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Implementing Predictive Analytics with Spark in Azure HDInsight (DAT202.3x)

learn how to implement predictive analytics solutions for big data using Apache Spark in Microsoft Azure HDInsight.

GK# 6734

Course Overview

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Are you ready for big data science? In this course, learn how to implement predictive analytics solutions for big data using Apache Spark in Microsoft Azure HDInsight. See how to work with Scala or Python to cleanse and transform data and build machine learning models with Spark ML (the machine learning library in Spark).

Note: To complete the hands-on elements in this course, you will require an Azure subscription and a Windows client computer. You can sign up for a free Azure trial subscription (a valid credit card is required for verification, but you will not be charged for Azure services). Note that the free trial is not available in all regions.

Add a course completion certificate to your cart when you enroll for your course, or purchase it at any time prior to course completion. A voucher code will be added to your MyGK dashboard that can be redeemed upon passing the exam in the course completion chapter.

Add Course Completion Certificate for $100

Schedule

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What You'll Learn

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  • Using Spark to explore data and prepare for modeling
  • Build supervised machine learning models
  • Evaluate and optimize models
  • Build recommenders and unsupervised machine learning models

Outline

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On-Demand Outline

Introduction to Data Science with Spark
Get started with Spark clusters in Azure HDInsight, and use Spark to run Python or Scala code to work with data.

Getting Started with Machine Learning
Learn how to build classification and regression models using the Spark ML library.

Evaluating Machine Learning Models
Learn how to evaluate supervised learning models, and how to optimize model parameters.

Recommenders and Unsupervised Models
Learn how to build recommenders and clustering models using Spark ML.

Prerequisites

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  • Familiarity with Azure HDInsight.
  • Familiarity with databases and SQL.
  • Some programming experience.
  • A willingness to learn actively in a self-paced manner.

Who Should Attend

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Do you introduce your self as a data professional at conferences? If you do, you should take this course.

Course Delivery

This course is available in the following formats:

On-Demand

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