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Learner Reviews & Feedback for Machine Learning in the Enterprise by Google Cloud

4.6
stars
1,481 ratings

About the Course

This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives....

Top reviews

MB

Dec 31, 2018

thanks for the great work. There is so much to learn and I appreciate the effort you made to break things down and providing lab while making the hard decisions on what to commit.

MK

Jun 7, 2020

This course is so really good to learn about the general knowledge and skill of Data Science like optimization batch or regularization and so on with Google Cloud Platform.

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101 - 125 of 134 Reviews for Machine Learning in the Enterprise

By Carlos V M

Jul 2, 2018

Excellent Course, in the Art and Science of Machine Learning, I quite enjoyed the Hyperparameter tuning in the Cloud and all the advanced tips to improve the models performance, thanks Coursera and Google

By Robert L

Apr 7, 2020

Sufficient theory to understand the basis of the ML approach with practical insights to help get started with building models

By Vishal K

Jul 15, 2018

Nice course however I think it suits folks who have good exposure of ML to take complete advantage of the techniques

By Yuan L

Apr 18, 2021

Great content. The course would be better if all the labs are up to date and include all necessary setup scripts.

By Phillip

Aug 17, 2020

The course is difficult. You may need to review some sections because off the amount of information.

By Manish G

Jul 30, 2019

The course is quite good and have balance of theory and labs. It is useful course for beginners.

By Phac L T

Aug 1, 2018

It would be nice to have more complex datasets where predictions would be more meaningful.

By Oleg O

Oct 20, 2018

Very good course, but probably requires some more hand-on practice

By Joel M

Dec 12, 2018

good lessons and in depth coverage of a range of issues

By Hugo H

Apr 3, 2020

Good course, pragmatic and full of practical exercises

By Attila B

Dec 20, 2018

Really good course with a lot of practical examples.

By Pratik S

Oct 21, 2019

complete hyper parameters is given in lab

By Ruslan A

Aug 16, 2019

Many notebooks contain some typo/erros.

By Wang Y

Oct 29, 2018

best course in the specialization!!!

By Gaurav B

Feb 13, 2020

I was looking for more hands-on.

By Sarwar A

Feb 23, 2021

Good course overall

By Swaraj P

Mar 10, 2019

Nice tutorial

By Xenon

Nov 11, 2022

Excellent !

By KyeongUk J

Oct 28, 2018

great

By Matthew B

Jun 29, 2019

Labs were very confusing. Explained theories well but in practice didn't really learn much. I wouldn't recommend if you're a beginner. Google has a very interesting way on teaching.... On that note they should stick to building tech, never teaching. Didn't really learn how to build anything in ML, sort of skimmed on some API's they offer. In reality, the first course was probably the best... The rest of the specialization was just a rinse and repeat sort of thing.

By Bhargav D

Apr 26, 2020

Great course must should make labs compulsory and not provide solution it takes away the fun of thinking.

By Siddharth A

Nov 10, 2018

I felt that hand-on or explanation was not sufficient. Coverage is good.

By Alberto C

Oct 23, 2018

There are some lessons where the concepts are exposed in a too fast way

By Rahul K

May 5, 2019

Some tough concepts !!!

By Yakov F

Oct 18, 2022

All eight labs had defects/ bugs. In four (4) labs the defects prevented me from completing the labs. There was no waiting to contact Google cloud support by chat, but the best the representative was able to do was to give Coursera credit for the unfinished lab, rather than to help find and fix the defect in the lab.