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Отзывы учащихся о курсе Fundamentals of Machine Learning for Healthcare от партнера Стэнфордский университет

Оценки: 140
Рецензии: 41

О курсе

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....

Лучшие рецензии

8 сент. 2020 г.

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 апр. 2021 г.

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 из 41 отзывов о курсе Fundamentals of Machine Learning for Healthcare

автор: Mike W

4 дек. 2020 г.

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

автор: Kushal A S

17 окт. 2020 г.

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

автор: Kent H

12 янв. 2021 г.

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

автор: NADY E B

6 дек. 2020 г.

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

автор: blue a

20 дек. 2020 г.

Tremendous learning and outstanding presentation of concepts.

автор: Ann V G

3 окт. 2020 г.

An excellent introduction. Concise. Helpful citations.

автор: Anton L

21 окт. 2020 г.

Outstanding team performance by the two lecturers

автор: Lori S

14 мар. 2021 г.

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

автор: Kabakov B

6 окт. 2020 г.

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

автор: Vasilis V

25 янв. 2021 г.

very elaborate and well organized

автор: Ernesto R

3 мая 2021 г.


автор: Claudia K

7 окт. 2020 г.

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.

автор: Edwin K G

26 февр. 2021 г.

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

автор: liz a

2 янв. 2021 г.

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

автор: Dasa G

26 дек. 2020 г.

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

автор: Zakir S

13 нояб. 2020 г.

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