This course covers a lot about the data pre-processing, and the tools available in Google Cloud to enable the gruelling tasks. Thanks very much for the lectures and training labs. Very informative.
It's a pretty interesting course, specially that's the only one that teaches featuring engineering with a focus on production issues, but it assumes some knowledge with apache beam, and dataflow.
by Bielushkin M•
by Said A•
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.
by Yaron K•
Feature Engineering is critical. The course attempts to explain both the principles of feature engineering and it's implementation on Google cloud in a few hours - and as a result both are short-changed. Note also that unlike other courses on Coursera you can't audit this course, can't download videos and some of the most insightful videos don't even have subtitles.
by Evren G•
As ever excellent course content, the major let down and loss of star is because of the labs. There are no graded lab exercises where you have to think about and apply your theoretical learnings. Instead you get python notebooks that have completely prepopulated code. So the only thing you need to do is run the cells. A missed opportunity for excellent learning.
by Michał K•
In general, this course is very well prepared, covers a good piece of material and I'm leaving it with a lot of new things to try. One thing I would correct in the future: more coding. Don't get me wrong, labs are quite good in terms of examples quality, but since everything is already there, it is difficult to "learn by doing".
by Sanket N•
Course is explain feature engineering in such a way that is it is to understand what is purpose of it and also how to use it. Very good course.
One issue I found that, big query in second last model is not working. I have to search and fix issue in big query to run it. It is kind of distracting from main objective of Lab
by Francois R•
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...
by Joe L•
Great topics, the instructions are great. The only suggestion is cut down the number of different videos. just combine them together. 15 3 mins is not a great experience vs 3 15 min videos.
by Timothy L•
Some of the labs had big query errors, and some of the google cloud interfaces changed, so careful when doing the labs, the options and the buttons may have been shifted or renamed
by zios s•
Its a graet course team me one of the most important took "Apache Beam" I defiantly use this in my upcoming projects. I only give 4 star because of poor teaching by "Carl Osipov"
by alireza s•
The part about tensorflow transform in the end is super rushed and not that clear, other than that the course is well made and clear in its instructions and very recommended!
by Daniel M•
Difficulty scaled dramatically in this course compared to the previous ones. I would have liked a slower introduction to apache beam and more information about tf.transform
by Gaurav B•
It had a great coverage of the different options available, however, I would prefer a bit more detailed coverage and hand-on should be from easy to tough.
by Kevin C•
In contrast to other courses in this specialization, this course had some meat in it and was more than just a thinly disguised ad for Google Services.
by Michael E•
The course was very informative, but I think that there are opportunities for the student to have to figure out how to do more portions of the labs.
by maheboob p•
faced multiple issues
a)Qwiklab wasnt allowing to login with error that said "account is locked"
b) labs were not as interesting as others
by Wang Y•
Nicely explained concepts with real world examples! Could have explain more about the code and the meaning behind some of the qwiklabs.
by CY J•
Good to learn the Feature Engineering. Tried all of Graded External Tool using Cloud Shell because AI Platform Notebooks doesn't work.
by Harm t M•
This was hard. Not directly applicable to where I am in my machine learning career, but good to know in the future, nonetheless...
by Keith H•
Love the course but this specialization is fairly complex and is new type of thinking as such take a bit of understanding.
by Gregory R G J•
I learned a ton but it appears as technology grows and changes updates to the platform is sort of static.
by Zezhou J•
The content is quite rich in this course. I feel decomposing it into two weeks might make it structurally more clear.
by Frederik C•
Very well explained, lost time during tutorials because of apache beam version conficts with google cloud dataflow
by Roberto T•
starts off with a bang, and generally excellent. the tf.transom section needs a bit of freshening and refocusing
by Vamsi K B•
This course gives an ample understanding on the significance of Features and Data in Machine learning.