It would have been nice if the video tutorials would explain the code section as well, and if there would have been some in-depth teaching of the code part. But this course did benefit.

Videos are good, but the code is more complex than other courses and it needs better description of what is happening, or less complicated code

Good an simple videos to understand the concept. The notebooks are very detailed and give a second layer of knowledge with practical example

Videos are good. Lab notebooks are a bit stale (still on tensorflow 2.2), so there are few wrinkles in getting them to work.

The course concepts are not in-depth enough, and the server for Jupyter notebook running is way too slow...

I expected some more explaination for the concepts. However from tensorflow website, more could be learnt.

The coding part was hard to understand. If that part could also be covered in videos as a tutorial.

Great introduction to unsupervised learning. However its an easy course with not much to offer

challenging but i wish the quiz questions were more useful in testing our understanding.

It would be grate that the examples have been updated to the TF 2.0 version.

i loved it. I have an undertsanding of different deep learning models

Was a really fun course, but the final assignments were very lengthy.

Good material but almost all the labs are too slow to run properly

Good introduction to Deep Learning Models with Tensorflow

Very informative, could use some more room for practice.

Lab content must be updated with latest TensorFlow.

Thank you. thought it's could be more deeper

no audio in the last learning unit 5.

some questions are a bit confusing

Met expectations

It is ok

good

This is a pretty good course on the different types of neural networks and their cousins. The presentation slides are really well done. The examples are programmed in TensorFlow. But the course does not really teach very much about TensorFlow itself. The opening lecture on TF describes it in terms that suggest this was created for TF 1.x, rather than the new structure in 2.x. But that turns out not to be an issue since they go into little detail on TF itself.

The programming examples are really good. However, most of the time, the CognitiveCourse.ai web site on which they run is usually not working. So you often cannot use the labs in conjunction with the lectures. You have to go back and access the labs sometime when the website is working.

While the lab and videos explained the concepts really well, the codes from the labs are outdated. They are using tensorflow version 1, while tensorflow version 2 (current version) is very different. I have to go outside of this course to learn the new codes.

Other than that, every other aspect of the course is good. explanations are clear, videos and diagrams are very detail. Just the right amount of labs etc

The course is good in order to gain an understanding of the different types of Neural Networks, Algoritms etc. are present and what their purposes are. However, the course stems from 2019 and doesn't seem to be updated that much if at all. The mechanisms and coding required have change significantly since them, so the actual exercises are kind of outdated.