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Friday, March 8, 2019

Google Cloud Basics Cheatsheet

Project: use a project  to organize a collection of your Google Cloud resources and services.  For example if you have a WordPress site it should one be project. If you use BigQuery to view its data, put the BigQuery instance under the same project. Project IDs are unique. If your resources or services need to have an unique name, you can just prepend its name with your project ID which is guaranteed unique.

Products
Google Colab: great for machine learning deep learning, GPU availability, without need to worry about dependencies.

Training
- Free live, instructor led Google Cloud Platform (GCP) onboarding. Google Cloud onboard free classes on Google Cloud Platform Fundamentals: Core Infrastructure. Google Cloud Platform Fundamentals: Big Data and Machine Learning. Kubernetes.

While these free classes have limited availabilities, the online paid versions are always available on Coursera.

Google Cloud Engineer certification
All Google Cloud Courses on Coursera https://www.coursera.org/googlecloud
Machine Learning with TensorFlow on Google Cloud Platform Specialization https://www.coursera.org/specializations/machine-learning-tensorflow-gcp
Google Cloud NEXT free coursera course credit https://www.coursera.org/promo/NEXTExtended
https://www.coursera.org/googlecloud
Data Engineering on Google Cloud Platform Specialization
https://www.coursera.org/specializations/gcp-data-machine-learning
Preparing for the Google Cloud Professional Data Engineer Exam
https://www.coursera.org/learn/preparing-cloud-professional-data-engineer-exam

Associate Cloud Engineer
https://cloud.google.com/certification/guides/cloud-engineer/

Machine Learning with Spark on Google Cloud Dataproc in data lab

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