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CPB100: Google Cloud Platform Big Data & Machine Learning Fundamentals Training Course

Nobleprog Limited

Course

Online

£ 950 VAT inc.

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Description

  • Type

    Course

  • Methodology

    Online

This 8 hour instructor-led class introduces participants to the Big Data & Machine Learning capabilities of Google Cloud Platform. It provides 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 CP100A)
This class is intended for:
Data analysts
Data scientists
Business analysts
It is also suitable for IT decision makers evaluating Google Cloud Platform for use by data scientists.
This class is for people who do the following with big data:
Extracting, Loading, Transforming, cleaning, and validating data for use in analytics
Designing pipelines and architectures for data processing
Creating and maintaining machine learning and statistical models
Querying datasets, visualizing query results and creating reports
At the end of this one­day course, participants will be able to:
Identify the 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

About this course

Before attending this course, participants should have roughly one (1) 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

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Subjects

  • Access
  • MySQL
  • Database
  • SQL
  • Database training
  • Network
  • Data analysis
  • Cleaning
  • SQL Database
  • Network Training

Course programme

Module 1: Introduction

In this module you will be introduced to Google Cloud Platform and the data handling aspects of the platform.

  • What is the Google Cloud Platform?
  • GCP Big Data Products
  • Usage scenarios
  • Lab: Sign up for Google Cloud Platform
Module 2: Foundation of GCP (Compute and Storage)

In this module, we introduce the foundations of the Google Cloud Platform: compute and storage and introduce how they work to provide data ingest, storage, and federated analysis.

  • CPUs on demand (Compute Engine)
    • GCE: the value proposition
    • Lab: Start GCE instance, ssh access
  • A global filesystem (Cloud Storage)
    • Google Storage, data centers, zones, regions
    • GS and its role in data processing
    • Lab: Set up a Ingest-Transform-Publish data processing pipeline
  • CloudShell
Module 3: Data Analytics on the Cloud

In this module we introduce the common Big Data use cases that Google will manage for you. These are the things that are widely done in industry today and for which we provide easy migration to the cloud.

  • Stepping stones to the cloud
    • Where GCP started
    • Towards no-ops
  • CloudSQL: your SQL database on the cloud
    • A no-ops database
    • Lab: importing data into CloudSQL and running queries on rentals data
  • Dataproc
    • Managed Hadoop + Pig + Spark on the cloud
    • Lab: Machine Learning with SparkML
Module 4: Scaling data analysis

This module is about the more transformational technologies in Google Cloud platform that may not have immediate parallels to technologies that attendees are using (“what's next”).

  • Fast random access
    • Datastore: Key-Entity
    • BigTable: wide-column
  • Datalab
    • Why Datalab? (interactive, iterative)
    • Demo: Sample notebook in datalab
  • BigQuery
    • Interactive queries on petabytes
    • Lab: Build machine learning dataset
  • Machine Learning with TensorFlow
    • TensorFlow
    • Lab: Train and use neural network
  • Fully built models for common needs
    • Vision API
    • Translate API
    • Lab: Translate
  • Genomics API (optional)
    • What is linkage disequilibrium?
    • Finding LD using Dataflow and BigQuery
Module 5: Data processing architectures

In this module we will introduce you to data processing architectures in Google Cloud Platform.

  • Asynchronous processing with TaskQueues
  • Message-oriented architectures with Pub/Sub
  • Creating pipelines with Dataflow
Module 6: Summary
  • Why GCP?
  • Where to go from here
  • Resources

Additional information

8 hours (usually 1 day including breaks)

See related categories

CPB100: Google Cloud Platform Big Data & Machine Learning Fundamentals Training Course

£ 950 VAT inc.

The best Other Database courses

See all

See all