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 |
| BIOST 509 |
Introduction to R for Data Analysis in the Health Sciences |
| BIOST 544 |
Introduction to Biomedical Data Science |
| BIOST 546 |
Machine Learning for Biomedical and Public Health Big Data |
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| 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) |
| DATA 515A |
Software Development for Data Science |
| EPI 555 |
Statistical Methods For Spatial Epidemiology |
| HIHIM 405 |
Introduction to Health Data Analytics |
| HSERV 521 |
Advanced Qualitative Methods in Anthropology and Public Health |
| HSERV 527 |
Intro to Qualitative Methods |
| HSERV 584 |
Assessing Outcomes in Health and Medicine |
| HSMGT 514 |
Health Economics |
| HSMGT 552 |
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 |
| LING 570 |
Shallow Processing Techniques for Natural Language Processing |
| LING 571 |
Deep Processing Techniques for Natural Language Processing |
| LING 572 |
Advanced Statistical Methods in Natural Language Processing |
| STAT 509 |
Econometrics I: Introduction to Mathematical Statistics |
| STAT 512-513 |
Statistical Inference |
| STAT 535 |
Statistical Learning: Modeling, Prediction, and Computing |
| VALUES 512 |
Justice Matters |