• Length:
    6 Weeks
  • Effort:
    3–4 hours per week
  • Price:

    FREE
    Add a Verified Certificate for $99 USD

  • Institution
  • Subject:
  • Level:
    Intermediate
  • Language:
    English
  • Video Transcript:
    English

Prerequisites

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

About this course

This course is part of the Microsoft Professional Program Certificate in Data Science and part of the Microsoft Professional Program Certificate in Big Data.

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.

edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.

What you'll learn

  • 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
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.

Meet your instructors

Graeme Malcolm
Senior Content Developer
Microsoft Learning Experiences

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