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Learner Reviews & Feedback for Serverless Machine Learning with Tensorflow on Google Cloud Platform by Google Cloud

2,524 ratings
305 reviews

About the Course

This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models. OBJECTIVES This course teaches participants the following skills: ● Identify use cases for machine learning ● Build an ML model using TensorFlow ● Build scalable, deployable ML models using Cloud ML ● Know the importance of preprocessing and combining features ● Incorporate advanced ML concepts into their models ● Productionize trained ML models PREREQUISITES To get the most of out of this course, participants should have: ● Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience ● Basic proficiency with common query language such as SQL ● Experience with data modeling, extract, transform, load activities ● Developing applications using a common programming language such Python ● Familiarity with Machine Learning and/or statistics Google Account Notes: • Google services are currently unavailable in China....

Top reviews


Jan 09, 2018

Thank you very much for making this course available on Coursera, I cannot agree more the knowledge of Mr Venkat. This is a great way to help people to get started with Google Machine Learning.


Sep 08, 2018

A very good course on TensorFlow, ML and Google MLE on GCP.\n\nThe Labs are self contained and the problems proposed are very challenging. I learned a lot on this course.\n\nThank you!

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251 - 275 of 299 Reviews for Serverless Machine Learning with Tensorflow on Google Cloud Platform

By Samuel J S

Oct 10, 2018

Too much waiting time for setting up workspaces.

By Juan P

Nov 14, 2019

a bit out of date in terms of versions used

By Kevin T G

Aug 18, 2019

Labs have issues with the versions.

By Eric S

Sep 07, 2017

Nice overview, but not much depth.

By Sanjeev B

Jun 03, 2018

Need to dig in more to understand

By Walter S

Jun 24, 2018

Too advanced for a beginner.

By Cristhian T

Feb 07, 2019


By Sungryong H

Nov 23, 2019

Terribly Broken Labs

By Benjamin O

Nov 22, 2019

7th lab was broken

By Miguel A C N

Dec 07, 2018

too specific

By Alberto C V

Oct 26, 2018

good intro

By Sergii S

Aug 19, 2018

Very short

By Subhrendu B

Jul 23, 2019


By Darshak S

Aug 02, 2017

Lak is a great teacher, I love his other courses, but this one is not up to the mark. This course has been basically recorded in a live training session and just uploaded the slides and audio as a video.

There are places where he is clearly pointing at stuff on the slide in his live session, but in the video there is no way of knowing what he is exactly talking about.

Please recreate this course from scratch specifically for Coursera format. This is a very important course and students should get all the concepts.

By Murat T

Jul 26, 2017

Decent content is made very difficult to take in due to poorest editing I have ever seen on Coursera. There may not be many alternatives to this course but in terms of quality this course is not a fair value for money. There are multiple duplications, haphazard cuts, 3-5 second videos that are tied together out of context. It seems the videos are taken from a classroom presentation and shoehorned into an online course format. Very disappointing.

By Edgar L

Jan 12, 2019

As a person who already knew ML and tensorflow, the way the instructor referred to things, mixed concepts, and simplified some of them, made everything a lot more confusing that it really is. I know its easy to dismiss it in this kind of lessons as "that's a complex subject, so it's normal" but it really comes down to the instructor not being effective as he should be.

By Brett W

Nov 08, 2018

The labs are incredibly slow - I also think you need a better background in the technology being taught to understand what is going on. Again, a lot of the quiz q&a aren't covered by the material - also - trying to get support via the discussion forums is a fruitless exercise, my post was ignored - and the course is done.

By Pavel S

Feb 20, 2019

Although the course is positioned as intro to machine learning with TensorFlow, it includes too many low-level details that you are unlikely be able to conceive without prior knowledge in machine learning and TensorFlow. The parts devoted to feature engineering and hyperparameter tuning are fully chaotic.

By Prabhu c

Jun 30, 2017

Course Content was good, but poorly organised and span of the videos were very short. Difficult to focus as videos were very short. lot of videos are less than two minutes. Kindly make the videos for atleast 5-10 mins long. If possible, combine the videos, it would help the course takers in future.

By Henrique T

Sep 11, 2018

The content was good, but the labs are awful. It is already done, so you only have to play it. It isn't helpful and I don't think anyone can learn this way. The ideal is to be like the other labs, where you had to input the code yourself. This might be a very hard subject to keep in mind.

By Bo Y

Aug 27, 2017

Not updated, python 2.7

Too many small clips, should build a 4 modules * 10 videos *10 minutes each

GCP also changed, not find the right place to execute the code. Local docker encounter some issue, so I give up the code part. Really pity, that is what i am looking for

By Ramón V

May 28, 2019

I'd like the updated version of the course and lab with the new tutorials with Keras etc. Sorry about the 2 stars, apart of that I learned important things in the lab and course. I'll give a 5 stars with the updated version. Thanks.

By Dharmesh K

Jul 22, 2017

Organization of the videos is poor. The videos are too many in number and a large number of them are extremely short in duration. But it really good to learn tensorflow and usage in distributed fashion in GCP.

By Daniel I

Jan 17, 2018

It's ok as an introductory course, but videos are not aligned with labs, and I expected to extract deeper knowledge from it.

By Aleksei

Oct 10, 2019

There are many problems with the Datalab and mismatching between "mlengine" in the course and "ai-platforms" at GCP