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Google Cloud Platform Big Data And Machine Learning Fundamentals (CPB100)

Learn about the big data and machine learning capabilities of the Google Cloud Platform.

GK# 8325

Course Overview


In this course, you will learn about the big data and machine learning capabilities of the Google Cloud Platform. You will be provided with a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.

For a more general overview of Google Cloud Platform, see Google Cloud Platform Fundamentals (CP100A).

What You'll Learn

  • Purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform
  • Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform
  • Employ BigQuery and Cloud Datalab to carry out interactive data analysis
  • Choose between Cloud SQL, BigTable, and Datastore
  • Train and use a neural network using TensorFlow
  • Choose between different data processing products on the Google Cloud Platform


Viewing outline for:

Virtual Classroom Live Outline

1. Introduction

  • What is the Google Cloud Platform?
  • GCP Big Data Products
  • Usage scenarios
  • Sign up for Google Cloud Platform

2. Foundation of GCP (Compute and Storage)  

  • CPUs on demand (Compute Engine)
  • A global filesystem (Cloud Storage) 
  • CloudShell 

3. Data Analytics on the Cloud

  • Stepping stones to the cloud
  • CloudSQL: Your SQL database on the cloud
  • Dataproc

4. Scaling Data Analysis

  • Fast random access
  • Datalab 
  • BigQuery
  • Machine Learning with TensorFlow 
  • Fully built models for common needs 
  • Genomics API

5. Data Processing Architectures  

  • Asynchronous processing with TaskQueues 
  • Message-oriented architectures with Pub/Sub
  • Creating pipelines with Dataflow 

6. Summary  

  • Why GCP? 
  • Where to go from here 
  • Resources


At least one year of experience with one or more of the following:
  • A common query language such as SQL
  • Extract, transform, load activities
  • Data modeling
  • Machine learning and/or statistics
  • Programming in Python


Who Should Attend

  • Data analysts
  • Data scientists
  • Business analysts
Course Delivery

This course is available in the following formats:

Virtual Classroom Live

Experience expert-led online training from the convenience of your home, office or anywhere with an internet connection.

Duration: 1 day

Request this course in a different delivery format.