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

1,430 ratings

About the Course

This course encompasses a real-world practical approach to the ML Workflow: a case study approach that presents an ML team faced with several ML business requirements and use cases. This team must understand the tools required for data management and governance and consider the best approach for data preprocessing: from providing an overview of Dataflow and Dataprep to using BigQuery for preprocessing tasks. The team is presented with three options to build machine learning models for two specific use cases. This course explains why the team would use AutoML, BigQuery ML, or custom training to achieve their objectives. A deeper dive into custom training is presented in this course. We describe custom training requirements from training code structure, storage, and loading large datasets to exporting a trained model. You will build a custom training machine learning model, which allows you to build a container image with little knowledge of Docker. The case study team examines hyperparameter tuning using Vertex Vizier and how it can be used to improve model performance. To understand more about model improvement, we dive into a bit of theory: we discuss regularization, dealing with sparsity, and many other essential concepts and principles. We end with an overview of prediction and model monitoring and how Vertex AI can be used to manage ML models....

Top reviews


Dec 30, 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.


Jun 6, 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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76 - 100 of 124 Reviews for Machine Learning in the Enterprise

By Naman M

Aug 19, 2019


By Kamlesh C

Jun 13, 2020


By Somaiya J G

Nov 14, 2018


By Gustavo M

Aug 17, 2018


By Phạm V T

Apr 17, 2020


By Manish K

Aug 28, 2019



Nov 24, 2020


By Dr. P S J

Jul 25, 2020


By Balasubramanian T K

Apr 13, 2020



Dec 3, 2019


By Mirza s N

Sep 18, 2019


By Fathima j

May 11, 2019


By Bielushkin M

Nov 23, 2018


By Atichat P

Jun 4, 2018


By Fuat A

Mar 20, 2020

Google provided with me an opportunity to take the specialization for free. Many thanks.

Just a comment: Labs were great. But, it takes long when i needed to start a lab, i.e. Opening a Google account every time and starting a vm. So, it would be great if i could use the same vm for more than one lab assignment.

By Nazli E

Jan 18, 2023

some of the qwiklabs are frustrating because even after following directions. and some directions are not clear or missing a step. it makes certain assumptions or does not include a step so that the person doing the lab will know what to do. otherwise rest of the course is okay.

By Randall B

Aug 25, 2022

Quite a few of the quiz questions and answer options are worded awkwardly, so that they are not useful as a review, these really need to be improved. A code error in the "Introduction to Vertex AI pipelines" needs to be fixed for it to work again, currently the pipeline fails.

By Carlos V M

Jul 1, 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 17, 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 16, 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