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Bewertung und Feedback des Lernenden für AI for Medical Prognosis von

697 Bewertungen
123 Bewertungen

Über den Kurs

AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine. Machine learning is a powerful tool for prognosis, a branch of medicine that specializes in predicting the future health of patients. In this second course, you’ll walk through multiple examples of prognostic tasks. You’ll then use decision trees to model non-linear relationships, which are commonly observed in medical data, and apply them to predicting mortality rates more accurately. Finally, you’ll learn how to handle missing data, a key real-world challenge. These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. This course focuses on tree-based machine learning, so a foundation in deep learning is not required for this course. However, a foundation in deep learning is highly recommended for course 1 and 3 of this specialization. You can gain a foundation in deep learning by taking the Deep Learning Specialization offered by and taught by Andrew Ng....



4. Juni 2020

I am a medical image analysis enthusiast. But I always wonder why I can't I combine other patient details for extending it's application. Sure this course is awesome. I really loved it !!


21. Apr. 2020

This course was great and more challenging that I have expected. More focus on statistics and survival data which is important for prognosis. Course has a good flow and valuable content.

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101 - 124 von 124 Bewertungen für AI for Medical Prognosis

von Adolfo S

18. Mai 2020

Top course

von Kamlesh C

18. Juni 2020

Thank you

von Matteo R

27. Apr. 2020



29. Juni 2020


von Alexander Z

17. Mai 2021


von Santiago G

29. Apr. 2020


von Ivo F s

11. Okt. 2021


von Jeff D

9. Nov. 2020


von DR. M E

25. Mai 2020


von Alex Y

16. Juli 2020

Unfortunately, I would like to admit that a quality of Andrew Ng's courses declined since he personally stoped working on it... For example, I enjoyed very much all those side steps in material which Andrew did in explaining and giving an intuition to the things directly not related to the subject. He is a person with very wide expertise and this seemingly not related material brings most of the enjoyment I bring home from his courses. Now it is gone... The course is still good, but now it lucks its magic ...

Andrew, please come back ! :) You still have RL unexplained and many other things )))

von Hugues D

11. Mai 2020


Great course. Maybe I missed something but the explanation to calculate the C_Index does not cover all cases and so the assignment is rather complicated. The Harell's C-Index algorithm is given here: "" and it helped me a lot.

Thanks again for course. See you at the next one.

von Erwin J T C

22. Mai 2020

I liked this course. Some of the concepts appeared somewhat abstract but I'll just have to review integration and derivatives. There was also a lot of syntax to learn in python but it was great to learn more about how to use numpy and pandas. Can't wait to learn more in course 3: AI in medical treatment.

von Jintao R

17. Jan. 2021

The machine learning part is very basic and limited, and there are no deep learning related parts. But I have gained a lot of basic concepts about prognosis, including risk model, survival estimates, Kaplan Meier, hazard, etc. Overall, a decent course.

von Karl J

24. Sep. 2020

Good introduction to these materials, but it's difficult to use this level to incorporate into research. If you want to really use this material, you have to go deeper independently, which isn't much of an issue with the proper motivation.

von A V A

21. Juni 2020

A good overview of the key concepts, tools and techniques used in medical prognosis with interesting Jupyter notebook exercises and assignments that illustrate the applications and allow us to work hands-on with these techniques..

von Taiki H

14. Mai 2020

Good practice, but i want more hands-on assignment which focuses on how to build model from scratch, for example about COX model.

von Giulia C

17. Okt. 2020

The course is well done and the content is high quality, as in the previous course of this specialization

von Romain G

23. Jan. 2021

Interesting content, but superficial

von Nyonyintono J P

27. Aug. 2020

Great course. However, i miss how Andrew deconstructs everything - it completely absorbs all your curiosity. When you move to the assignments, without extra work you can fully understand how the libraries work. This however has a different approach, they absolutely open your mind up and enthuse you to do much more background work. really good stuff!

von Irina G

23. Juni 2020

I liked very much the first course of this specialization, but the second one is a waste of time. Too much of medical heuristics that doesn't transfer to other fields, and will be forgotten in a week after completing this course.

von Martin S

23. Mai 2021

The part of the course is repeating simple algebra operations from grammar school. Also grading of python labs is based on using specific command instead of validity of results. The ratio of knowledge gained / price is very low.

von ‍이그나티우스이완[재학 / 산

25. Apr. 2022

The explaination about fundamental and how the survival model works was terrific but the practical lab is lacking the practice and guidance regarding how survival model implemented and to interpret it

von Prithviraj J

13. Dez. 2020

This course has more to do with empirical prognosis models, nothing to do with AI.

von geoffrey a

21. Okt. 2020

Good content. Bad quality control. The QC mistakes resulted in wasting hours of student time, and coursera help desk time. It almost resulted in lost income for coursera due to refund of money being my next step I would have taken.