Course Requirements
The program consists of five courses; the first four courses provide core training in data management and analysis using R, foundations of statistical methods for data analysis, and reporting and presentation of results. The final capstone course is a guided project, in which students will synthesize knowledge gained in the first courses, develop a research question, analyze data and present their findings.
BIOS 640. Introduction to Health Data Science Methods
Credits: 3
Offered by: Epidemiology and Biostatistics (Graduate Studies)
Terms offered: Fall 2025
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Description
Introduction to the basic principles of data analysis and knowledge dissemination. Topics include introduction to R and RStudio; good coding practice and file organization; tidy data; version control; creating reproducible research reports; data visualization; R package creation and online publication.
- Due to the scheduling of this course, the standard add/drop and withdrawal deadlines do not apply. Add/drop is September 3, withdrawal with refund is September 10, web withdrawal with NO refund is September 24.
Most students use Visual Schedule Builder (VSB) to organize their schedules. VSB helps you plan class schedules, travel time, and more.
BIOS 641. Health Data Analysis: Essential Theory
Credits: 3
Offered by: Epidemiology and Biostatistics (Graduate Studies)
Terms offered: Fall 2025
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Description
Foundations for statistical inference applicable to health data. Topics include: sampling distributions and statistical inference for means and proportions.
- Prerequisites: BIOS 640
- Due to the scheduling of this course, the standard add/drop and withdrawal deadlines do not apply. Add/drop is November 10, withdrawal with refund is November 17, web withdrawal with NO refund is December 1.
Most students use Visual Schedule Builder (VSB) to organize their schedules. VSB helps you plan class schedules, travel time, and more.
BIOS 642. Health Data: Statistical Learning and Model Visualization
Credits: 3
Offered by: Epidemiology and Biostatistics (Graduate Studies)
Terms offered: Winter 2026
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Description
Basic principles of regression analyses applicable to the health sciences, covering regression (linear and generalized linear models) and inference for regression parameters; confounding, effect modification, and collinearity; model selection; prediction; and visual representations of model output, covariate-response relationships, and prediction curves.
- Prerequisites: BIOS 641
- Due to the scheduling of this course, the standard add/drop and withdrawal deadlines do not apply. Add/drop is January 16, withdrawal with refund is January 23, web withdrawal with NO refund is February 6.
Most students use Visual Schedule Builder (VSB) to organize their schedules. VSB helps you plan class schedules, travel time, and more.
BIOS 643. Theory to Practice: Analysis and Reporting
Credits: 3
Offered by: Epidemiology and Biostatistics (Graduate Studies)
Terms offered: Winter 2026
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Description
Consolidation and reinforcement of data analysis and reporting skills.
- Prerequisites: BIOS 642
- Due to the scheduling of this course, the standard add/drop and withdrawal deadlines do not apply. Add/drop is March 16, withdrawal with refund is March 23, web withdrawal with NO refund is April 6.
Most students use Visual Schedule Builder (VSB) to organize their schedules. VSB helps you plan class schedules, travel time, and more.
BIOS 644. Health Data Analytics Capstone Project 1
Credits: 3
Offered by: Epidemiology and Biostatistics (Graduate Studies)
Terms offered: Summer 2026
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Description
Analyzing real datasets and communicating the analysis and results.
- Prerequisites: BIOS 643
- Due to the scheduling of this course, the standard add/drop and withdrawal deadlines do not apply. Add/drop is May 15, and withdrawal is May 22. (Withdrawal with refund not applicable in summer.)
Most students use Visual Schedule Builder (VSB) to organize their schedules. VSB helps you plan class schedules, travel time, and more.
No exemptions or substitutions are permitted for this program. The program has been carefully designed to provide a comprehensive and cohesive learning experience, ensuring that students gain the full range of competencies needed in the field of health data analytics. To maintain this standard, students must complete all five courses to receive the certificate of completion.