This is more like an advertisement for google cloud more than teaching it. There should be a provision to explore the Google cloud to learn more rather than putting so many restriction at least for educational purpose. Removing restriction will let people understand and experiment more, which in turn attracts talents to use GCP while they work for enterprises.

Overall, the course is good as it gives a good introduction to all GCP services related to Big Data and Machine Learning.

However, what I was eager to experience in taking the course is more hands-on practice of the tools within GCP. Also, there could be more explanations in the labs, especially the codes (not just them being copied and pasted).

1.The accent of one instructor is hard to tell, not friendly to non-native English speaker.

2.Some pauses and interruptions during the lectures. I'm not sure if the instructor(s) is well prepared but at lease they should have had script for what is going to talk.

3.The review section of each lab is not necessary. The instructions is clear enough.

Overall a good foundation course. Unfortunately, the shared lecture slides are from the older version of this course and utterly do not match the current video lectures; moderators do not respond to the request to upload the current slide decks. The instructions for the last lab (Vertex AI) are buggy or incomplete in several places.

it was good to plug and play data on the labs and see results. I am quite impressed by the scope of ML in our world. listening about different applications of all GCP software is very intriguing. I am from non CS background, and i find programming challenging. I really do look forward to change my field and move in data analytics

The course was not as hands-on as I would've liked it to be. The exercises are not problems to be solved. They are recipes/instructions to be followed. The instructors spend a lot of time pitching GCP. On the bridge side, GCP is an impressive tool. I feel now comfortable using some of its key features.

I liked the details in the explanations and the huge knowledge the trainer has.The labs were a little disappointing at times. Lots of configuration and then you didn't really do much with it. Would have been great to have some more practice included using the data once the infra is up and running.

scratch very basic of gcp. overall great course. but i got difficulties on following when i need to execute datalab python which the notebook is available on github. i thought i followed every step told by the instructor but I couldn't find how I could git clone to my datalab like the video did.

I simply satisfied with this lecture, but i had just a little point that i've disapointed.

First, There isn't any subtitle for Korean.

Second, It's difficulty has grown up too fastly to compare start and the end.

Anyway, Thanks for such a good lecture. Thx :D

The Labs and Course Assignments can be better. Fundamentals of GCP was a good course with tough assignments and a lot more learning. In this one the videos are too long and sometimes repetitive like Lab and Leab Review.

last lab was a bit disappointing. suspect something to do with a GCP outage. But rest is a very good up-to-speed on GCP and the various tech available there. Looking forward to using for some of my next projects.

There are some steps missing in the labs, while the video on DataFlow didn't provide an introduction into why MapReduce is applicable to certain problems. Besides that, the tutor is speaking too fast.

Applying the supervised and unsupervised methods through Google, with more examples would be a better learning experience. But this course gave perfect confidence to tackle anything that comes up.

I got familiar with a lot of options, and had hands on experience with Qwiklabs. But it would be more interesting if the we actually had to do something ourselves instead of following instructions.

Las explicaciones de cada paso a veces son ambiguas y obliga en gran medida a hacer nuevamente los laboratorios.

El contenido del curso es poco para todo lo que puede hacerse como Data Engineer.

This felt like half marketing, half using GCP for machine learning. Prebuilt solutions are useful for many cases but I only really needed info on the storage and data processing to get started.

Awesome instructor. An advanced course on this topic (4-5 weeks ) would have been better. To join this course is basically paying for someone to comment on the tutorials available for free.

The course is really more focused on GCP and the products it has rather than you doing anything significant with the product. The course is extremely basic and I wish I didn't pay for it.

Its a very Introductory course, you will get a high level overview. Most of the hands on are some what pre- configured with steps, which prevents learning end to end learning of the flow

Some of the labs are repeated, why do we have to repeat the steps all over again and again, the course could have been shorter, and the last module was really fast and not explained well.

Instructor's tone was monotonous. Course would have been interesting with more real-life examples. Module 5 rushed through pub/sub and dataflow, could have added a small lab for the same.

This course could almost be retitled, Learning the Google Cloud Marketing Material. I won't say it was without value, but it is a really high overview of the Google Cloud offerings.

Way too much advertising - and too much copy and paste in the labs. Tests/quizzes are getting sparse in the last modules - but still it is a good intro in the field for beginners.

The explanations were clear, but I think it might have been nice to go a bit more depth. Even perhaps building something a bit more robust, something like a portfolio piece.

It's very fundamental, more excersices from scratch will be less easier AND yield self awareness of the services from GCP to be applied depending on the problem presented.