Chevron Left
Back to Fundamentals of Machine Learning for Healthcare

Learner Reviews & Feedback for Fundamentals of Machine Learning for Healthcare by Stanford University

260 ratings

About the Course

Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. But we will never realize the potential of these technologies unless all stakeholders have basic competencies in both healthcare and machine learning concepts and principles. This course will introduce the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. We will explore machine learning approaches, medical use cases, metrics unique to healthcare, as well as best practices for designing, building, and evaluating machine learning applications in healthcare. The course will empower those with non-engineering backgrounds in healthcare, health policy, pharmaceutical development, as well as data science with the knowledge to critically evaluate and use these technologies. Co-author: Geoffrey Angus Contributing Editors: Mars Huang Jin Long Shannon Crawford Oge Marques The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. Visit the FAQs below for important information regarding 1) Date of original release and Termination or expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content....

Top reviews


Sep 8, 2020

Amazing course teaching the innumerous opportunities in the healthcare sector and the application of AI in the same. Beautifully drafted course with intriguing tutorials and exercises.


Apr 1, 2021

This was a great course, the presenters really gave a clear view about the differences which could happen when working with health related data set. Very well done,

Filter by:

26 - 50 of 71 Reviews for Fundamentals of Machine Learning for Healthcare

By Raimundo N

Mar 28, 2022

By hani j

Oct 5, 2021

By Marcelo M C

Jul 15, 2022

By Jau-Jie Y

Jul 12, 2021

By Jonathan W

Feb 2, 2022

By Gonzalo R C

Jan 19, 2022

By Sandro M

Aug 20, 2021

By María F R E

Jan 16, 2022

By Chetan D

Mar 4, 2021

By Mike W

Dec 4, 2020

By Kushal A S

Oct 17, 2020

By Sabine F

Aug 1, 2022

By Kent H

Jan 12, 2021

By Kedir O

Jul 30, 2022

By Scott L

Nov 6, 2022


Dec 6, 2020


Jul 19, 2021

By blue a

Dec 20, 2020

By Andrew M

Jul 16, 2022

By Ann V G

Oct 3, 2020

By Vera S

Oct 20, 2021

By Huma P

Jun 7, 2022

By Anton L

Oct 21, 2020

By Lori S

Mar 14, 2021

By Vincent C

Nov 10, 2021