Awesome but difficult

course is good useful

Excelente curso

Amazing courses

Amazing course

Excellent !!!

Great course

Great course

Thank you

Brutal.

Thanks

Excellent. The first programming assignment is definitely challenging and long! The other two are shorter but are still exciting enough as they show the actual application of AI in medicine. I loved the course. Just a formality not to give 5 stars

Many interesting things are teached in this course, such as interpreting ML and DL models. Yet i don't feel the exams and the notebooks really make you ready to use these skills on the field, it's just an introduction. 4 stars rating.

The assignment for the first week was out of scope for the course in my opinion. It was too much focused on a good handling of pandas which is rather difficult for people who are not experts in pandas

Outstanding hands-on machine and deep learning eHealth projects with real-life applications.

I wish I could download the support material for this course

Weeks 2 and 3 were excellent! The week 1 programming assignment was tedious and even the quiz was a repeat from course 2.

The assignment was very heavy. It was better to have some practical case studies to understand the implementation steps.

Please check out my comprehensive review on LinkedIn. Thank you!.

Unable to use it on real datasets.

Unique awesome course

Thanks coursera

I thought the course was well-taught and interesting, but I felt that it was more of an Introduction -- Here are some things you can do with AI and ML techniques in the context of Medicient -- rather than a detailed explanation of how the techniques work and how to use them in practice, so probably more valuable for Medical professionals than AI/ML specialists. It would be great to have some follow-on courses that get deeper into the technical details; the Coursera Deep Learning Specialization is a great example.

In general, the programming exercises were valuable and engaging, but I have a particular gripe with the grading: In some cases, I had to spent quite a bit of time making micro-adjustments to my program text to satisfy the rather picky criteria of the grader, including one case were I had to remove spaces between tokens in an expression in order to pass. I really think the criterion for grading should be correctness of results rather than conformance of the program text.

This name of this course is in my opinion wrong. It is much more about model tuning and evaluation than medical treatment in itself. Though it gives very useful and numerous techniques for this purpose, the assignments are quite boring, especially implementing the gridsearch in week 1 (quite out of the scope of the course, and much too long) or copying/pasting Keras functions in week 3.

The videos are however once again very clear and interesting.

The lecture videos are great, but the Jupyter labs are entirely convoluted.