Marketing your products and not actually teaching anything.

Multiple labs had issues loading. In particular, any labs that required me to open ungit in Datalab would hang for extended periods of time or fail altogether. I would have to reload or reopen the Datalab pages multiple times just to be able to click to the next section. These assignments are timed. The amount of time wasted was not critical to my project success, but they were very frustrating to complete.

The last lab (before the final module quiz) simply stopped working. I closed the lab and tried again. I closed Coursera and tried again. I closed my browser and tried again. I restarted the computer. After 4 attempts, this process just became too frustrating to be work fighting with - especially since my employer wants me to compare Google Cloud Platform to Microsoft Azure and choose the one that works.

After working with GCP in this course, I can say that the Google Cloud Platform has exceptional features and API support. However, I have no reason to fight to learn the Google Cloud Platform if the course fails to load key aspects of the Platform in a reliable manner.

Overall a good curated course to help understand the GCP offerings and high level architecture of how their offerings fit in the current landscape. Easy to follow along as this was fundamental course.

This course really helped me in understanding exactly 'How the Big data and Machine learning can be used in Cloud' and 'The ease to use it'. Thank you for summing all the fundamentals in this course.

This was a great course to understand at a high level how to design and create my data ecosystem and how to do it sustainably. Hopefully, next courses provide more in-depth the technical features.

It felt a bit long in some places but I appreciate the breadth of information being squeezed in a small time frame. The qwik labs and datalab notebooks were great to learn some things by trying them out. I think it would be even better if there was a task to create a simple notebook from scratch - that is something that I will need to do to continue learning.

This course provides the basics of Google Cloud Platform and makes us understand Google Products and services on Cloud. I would love to explore GCP more and will opt for the remaining GCP courses.

A good intoduction. I liked that the integration capabilities of GCP services were shown in almost every module.

Great high level overview.

I love the content Lak and the team generates and this is a great "sneak peek", but actually my experience in production is that details matter - a lot! This is why e.g. a 30 minute tutorial on deploying a deep learning model on a VM/CMLE, with pipelines in dataflow would actually take a few days to figure out.

For the courses from GCP to be really effective, a section with gotchas is needed: how does that work in real scenarios, like VPNs, security, package management, dataflow packages conflicts, limitations of language choice (e.g streaming and python)

Also, it wouldn't hurt to make the code cleaner. The repositories are a mess and the spagetti shell scripts, honestly, aren't the best idea.

Very Basic course.. But helpful to get started with GCP

There is valuable information in the course and some good exercises, but they are hidden among many information which is not so useful. In overall it is an entry class to use the technology, but many customers already know this sort of things because they tested our products or the features we comment here are similar to features of other vendors' products. Their reaction when they are presented the technology for the first time is: "Thank you. My questions and issues are quite specific and not reflected here".

disappointing, Lab instructions and Video is not at all matching, and there are numbers of errors in lab instructions

and also Video should be some more informative

I completed the "Google Cloud Platform Big Data and Machine Learning Fundamentals". I found that this course has the required material one should get to do hands on. I have seen people in my organization who says that they have given other cloud certification but they didn't do hands on. And these people who hasn't done hands on are unable to implement there knowledge in real time scenarios. For example if you have to schedule a job that loads the data (daily) from Datstore (GCS) then these guys says to open a bigquery and to do it manually. Whereas one who has done hands on will schedule a job and will call a wrapper (shell script or Python code) that will do this activity without manual intervention. The one who has not done hands on says why you are running Bigquery from Python or shell script. I am very much found of this course as this course connects you to the every possibility of connecting GCP with real world applications.

It is a great course suitable for any beginner without prior experience and knowledge about Google Cloud Platform.It is aimed for those who interested in Big Data and Machine Learning.Some of the Big Data and Machine Learning products in GCP are explored and learnt about BigQuery using SQL,Cloud Data Pub/Sub,AutoML Vision and lastly about how to build Tensorflow model.The hands-on labs given are helpful and gave step-by-step instructions to the user.The videos are designed to teach someone who is not familiar with common query language,SQL,data modeling and Machine Learning.It is totally fun and enjoyable throughout the learning journey.Can't wait to learn more and deeper about Machine Learning with Tensorflow in GCP or the specialization for Big Data and Machine Learning!Aim to become Google certified Associate Cloud Engineer next!!

