This is another awesome course. I'd been learning about Smart Analytics, creating simple models with BigQueryML and training datasets with AutoML. You must use your model and data, but I just have my data.

I couldn't complete the Kubeflow lab due to issues that I encountered setting it up. Overall, the course has given me a good understanding of Machine Learning model creation options available on GCP

In general - very hot industry knowledge, however it feels that this content needs some time to get flawless and robust as the other ones from this specialization.

The course is good but there is a lot of repeating concepts from the first course of the data engineering specialization and some labs are a bit buggy

Course gives basic overview on ML concepts and how we can do using GCP. Good enough for Data Engineer to understand

Great hands one excercises to confirm few coding lines to do real world predictions

Few important concepts like kubeflow should have been covered in a bit more detail.

I learned how to use Auto ML and its benefits. The tool looks like a black box.

A general introduction for enabling data engineer start working on GCP

Great learning. Thank you for the wonderful videos and assessment labs

Solid module. The Kubeflow Qwiklabs would benefit from improvements.

nice introduction in the world of AI in gcp. Relatively short though

Running AI models on Kubeflow - this lab is long but interesting

Great course, except many of the labs were on cloud shell only

A lot of material, requires careful review and study.

It was good course to see the overview of ML on GCP.

Pode ser melhor, ter labs mais didaticos

This course help me understand AI, ML.

would be nice if it could dive deeper.

I missed Dataproc approach

good for the introduction

quality springboard

Very introductory.

Very informative

Good course