The video segments could be made longer to incorporate more information on how the modeling is done. A lot of new information was thrust into the weekly exercises. It would be better if the weekly exercises were a test of what we had learnt. A great course on the whole, anyway. The instructor was very clear.

This is an outstanding course. I am a physician and this has been very helpful in bridging the knowledge gap between what I learned in other deep learning courses and the unique situation of working with medical data. I would however appreciate a deeper dive into how to work with the DICOM format.

Introduces the fundamentals of using AI for medical diagnoses. Concepts are clearly explained and the assignments are well framed. More lectures regarding subtle concepts like MRI Image registration and calculation of confidence interval would have made the course more interesting and comprehensive

The course serves as an introduction to AI applications on medical diagnosis. The assignments are easy. However, video lectures are missing some minor concepts that suddenly appear in the programming assignment. It is recommended to take this course after you took Deep Learning Specialization.

Good course but, as often is the case, too much time was spent on fixing small errors in notebooks, such as using the "wrong" function (i.e. np.multiply doesn't work when * does due to the very specific setup of the exercise, even though they are both element-wise multiplication).

A very well structured course that covers most of the practical design challenges of deep learning applications in healthcare sector. A good foundation for people who want to pursue a career as a Machine Learning Engineer for medical diagnosis and/or computer vision.

Great course! Although the coding exercises focus more on lower level details of matrix manipulation, and not on the parts for selecting a model, building and training it. Most of the model related code is provided if form of utility code or as pretrained weights.

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.

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.

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 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.

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

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.

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.

last assignment of week 3 of this course is quite difficult to understand so I feel few more explanation should be mentioned

More detailed skills like data converion would be desirable, but still good starting point for beginners. Thanks!