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The required BHI core coursework reflects the importance and interaction of our practice domains ranging from human biology to clinical medicine and consumer health to public health. Students complement their core coursework with additional courses in statistics and advanced research methods, as well as electives drawn from other UW academic units. Departmental seminars are also offered that present new and integrative research in the field.

Please see the MS coursework requirements and PhD coursework requirements for full details.   Below is a more informal listing of the classes, including some example electives:

BHI Program Core Coursework Requirements: All courses listed below are to be numerically graded, with the exception of Research Seminars, and the student must pass all these with individual grades of at least 2.7. Courses count for 3-4 credits (in parentheses), for a total of 30 credits.

  • BIME 530   Introduction to Biomedical & Health Informatics (3)
  • BIME 533   Public Health and Informatics (3)
  • BIME 534   Biology and Informatics (3)
  • BIME 535   Clinical Care and Informatics (3)
  • BIME 537   Informatics Research and Evaluation Methods (4)
  • BIME 550   Knowledge Representation and Applications (3)
  • BIME 554   Biomedical Information Interactions and Design (4)
  • BIME 543   Consumer Health and Informatics (3)*
  • BIOST 517 Applied Biostatistics I (or BIOST 537 Survival Data Analysis in Epidemiology or other equivalent biostatistics graduate course with approval) (4)**

*  effective for Autumn 2015 cohort and later
** effective for Autumn 2014 cohort and later

See our course description page for more detailed information about each course. The above nine courses are required for all MS and PhD students. (In addition, all postdoctoral fellows must take four of the BIME courses; please see postdoc coursework requirements.) BHI core courses may be completed during one’s first year, as shown in the table below. Each course is offered only once a year in the quarters indicated. MS Students are not required to take all of the BHI core courses during their first year, but instead, may take core courses with more flexibility in order to incorporate electives, rotations, and research.

Fall Quarter – First Year 

  • BIME 530 Introduction to Biomedical & Health Informatics
  • BIOST 517 Applied Biostatistics I
  • BIME 543 Consumer Health and Informatics

Winter Quarter – First Year

  • BIME 550 Knowledge Representation and Applications
  • BIME 533 Public Health and Informatics
  • BIME 537 Informatics Research and Evaluation Methods

Spring Quarter – First Year 

  • BIME 554 Biomedical Information Interactions and Design
  • BIME 534 Biology and Informatics
  • BIME 535 Clinical Care and Informatics

Graduate students must also take a number of  research seminars and electives. Please see the MS coursework requirements and PhD coursework requirements for full details. The electives below are just examples, and there are many other courses that may be appropriate electives for BHI students.

Research seminars (6 for MS, 12 for PhD)): In addition to the numerically graded courses listed above, all students must complete six (MS) or twelve (PhD) BHI research seminar credits. Please see the MS coursework requirements and PhD coursework requirements for details about these research seminars.

Professionalism and Communication in BHI Seminars: In addition, all PhD and MS students must take a series of 1-credit seminars on Professionalism and Communication (BIME 585,586, 587) . Each seminar is 1 credit and should be taken in Autumn, Winter and Spring quarters of their first year.

BHI Research Seminars:

  • BIME 590 Selected Topics in Biomedical and Health Informatics
  • BIME 591 Biomedical and Health Informatics Research Colloquium
  • BIME 585, 586, 587 Professionalism and Communication in Biomedical Informatics

Example electives outside BHI:

ASTR 598
Topics in Theoretical Astrophysics

Introduction to R for Data Analysis in the Health Sciences

Introduction to Biomedical Data Science

Machine Learning for Biomedical and Public Health Big Data

CHEM E 599
eScience Community Seminar/Big Data Seminar Course

CSE 442
Data Visualization

CSE 512
Data Visualization

CSE 517
Natural Language Processing

CSE 527
Computational Biology

CSE 544
Principles of Database Systems

CSE 546
Machine Learning

CSE 583
Software Development for Data Scientists (4)

Software Development for Data Science

EPI 555
Statistical Methods For Spatial Epidemiology

Introduction to Health Data Analytics

Advanced Qualitative Methods in Anthropology and Public Health

Intro to Qualitative Methods

Assessing Outcomes in Health and Medicine

Health Economics

Health Administration and Business Law

INFX 565
Designing Information Experience

INSC 518
Seminar in Human Information Interaction

INSC 541
HCI Design Foundations for Interactive Systems

INSC 543
Value Sensitive Design

INSC 545
User-Centered Design

Quantitative Pharmacology

Pharmaceutical Outcomes Research and Policy Seminar

Systems Pharmacology I: Foundations

Systems Pharmacology III: Kinetics

PHG 512
Genetic Epidemiology II

STAT 509
Probability Theory and Statistical Inference

STAT 535
Statistical Computing in R

STAT 542
Statistical Methods for Environmental and Climate Sciences

STAT 570
Statistical Methods for Big Data

UW 591
Introduction to Computational Neuroscience

Justice Matters