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

141 ratings
41 reviews

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,

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26 - 41 of 41 Reviews for Fundamentals of Machine Learning for Healthcare

By Mike W

Dec 4, 2020

great overview to explain ML to all members of a team developing healthcare applications of AI

By Kushal A S

Oct 17, 2020

Nicely Framed and Executed in a simple language so anyone can catch up earliest.

By Kent H

Jan 12, 2021

Great course. Thank you so much for the time and effort putting it together.


Dec 6, 2020

A bit too technical yet very interesting. Excellent course. Thanks!

By blue a

Dec 20, 2020

Tremendous learning and outstanding presentation of concepts.

By Ann V G

Oct 3, 2020

An excellent introduction. Concise. Helpful citations.

By Anton L

Oct 21, 2020

Outstanding team performance by the two lecturers

By Lori S

Mar 14, 2021

"a labor of love' indeed; wonderful ! thank you!

By Kabakov B

Oct 6, 2020

101 to ML. Like Ng's book ML Yearning.

By Vasilis V

Jan 25, 2021

very elaborate and well organized

By Ernesto R

May 3, 2021


By Claudia K

Oct 7, 2020

It is really good overview for people coming from a commercial background but it is done in a pretty fast manner such that I need to listened into videos again to appreciate the concept. A lot more work and reading needed to really get myself on board. I suggest a even more basic AI course prior to this module. Otherwise, if you are from Healthcare, the first 2 modules structure overviews (also very good but more US-centric) are good revisions and segway into the later module.

By Edwin K G

Feb 26, 2021

Would have been helpful to go through all stages of a model development top show how things tie together. Otherwise well done.

By liz a

Jan 2, 2021

it was a very interesting course and look forward to taking more.

By Dasa G

Dec 26, 2020

Great instructors. The mathematical part threw me off as an MD.

By Zakir S

Nov 13, 2020

I was hoping to learn with hands on assignments but unfortunately it was mostly lectures.