd.edu.

Overview

The Graduate Certificate in Health Data Analysis, Online (Z140) has a 12-credit, four-course curriculum that emphasizes statistical methods and the computer programming skills required to manage and analyze health data sets.

  • Fulfills the substantial need among health professionals to learn in a formal and structured manner the statistical methods and computer programming skills necessary to organize and analyze health-related data, especially data collected for a specific purpose or readily available in national surveys. 
  • Focuses on health data applications wherein students master the material sufficient to improve their understanding of health data management and analysis which can further their professional careers.
  • Addresses statistical survey techniques and software and covers the basic statistics and programming concepts which are the foundation of management and analysis of health data.
  • Opens doors to students who lack a sophisticated statistical coursework or have no experience with computer programming.
  • Successful graduates learn how to apply health care data analysis and skills in a practical setting, demonstrate effective problem-solving, time management, and critical thinking skills, and communicate findings with a wide variety of audiences.
  • Can be completed in twelve months of continuous part-time enrollment. See Designation of Full-time/Part-time Status.

Courses

Below is a listing of all program courses. For a detailed course description, that includes pre-requisites or co-requisites, see The Graduate School Catalog, Course Listing as follows: EPIB Course Descriptions.

Course Number Title
EPIB650 Biostatics I
EPIB651 Applied Regression Analysis
EPID660 Analysis of National Health Survey Data
EPIB697 Public Health Data Management

Registration Overview

See the sample plan of study, below. Students should use this as a guide to develop a plan with the academic program director. 

  • Actual course offerings are determined by the program and may vary. Students should note if a course has a pre-requisite or co-requisite.
  • Specific class meeting information (days and time) is posted on the University of Maryland’s (UMD) interactive web service services, Testudo. Once on that site, select “Schedule of Classes,” then the term/year. Courses are listed by academic unit. 
  • The program uses specific section codes for registration that are listed on the sample plan of study.

Sample Plan

Semester Course Number Section Number Credits
Summer II EPIB650 PLY* 3
Fall EPIB697 PLY* 3
Spring EPIB651 PLY* 3
Summer I EPID660 PLY* 3

Overview

  • Features 100% online instruction with engaging and interactive learning.
  • Uses the semester academic calendar with classes held during fall and spring semester (16 weeks each) and Summer Session (two 6-week sessions).
  • Instruction provided by University of Maryland faculty and professionals in the field.
  • Using advanced audio and video technology, UMD’s online learning environment delivers dynamic and interactive content. 
  • Featuring convenience and flexibility, online instruction permits asynchronous or synchronous participation.
  • Lectures are video archived. Students who are unable to attend in real time can review the session through asynchronous participation.
  • Upon successful completion, graduates will have mastered the following competencies.
  • Understand how to apply statistics and probability techniques using the methods most commonly used to analyze health data.
  • Perform the data management operations necessary to prepare health data for analysis using statistical programming software.
  • Analyze health data (including national surveys) using relevant statistical analysis methods and software.
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