The contents offered by the course are really useful. However I need to review again and practice more to fully acquire the techniques as even I passed all the tests, I think I couldn't make complete notebooks in the course from scratch without guidelines.

Hello,

I enjoyed taking this course. It would be great if assignments could be debuged, I tried downloading the assignments to debug using vscode but some parts of the assignments(datasets or some functions) were not there to be downloaded.

Thank you

This was a great course for getting a high-level understanding of AI's applications in medical diagnosis.

The only issue is that the assignments are auto-graded which, coupled with bugs, can make submitting assignments very frustrating.

Great but 1) all notebooks must be moved to Tensorflow 2 and Pytorch 2) it's not a Deep Learning course but a data course (for people who want to really understand the classification/Unet models, they need to study another DL course)

Course data and related util files with reasonable explanations will make this course magnificent. I spent a lot of time figuring out differences while I try it in my local engine due to version differences.

Pleasant pacing, very clear and concise lecture material. I was really frustrated with the final assignment though. Would be nice if the grader gives something more instructive than correct/incorrect.

A good course to understand the use of Deep Learning and AI in Medical Diagnosis. In this course, you can understand different ways to segment and analyze the images of brain tumors and X-Rays.

Use cases selected were really nice, Videos should carry more detail technical aspects and could be bit more lengthy and Assignments should consider multiple options to solve given problem

too hard

too little explanation in the exercises,

definitely not for beginner,

this is an expert class course,

even an experienced student, who's familiar with tensorflow might struggle a bit

A good course with challenging assignments. However, the assignments could have been a little less self explanatory and should have triggered deeper and more individualistic thinking.

The assignments are extremely simple; mostly just implementing an equation in Python. The rest of the notebooks are basically readings. Maybe give a little more coding practice.

A good introduction to the problems of using AI for medical diagnosis. A little bit too much hand-holding in the final assignment sections, especially for the MRI project.

The course is build in a way makes it easy to learn. I liked how the assignments had been built and the way of grading quizzes

I think we need a special course for U Net

Very in depth course that covers manipulation of multi-dimensional data. A little copy paste but that seems to be the par on Coursera. Very glad I took the course.

Very abstracted and high level course, no "intution" presented compared to Machine Learning of Andrew Ng; Nevertheless, still a great course for AI in Healthcare

This course is a good starter for applications on AI on medicine. I enjoyed. But I felt there can me little more explanations instead of a very short videos.

The course content was great and all theoretical concepts were clearly explained but, the instructions in the programming assignments were a bit unclear.

Getting the right code for week3 assignment was really time-consuming - still have not found what was the error giving me the standardize function

Nice course to learn basics of machine learning as well as get your hands dirty with application of artificial intelligence to medical diagnosis.

it's good, I expected it to be richer, but I guess there's no much development in that area to teach currently, I hope it will evolve with time

the codes do not work in google colab, they can only work in the environment on coursera, which is bad, but otherwise it was a good training

There were a lot of problems when I was completing the programming task in week 3. I Think that many points are not sufficiently explained.

The lectures are great, but the labs could use more practicing/exercises than just reading a notebook already filled with code that works.

So nice and complete. May be some programming assignments need to be more clearer or explained, but over all; great course. Thank you.

It is so much better than courses from NLP specialization. But still too many "translate well-known formulae to python code" tasks.