Opiniones y comentarios de aprendices correspondientes a AI for Medical Diagnosis por parte de deeplearning.ai

Really nice and well-explained

Last assignment was insane.

The problem is quite easy

The course is too basic.

excellent course

finally

The course is useful but the grading is terrible. In case of testing the code based on test cases, the grader looks into the code and only passes the code if it's written in a way consistent with the hints. This means that vectorized computations are out and one has to implement loops by hand. Furthermore, since its not clear what the grader is complaining about, one ends up wasting a lot of time if one really cares about "completing" the course. Furthermore, despite a lot of complaints the instructors have not fixed this issue.

This is interesting topic and I learnt how these things are done in medicine. However, from technical point of view, there are many issues. Bugs, typos, unexplained terms (dear learner, now please calculate background ratio) make this course messy and leaves the taste of "rushed product of corona crisis".

The course is very shallow. It explains in detail some simple concepts like Sensitivity and Specificity and then immediately touches complex topics like image recognition architectures, without much explanation. The course materials are unclear and the auto-grader is buggy.

Instructions in the graded assignment did not have clear instructions. Sometimes, correct implementation was graded 'incorrect' by the grader. Also, videos of the ROC curve was not clear about why it is needed or what does it say about a model.

Hi Sir/Madam,

i took this course then realised it is beyond my understanding. I am a grade 12 student . please help me to cancel this ,so, i can take another course which can benefit me.

i will appreciate your help.

thanking you

Too much task was given but less explanation. It was really hard to complete all the tasks. It would be better if easiest tasks are given or more explanation with huge explanation.

Good instructor but concepts were not taught in-depth. The assignments gave only a superficial understanding of the subject and cannot prepare one for working in the industry.

The course touches on several aspects of ML for medical. However, the content seems too little and narrow. Only a few cases and architectures are explored.

Would like it if the projects were more in-depth. We should understand the end-to-end pipeline: from preprocessing to deploying in production

Some concepts used in the assignments are note explained in the videos e. g. the calculation of AUC.

Content is too shallow, could have gone deeper into some topics.

The codes should have be explained ...

Too general for practical usage

good as an introduction

Fairly shallow.

I first took Deep Learning Specialization by Andrew and then took NLP specialization by Younes Mourri and then this course. One difference I noticed that Andrew explained all the stuff by himself in detailed 8-10 min video and here these in these two coursers, the two instructor explained concept in 1-2 min video and left the remaining concept to learned by ourselves through notebooks. Andrew put much more effort than these two guys.

Did a good job of explaining some of the terms and processes involved in using AI for medical diagnosis, but the flow and organization of the course were really poor and the methods taught were not general enough to be able to extrapolate to use in new ways outside of the course.

There is no reply or response to discussion forums from the instructors and assessment of the assignments are always zero so I can not pass to week two even my assignment's outputs are matched with the correct ones .