The tf.transform and Apache Beam concepts are not explained in simple ways.

Also the lab jumped from simple programs to complex programs.

A lot of the code, did not work.

The videos are good and better than the last two courses in the specialization; however, the labs lack proper instructions and not that helpful. This course seems like more of an advertisement for Google Cloud Platform than feature engineering: details of engineering part is hardly covered in the course; more emphasis is on demonstrating on how to do it on GCP.

Had a lot issues with the quiz grader.

The assessments do not actually require writing any code; you just execute the given code blocks. Little knowledge will be retained unless students actually write code and solve problems, even for the motivated ones who read through all the given code.

Would appreciate more guidance on the exercises

Every aspiring Data Scientist or data analyst MUST take this certification!!

It's nice

great course and very intrsting

Lovely Course. Thanks Google

개요를 알게 되서 좋음

Thank you.

nice & fun

Awesome!

faced multiple issues

a)Qwiklab wasnt allowing to login with error that said "account is locked"

b) labs were not as interesting as others

Excellent course, great trainers.

Very interesting theory, shows the power of Tensorflow in the field. I had trouble with the last lab though, which when I ran it step by step, would block my qwiklab account because of resource limitations...

Pros: Tensorflow is an excellent framework for deep learning

Cons :

1- The way this material is designed is 10 X SHIT

2- Either teach properly or don't teach at all.

Basically this course would receive four stars, but repeated problems with qwiklabs had a severe impact on my overall experience. I got thrown out three times in a row (and my account locked) during dataflow lab.

Every time I had to request unlockin of my account, which took half a day every time. When requesting advice to avoid this error, I got offered the general and vague explanation that I "should only use the resources required by the lab". I am 100% sure that I didn't use any extra resources, including zones and regions.

The Coursera's helpdesk went behind the excuse that Qwiklabs is a third-party service. That may be the case, but since Qwiklabs has been integrated into the Courseras' course, the ultimate responsibility lies with Coursera.

I hope that Coursera will co-operate with Qwiklabs to sort out this very annoying problem.

Great teaching

Great, Labs were redundant at times.

A separate course to emphasise the role and importance of feature engineering in machine learning is what really got to me. With examples and explanation how your model can improve with feature engineering did the trick. Before, it was just a note in my notebook. Now, I really understand the importance of it.

However, having said that, the course could have been much shorter. It feels like, these courses are Google way of promoting its ML Cloud services.

This was hard. Not directly applicable to where I am in my machine learning career, but good to know in the future, nonetheless...

Hope all the materials in this course will be updated soon. However , thanks to all of you!

The content is great, not just from a technical point of view but for all the know-how that the different instructors share during in the videos and labs.