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Comentários e feedback de alunos de Fundamentals of Machine Learning for Healthcare da instituição Universidade de Stanford

233 classificações
66 avaliações

Sobre o curso

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....

Melhores avaliações


8 de set de 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.


1 de abr de 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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51 — 68 de 68 Avaliações para o Fundamentals of Machine Learning for Healthcare

por Jiameng L

26 de set de 2021

Super helpful and engaging course

por Vasilis V

25 de jan de 2021

very elaborate and well organized

por Mike S

10 de fev de 2022

Concise and to the Point!!!

por Philip T F

10 de jul de 2022

Very Interesting Course

por Faizy H

27 de mar de 2022

very engaging!

por Sauranshu P

22 de jul de 2021


por Ernesto R

3 de mai de 2021


por Claudia K

7 de out de 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.

por Sana M

22 de set de 2021

the quality of videos was great. week 4 till week 7 have some hard to learn problems, it is better to make it more clear and easier to understand.

por Bui M H

4 de out de 2021

There are maybe too much scenes without slides, if you explain with slides combined, it would be more easy to understand and follow

por Edwin K G

26 de fev de 2021

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

por Mahdi Z

29 de ago de 2021

very good and fun, maybe would've been better with more Instances, not just talking (last2/3 weeks)

por Alena K

12 de dez de 2021

I​ enjoyed the course but for a beginner some lectures were hard to follow

por liz a

2 de jan de 2021

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

por Dasa G

26 de dez de 2020

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

por Anushka B

28 de jan de 2022

very informative

por Deepika P

10 de jan de 2022

the course can be made more better and effective y including real-world healthcare case studies

por Zakir S

13 de nov de 2020

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