Course Description
Today, anyone can train a near state-of-the-art machine learning model with a laptop, a dataset, and a few lines of code. For many applications, model building is no longer the rate-limiting step in using AI and machine learning to improve human health. In this course, we examine the other areas that need to be addressed -- from choosing the right problem, to moving technical advances into the clinical setting and making sure we are actually improving outcomes that matter. This course is geared at anyone who is looking to use AI and machine learning to make a real-world positive impact on human health. Students from all schools welcome. The course can be taken for 1 unit (lecture attendance/participation) or 2-4 units, which will include a project component. Class website: https://cs337.stanford.edu/
BIOE 277
Units: 1–4
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Typically Offered
Not Available
Grading Basis
Medical Option (Med-Ltr-CR/NC)
Class Level
Graduate
Instructional Mode
In Person
Gen Ed Requirement(s)
None
