Google Cloud Big Data and Machine Learning


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level


Overview/Description
Google Cloud Storage is unified object storage for developers and enterprises, from live data serving to data analytics/ML to data archival. In this course, you'll learn about the fundamentals of the Google Cloud Datastore and other storage options along with the basics of Big Data and Machine Learning with Google Cloud Platform.

Target Audience
IT professionals including managers, engineers, and developers evaluating or implementing application environments on Google Cloud Platform

Prerequisites
None

Expected Duration (hours)
1.2

Lesson Objectives

Google Cloud Big Data and Machine Learning

  • start the course
  • identify the purpose and characteristics of Google Cloud Datastore
  • define various datastore terms including kind, entity, property, keys, and entity groups
  • define development libraries, queries, and indexes
  • deploy an App Engine application backed by Google Datastore
  • identify the features of Google Cloud Storage
  • identify the features of Google Cloud SQL
  • identify the features of Google Cloud Bigtable
  • create a Google Cloud Storage bucket and use it to store images
  • view objects using the Cloud Storage Browser
  • identify considerations for deployment of Cloud Storage required Applications
  • identify characteristics and purpose of Google Cloud Big Data and Machine Learning platforms
  • recognize loading a CSV File Into a BigQuery Table
  • recognize querying data using the CLI
  • recognize querying data using BigQuery Web UI
  • recognize querying data using BigQuery Shell
  • perform interactive queries using BigQuery
  • review the basic features of datastore, storage options, big data, and machine learning

    • Course Number:
    cl_gcpf_a03_it_enus

    Expertise Level
    Intermediate