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

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.

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

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While the lab and videos explained the concepts really well, the codes from the labs are outdated.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

Lots of code and theory heavy, which is not a bad thing, but there is little thought given over to the actual learning objectives. There is also no real opportunity to practice learning to use TensorFlow. There are likely better tutorials out there, which is a shame because a lot of effort has gone into this course.

The Course was more about the the types of neural networks and how they work than Tensorflow, except for week 1 where we had a Tensorflow introduction, I could gather a lot from the programming assignments but I think there needs to be more about the Tensorflow library in the lectures.

I found the practice notebooks of this course to be lacking due to two reasons: 1) The notebook links are broken, resulting in my not being able to complete them. 2) The notebooks do not have practice sections where we could code ourselves following the examples given.

The course is good, but 1) the lab environment is not working at all.... I had to run the notebooks on google colab ! 2) The code is outdated. Tensorflow 2.x is out.

Overall good course but lectures were a bit weak on underlying math, compared to labs which made it a challenging at times to tie the two parts together.

One of the better courses in the IBM AI certificate. The notebooks are nicely annotated and have more relevant information than the video lectures.