Valuable overview of central big data topics and how they are supported by Google Cloud Platform. Labs are clear and well thought out, but I did have some struggles with a minor misalignment between what I saw upon "open console" - (a sign-in window), and what the lab expected me to see (a "choose account" window). When I viewed the qwiklabs overview video again, it then became clear to me that I needed to simply go ahead and sign in with the credentials provided by the lab. It might be appropriate to update the lab instructions accordingly.

A course which is must to be done by a beginner who like to come to the cloud world as a beginner. Very interesting sessions mixed up with hands-on labs will give you a lots of confidence to make experiment on GCP without any other tutorials. Almost all the products and technologies are well explained not only the concepts but the actual real world scenario where we can suggest and implement the GCP tools. This course extremely boosted my confidence to go for my next goal which is to become a Google certified Professional Data Engineer.

I'm a machine learning Student. Every time I tried to apply my theoretical knowledge to a real problem, I was unable to do so by the limits of my local machine. I tried to learn how to use GCP, but being much closer to a mathematician than a computer expert, I found it very difficult to do it alone.

This course made the general guidelines for the GCP environment very clear, showing me all the tools I could need for the different cases of use. I can not wait to continuing with the dedicated Tensorflow module.

I took this Google Cloud Platform Big Data and Machine Learning Fundamentals without any knowledge on GCP. I strongly recommend this course for professional who willing to step in to cloud analytics and data engineering . This course really helped me to push more to learn and dive in to MLE and other cloud platform tool. Coursera designed the course in such a way it will be definitely helpful for professionals who want to achieve in Cloud Platform. You can learn at anytime and anywhere.

There were some frustrating tech glitches when I started, e.g., the lab just sits there after you agree to the policies dialog when you start each lab, that I eventually learned is a known bug that is fixed by refreshing the browser. But other than those sorts of things the class was very good. Taking the class in person helped me get past the lab setup, logging in in an incognito window, copying the lab-generated credentials, etc., that I may not have been able to get past on my own.

I wish the course did a better job of identifying each GCP service with it's most important features.

Having so many products (many of which offer similar, or similar sounding jargon/names) it was quite tricky to encode it to my memory. Even with repetition learning was a bit tedious.

Other than that however, I loved the easy to listen tone of speaking and "good vibe" from Lax. He made the course overall a very positive experience. Thank you to the instructor and GCP for this.

It was really a nice experience learning directly under people working for Google. I am really happy for the knowledge regarding the fundamentals of Google Cloud Platform Big Data and Machine Learning and got to know the importance of Data Management, Infrastructure Management and List of Features provided by Google Cloud such as BigQuery, DataProc, AppEngine etc to name a few. I would be proceeding further more into the Data Engineering Specialization Course.

Aaqib Ahmad

It is a great course, highly recommended for those who wants to work in the AI / Data science field or get a better understanding of these fast developing and highly sought after skills. It is very practical and designed for non-math background, so you do not need to have ample knowledge in probability, statistics, calculus to complete the course, although basic skills including programming and linear algebra are the key contributors of smooth completion of the course.

I could have got basic knowledge of GCP and how to manipulate it. Through this course, I have understood how useful it is and where I should use it. If I took this course in student life then I didn't struggle dealing with a big data. I faced some problems when tackling the labs. However, the support team kindly solved them soon. I would like to proceed to the next course. Thank you for providing the excellent cloud and machine learning course!

Practical Examples in the lab are good practice to understand concepts and implement them live. Sometimes got lost in following the the instructions and not understanding the concept. However, could redo the exercises multiple times that helped gain confidence and a good practice at the same time. Very relevant examples covered throughout the course. Videos and enough information provided thru multiple resources - case study link and pdf docs.