Nice overview, but not much depth.

Quality of material is mediocre:

-tons of useless short videos

-inconsistent sound level

-missing lab

Some funky non editing in the videos, but overall this was a good overview.

The course appeared to be put together poorly by pulling from many different sources. Therefore it lacks coherence. There are many videos that are under 1 minute long and just there to make a statement or two or just to repeat the last video. Some videos end before instructor could complete his statement. Some videos are recordings from a classroom setting and makes it hard to follow. Also would've appreciated some support from the course team for questions posted on the discussion forum. I think topics such as machine learning in GCP deserves a bit more respect. This course needs to be planned from scratch with MOOC and Coursera format in mind.

Great course in many ways, but I encountered a lot of errors/warnings regarding outdated TF-versions. Kind of felt unprofessional at times because of that. Otherwise - great content, great tutorials, great lectures and great labs!

Need good understanding of Python and TensorFlow syntax.

Good introductory course for use of TF on GCP! Prior knowledge of TF would be handy as well. Video recordings needs improvement. Video clips from a group class setting appear in the course as well.

The title doesn't reflect the real content of this course, it is more like an introduction to start developing on ML solutions rather than to actually getting in to production on ML google engine

It would be better to present a easier material on TF. This is not for someone starting on TF.

Course content is excellent. Organization is not good. It seems like there were some errors in the order of a few quizzes as well as links to the wrong sections. If you take this course and find yourself lost on a quiz or a lab; skip it watch more content, then go back. It was probably out of order.

Tends to drag on a bit and the instructor does nothing to make machine learning sound interesting.

many of the classes had copies in the next video - or had stopped midway in conversation. - please review and re-edit.

Too advanced for a beginner.

Need to dig in more to understand

Often video repeats same things over and over, provides obvious examples.

the lab is outdated but features engineering is suitable for Data Engineer to implement on works

I understand the complexity, this is why I rate 3 stars

Good

Labs have issues with the versions.

A number of videos cut off mid-sentence.

The video flow was poor.

Some videos were too long, some were too short.

The code for TensorFlow was absolutely blown through, and then time focused on other stuff.

Most of the time in the labs was spent waiting for SSH keys to propagate - 3 of the 4 labs in the TF module(I think that's the one) should be combined and made into 2 hours total instead of 1.5 hours each because they are all extremely related and yet had separate, extremely long setup times.

para sacarle un mejor provecho al curso es necesario entender por completo python.

a bit out of date in terms of versions used

Course is an ok introduction to ML with Tensorflow. It does however needs a serious face lift when it comes to the labs. Several where broken and required debugging and some intuition to work around the bugs in order to finish them and get a grade.. If you want to learn Tensorflow, I would look elsewhere, if you want a quick course where you want the very basic and do not mind the hands labs being broken (i.e. just care about the very high level information), then sure, go ahead and enroll

7th lab was broken

Terribly Broken Labs