#1035 overall
Data Engineering on Google Cloud
Coursera
1 recommender · 1 thread · recommended in 1 year, 2018 · score 0.7
A Coursera course from Google Cloud on building data pipelines and data engineering workflows using Google Cloud services. It is one of the Google Cloud courses on Coursera that commenters point to for learning the platform.
One commenter recommends it alongside the Google Cloud architect course as a way to learn GCP, noting the platform's generous free tier and good developer tools.
Databases & Data Engineeringintermediatevideo lectures#google cloud#data engineering#data pipelines#coursera#gcp
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I'll say this in GCP's favor: it has an extremely generous free tier and a $300 credit for signing up, a ton of fantastic tutorials and walkthroughs at https://codelabs.developers.google.com, and they seem to be at the forefront of most major R&D advances in cloud computing over the last couple of decades, so you'll probably see new things there first (managed kubernetes, Spanner, and a wealth of fancy machine learning shit just to start).
I also recommend going through the "Google cloud architect" and "data engineering on Google cloud" courses on Coursera: https://www.coursera.org/googlecloud.
The docs have gotten much better over the years, but you have to put in the time to really dive into them. They are essential reading, so put in the time.
Also the developer tools, (web dashboards, CLI tools, APIs, code libraries, etc.) seem to be light years better than what I've experienced with AWS and Azure.
Disclaimer: I used to work Platinum support for Google cloud. Now I'm an SRE at a company that uses AWS, and I play around with Azure here and there to see what's what
Whatever you decide to do, I recommend coming up with one idea for an application that can start simple but grow into something complex, start from the bottom with a simple deployment, and add pieces as you learn them so you can understand how everything fits together in the grand scheme of things. I picked election/voting software, which is good because it starts at just simple vote counting over an API, then grew to teach me auto scaling, data pipelines, machine learning analysis, etc.