RK
Jul 2, 2020
It was a nice course. Though it covers basics. A follow-up advanced specilization can be made. Overall, it's sufficient for beginner for an engineer trying to learn application of AI for medical field
KH
May 26, 2020
Throughout this course, I was able to understand the different medical and deep learning terminology used. Definitely a good course to understand the basic of image classification and segmentation!
By Ravi C
•Apr 25, 2021
Expected content that would be new but found content which I was already familiar with. Disappointed a little on that. Course could have some more interesting and new content.
By Harit J
•May 18, 2020
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.
By nithin s
•May 8, 2020
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.
By Sundeep L
•May 1, 2020
Would like it if the projects were more in-depth. We should understand the end-to-end pipeline: from preprocessing to deploying in production
By Laurin R
•Jan 3, 2021
Some concepts used in the assignments are note explained in the videos e. g. the calculation of AUC.
By Marcel L
•Mar 7, 2022
Its a good introduction course, but it spends alot of time going over a lot general concepts.
By Pedro G
•Nov 19, 2021
The lectures are good, but I experienced many issues on homeworks.
By Thiago M d O
•Jul 21, 2020
Content is too shallow, could have gone deeper into some topics.
By mohit r
•Jun 21, 2020
The codes should have be explained ...
By Andrey A
•Aug 22, 2020
Too general for practical usage
By Liwen T
•May 16, 2023
not a deep course. very basic
By Hanan S A
•Jul 13, 2020
good as an introduction
By Matthias K
•May 7, 2020
Fairly shallow.
By Apoorv G
•Aug 8, 2020
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.
By Michael L
•Jan 9, 2021
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.
By Tolou S
•Mar 6, 2023
It was not covering the preprocessing and in-depth hands-on but was mainly focused on the beginner material and being able to run the code or evaluate the model rather actual preprocessing of the data or the modeling part.
By Kemal U A
•Sep 2, 2020
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 .
By Duncan L
•Jul 2, 2020
A far too brief overview of AI applications in medical diagnosis - only really covers image analysis and even then is cursory at best. Disappointing as I have found the other deeplearning.ai courses quite helpful.
By Houssem A
•Jun 20, 2022
Very basic, and the assignments are basically NumPy arrays manipulation rather than actually using ai on real-world data to get predictions.
By krishan s
•Jul 6, 2020
Not useful. Probability distributions are not intuitive mostly.
By Жулдызжан С
•Jun 10, 2020
This course relays on "add one line" code too often.
By Julian S
•Dec 5, 2021
The course was quite shallow, and the actual challenges of model selection, training or building appropriate augmentation steps were pre-built and not discussed in any detail.
The coding challenges were using badly outdated package versions, for which documentation does not exist anymore and which do not represent best practice usage of the libraries involved.
On top of that, the coding challenges expect a very specific solution, while not considering equivalent implementations as correct (case in point: In the week 3 coding challenge, I used np.transpose where the challenge used np.moveaxis. I prefer transpose since it clearly and explicitly states where _all_ the other axis go, while moveaxis makes that change of state implicitly.)
Finally, the grading of the last coding challenge does not respect the special cases that are explicitly mentioned in the excercise itself. The "standardize" function to be implemented explicitly mentions the possibility of a slice having a zero standard deviation and the pre-coded framework handles this special case correctly. However, if one changes the selection of the slice in the cell before, which the user is encouraged to do, it is possible to obtain an empty slice. The grader expects a unit standard deviation though, without checking this edge case.
The shallow content and lackluster excercises, as well as the common mistakes in the presentation videos (sometimes corrected by a "question" popup during playback) do not give the impression this course was prepared well.
By Aliakbar D
•Jul 28, 2020
I have done several of AI courses including the TensorFlow. While the TensorFlow course, gives you a neat and excellent hands on on how to build a network from scratch or implement easily a CNN such as Inception V3, this course make you confused as what sort of aim it follows. Overall confusing and not useful. Though you find some good stuff in the videos but the design and strategy of the course is meaningless.
By Jamal H
•Aug 19, 2021
Lectures are short, mainly focused on programming details (how to subsample and image or how to calculate an error). The assignments do not help understand the AI part of the medical diagnosis. It can be considered as an intro course for the AI for MD.
By NICOLA F
•Jun 1, 2021
No for medical students. Terrible time loosing