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

2,420 ratings
289 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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276 - 287 of 287 Reviews for Serverless Machine Learning with Tensorflow on Google Cloud Platform

By Viswanatha S

Oct 23, 2018

Hey it does not let me access my lab or course, it says, course has not started yet. This is really bad and what ever else you want to call it.

By Narendra P

Mar 18, 2018

A really substandard course. Does not do justice to its name or GCP.

This is in no way reflective of the accent or knowledge that instructor has but his teaching abilities.

By cheng y

Oct 09, 2017

the worst course in the Coursera

By Mark D

Aug 12, 2017

Should be a much longer course with more hands on programming instead of just reviewing what is written. So many videos are 30s or less, videos are cut off, or following video is incorrect. In at least one instance a video was duplicated out of order.

By Ajit K

Dec 08, 2017

This course is very high level

By Chaz R

Oct 18, 2017

I was very disappointed by this course. The spoon-feeding, no-skills-required approach was out in full force. After going through this entire course I feel like I still don't have a solid grasp of how any of the serverless machine learning scripts actually worked, because it was just "read this," "run that," "push this button." There was no explanation of what "run this" was actually doing, or how I would write something like that myself.

Most of the actual learning I'll do on this topic won't happen watching the Coursera videos - it'll happen while looking through the training-data-analyst repository and understanding the many moving parts that went unexplained during the course. I don't feel this course is adequate preparation for doing serverless machine learning with the Cloud ML Engine.

On top of all of the frustrations about the content, there's also the fact that every video for the entire course was chopped into 30 second or 1 minute intervals, making it distracting and hard to learn. This was made worse by bugs in Coursera's video playback mechanism, which prevented videos from automatically advancing, and meaning I was getting stuck every minute (for HOURS) clicking on the "Next" button.

By Leo Y

Jul 10, 2018

The most of the subtitles of this course are either out-sync or totally incorrect. Please fix it ASAP!!

By Danish S

Jun 26, 2019

Labs failed with Bad model error and deprecated command warnings. Please update the material to keep pace with changes from GCP

Overall the practical part of the course was not very useful for learning. There is no point in doing shift + enter - without diving into the code I don't think you can learn anything. On top of that errors and down rev material causes more confusion.

You guys need to pick up game. There are other places that are providing much better learning experience and updated course material than Coursera (e.g. Linux Academy). I'm very disappointed

By Deleted A

Jul 29, 2019

Can't understand his English accent.

By Dmitry B

Oct 02, 2019

A lot of labs with small resources.

By Ken F

Nov 16, 2019

Lab 7 is a mess. Whole class was an exercise in running cells in notebooks. Simplify the use case and have students do some actual coding.

By Richard B

Nov 11, 2019

Its presumably a tough course to teach, but the pace of the videos and the structure of the qwiklabs was very much out of sink. With this course expect to find yourself doing a lot of thumb twiddling while GCP 'thinks about stuff'. 15 minutes just to spin up the datangvm. Unlike many other qwiklabs on the way to GCP mastery, YOU WILL WASTE A LOT OF TIME just waiting.

Huge swathes of RED Error text to wade through wondering if it works at all.

Large numbers of very seriously worded warnings make me think this course is up for imminent decommission or rewrite.

Note that the marking is totally dependent you using the specified region for your compute, not the recommended nearest to you that many of the other courses on the subject recommend. The Qwiklabs are tedious and repetitive, and not in their own right very educational; promoting a point and click approach rather than a real learning experience. Its a good set of material if you can access it all and run through it in a single, much longer lab experience though. Course really feels much more like a few sessions at a free GCP Data Meetup than a real course for home/office learning. Would struggle to recommend.