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Without practical experience in GCP or AWS in background and personal knowledge about technologies like AWS Lambda's, Apache Kafka or Apache Cassandra etc. it would be hard to understand half of this course, especially about different data storages. Too much water. Sometimes questions or answers to them are generally incomprehensible. Like "orchestration" as an answer to a question about Google Cloud Dataflow use cases. Orchestration, really? Of what? Compute instances? Linux servers? Is it the same as Ansible or Salt? Absolutely confusing and not clear why and when I need Dataflow and other services also. Transactions are not the only one thing that people should understand. We need more practical use cases. And there are some other questions with the same problems. 90% of people who really passed the GCP certification recommended Linux Academy but not Coursera for the preparation. Now I have to try it to compare personally.

Overall, you made a great work. The platform is good and the course also is good. I found a lot of new information about GCP and now I need to dive into them deeply.

Thank you.

I am really happy with the way labs were set up. It was easy to get into and not much of a hassle for me to set everything up - I could just focus on learning. I love that.

Other aspect of those labs was... There just wasn't that much things to do in them. I would really love if there were some projects that we could do, on our own, without exact instructions, to achieve something. I think that it would definitely cement the knowledge into us.

The videos were good. Speakers were engaging and they spoke clean English. Clean English is very important for me in courses, because I don't want to listen to the same sentence a few times, in order for me to understand it. Every teacher should strive to minimize their use of accent.

The tests often time asked questions that just weren't given enough attention. It would be really good if you added additional, reading, materials to this course - to bolster the knowledge acquisition and retention.

Most things worked out nicely, but there were issues with two of the labs:

"Developing, Deploying, and Monitoring in the Cloud": The monitoring part did not work for me, as using the monitoring service now requires installing some agent on the VM. I followed the instructions, but starting the agent failed due to missing certificates. I found no straight-forward way of making the agent work on the VM so I could not test out the monitoring services.

"Getting started with BigQuery": After loading the logdata table, viewing it in the console fails with error "Unknown error response from the server". Stackoverflow says this is a known issue due to the table being too big. Making queries in the console or shell works fine, but you cannot directly see anything about the logdata table / its rows in the console due to this error.

As a student in computer hardware and electronics system, I took this course to gain a solid foundation in cloud computing. “Google Cloud Fundamentals: Core Infrastructure” provided an excellent introduction to the core services of Google Cloud, including Compute Engine, App Engine, Cloud Storage, and networking tools. The video explanations and real-world use cases were clear and beginner-friendly. I particularly appreciated the diagrams and step-by-step examples, which helped me understand how cloud architecture works. This course has improved my understanding of modern IT infrastructure and made me more confident in pursuing cloud-related roles. I highly recommend it to anyone starting their cloud journey, especially aspiring IT professionals and students.