Google Cloud Big Data and Machine Learning Fundamentals


Course Number: GCP-100

Duration: 1 day (6.5 hours)

Format: Live, hands-on

Google Cloud Training Overview

This Google Cloud Big Data and Machine Learning Fundamentals training introduces Google Cloud's data processing and machine learning capabilities.

Location and Pricing

This course is taught as a private, live online class for teams of 3 or more. All our courses are hands-on, instructor-led, and tailored to fit your group’s goals and needs. Most Accelebrate classes can be flexibly scheduled for your group, including delivery in half-day segments across a week or set of weeks. To receive a customized proposal and price quote for online corporate training, please contact us.

Objectives

  • Identify the purpose and value of the key Big Data and Machine Learning products on Google Cloud
  • Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud
  • 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 Google Cloud

Prerequisites

  • Basic proficiency with a common query language such as SQL
  • Experience with data modeling and extract, transform, and load activities
  • Application development experience using a common programming language such as Python
  • Familiarity with machine learning and/or statistics

Outline

Expand All | Collapse All

Introducing Google Cloud Platform
  • Google Platform fundamentals overview
  • Google Cloud Platform big data products
Compute and Storage Fundamentals
  • CPUs on demand (Compute Engine)
  • A global filesystem (Cloud Storage)
  • CloudShell
Data Analytics on the Cloud
  • Stepping-stones to the cloud
  • Cloud SQL: your SQL database on the cloud
  • Spark on Dataproc
Scaling Data Analysis
  • Fast random access
  • Datalab
  • BigQuery
Machine Learning
  • Machine Learning with TensorFlow
  • Pre-built models for common needs
Data Processing Architectures
  • Message-oriented architectures with Pub/Sub
  • Creating pipelines with Dataflow
  • Reference architecture for real-time and batch data processing
Conclusion
  • Why GCP?
  • Where to go from here
  • Additional Resources

Training Materials:

All GCP training students receive comprehensive courseware.

Software Requirements:

Students must have the Google Chrome web browser and Internet access.



Learn faster

Our live, instructor-led lectures are far more effective than pre-recorded classes

Satisfaction guarantee

If your team is not 100% satisfied with your training, we do what's necessary to make it right

Learn online from anywhere

Whether you are at home or in the office, we make learning interactive and engaging

Multiple Payment Options

We accept check, ACH/EFT, major credit cards, and most purchase orders



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