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This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, you will get an overview of the Google Cloud platform and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform.



Highlights:
  • Purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform
  • Use Cloud SQL 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
  • Train and use a neural network using TensorFlow
  • Employ ML APIs
  • Choose between different data processing products on the Google Cloud Platform

Prerequisites:
  • Basic proficiency with common query language such as SQL
  • Experience with data modeling, extract, transform, load activities
  • Developing applications using a common programming language such Python
  • Familiarity with Machine Learning and/or statistics


Audience:
  • Data analysts getting started with Google Cloud Platform
  • Data scientists getting started with Google Cloud Platform
  • Business analysts getting started with Google Cloud Platform
  • Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports
  • Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists

1. Introducing Google Cloud Platform

  • Google Platform Fundamentals Overview
  • Google Cloud Platform Data Products and Technology
  • Usage scenarios

2. Compute and Storage Fundamentals

  • 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
  • Lab: Importing data into CloudSQL and running queries
  • Spark on Dataproc

4. Scaling Data Analysis

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

5. Data Processing Architectures

  • Message-oriented architectures with Pub/Sub
  • Creating pipelines with Dataflow
  • Reference architecture for real-time and batch data processing

6. Summary

  • Why GCP?
  • Where to go from here
  • Additional Resources
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    • V Virtual Live
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Virtual Live2/9/2018 11:30:00 AM<span class="course-type type-v" style="cursor:default;word-wrap:normal;display:inline-block;" onmouseover="showHoverInfo(this, 'ProductTypeDescription' ,'VILT')" onmouseout="clearHoverInfo()">V</span>1 day995.002461808
Virtual Live3/23/2018 8:30:00 AM<span class="course-type type-v" style="cursor:default;word-wrap:normal;display:inline-block;" onmouseover="showHoverInfo(this, 'ProductTypeDescription' ,'VILT')" onmouseout="clearHoverInfo()">V</span>1 day995.002461803
Virtual Live5/4/2018 8:30:00 AM<span class="course-type type-v" style="cursor:default;word-wrap:normal;display:inline-block;" onmouseover="showHoverInfo(this, 'ProductTypeDescription' ,'VILT')" onmouseout="clearHoverInfo()">V</span>1 day995.002461807
Virtual Live6/29/2018 8:30:00 AM<span class="course-type type-v" style="cursor:default;word-wrap:normal;display:inline-block;" onmouseover="showHoverInfo(this, 'ProductTypeDescription' ,'VILT')" onmouseout="clearHoverInfo()">V</span>1 day995.002461811
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