Seems very easy course. Good for beginners.

a bit easy but well put together material

Basic course but best to start for Keras

Great course to kick off as ML Engineer

Clear, easy to follow

Good Assignments,

very Good

Excellent

Fantastic

good

good

The content is for new comer of tf.keras OK.

When you have been in this area for a long time but still want to finish the whole specilization, pls go ahead and finish the final exam directly.

The week 2 of describing the back propagation is pretty nice, not too much detail but somehow it is using an example which is even clear at some points comparing to Prof.Ng 's course, however, wont let them competet each other

The course materials need to be updated to clearly show how to get to the labs. The video talks of one way but the real method is different. Although one is supposed to use the IBM Labs the staff gives direction to use google colabs. I downloaded the files to local machine and discovered the dependencies by accident.

One should not expect to learn much about Keras here. It is a basic introduction to DL and NN.

A very light introduction into training Neural Networks with Keras. Content is of good quality, but there is not enough of it to qualify as a course. Some weeks contain ~20 min worth of videos and a quiz. I bet all the material could have been condensed into just 1 week of video lectures and a final project week.

Final project is good, but it would be way better begin auto-graded instead of peer-graded.

A good course overall, with reasonably good explanations and step-by-step labs. However, the course did not really cover Recurrent Neural networks and Auto Encoders properly: the theory part was barely an overview and there were no code examples or labs related to them. It is a bit disappointing to see them in the syllabus but not covered in the course.

This course is too shallow in terms of content and too light in terms of workload, it can only serve as a stepping stone towards a more advanced course. It does accomplish its stated goal of offering an introduction to many Deep Learning concepts and Keras, but nothing beyond that.

The course content is very brief not much for getting a better understanding of topics. It can be a good starting course for someone but if you are interested in getting details of topics I recommend taking the courses of deeplearning.ai

Very light. The current material requires much less time to finish than annoucned at the beginning of the course. The teacher could have hence taken some time to go more into details, even though it's an introduction course

The course should have discuss either deeplearning or keras library more deeply. As it is not discussed, at least other resources or courses should be mentioned for interesting strudent who is prone to advanced learning.

Course is too easy... And some guy copied my work for the final assignment after he reviewed it. IMO it should not be possible to review someone else's work, when you haven't passed the course yourself yet.

The course was very elementary and brief but well organized. Week 4 (supervised and unsupervised models) is definitely too short to grasp the ideas behind the different designs.

The topic explanations are pretty rushed for beginners. The assignment has been unnecessarily added with lots of iterations that created issues with debugging and testing.

Extremely simplified course of ANNs, tells you how to create a simple ANN, but you are not going to learn almost anything about how it's components work together.

Good introductory course, just scratches the surface. What I did not like is that the instructor just reads the content for you. Could be improved.

It seems more a review of concepts that you need to have already have studied on other courses/books than a real introduction.