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(This article was first published on <strong><a href="http://www.datacamp.com/community/blog/new-course-introduction-to-spark-in-r-using-sparklyr"> DataCamp Blog</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Hello R users! We have a big announcement this week as well, DataCamp just released our first Spark in R course: Introduction to Spark in R using sparklyr! This course is taught by <a rel="nofollow" href="https://www.datacamp.com/instructors/richie?tap_a=5644-dce66f&tap_s=10907-287229" target="_blank">Richie Cotton</a>.</p>
<p>R is mostly optimized to help you write data analysis code quickly and readably. Apache Spark is designed to analyze huge datasets quickly. The <code>sparklyr</code> package lets you write <code>dplyr</code> R code that runs on a Spark cluster, giving you the best of both worlds. This course teaches you how to manipulate Spark DataFrames using both the <code>dplyr</code> interface and the native interface to Spark, as well as trying machine learning techniques. Throughout the course, you’ll explore the Million Song Dataset.</p>

<p><center><strong><a rel="nofollow" href="https://campus.datacamp.com/courses/introduction-to-spark-in-r-using-sparklyr/light-my-fire-starting-to-use-spark-with-dplyr-syntax?tap_a=5644-dce66f&tap_s=10907-287229" target="_blank">Take me to the first chapter! </a></strong></center></p>
<p>Introduction to Spark in R using sparklyr features interactive exercises that combine high-quality video, in-browser coding, and gamification for an engaging learning experience that will teach you how to work with Spark in R!</p>
<p><a rel="nofollow" href="https://www.datacamp.com/courses/introduction-to-spark-in-r-using-sparklyr?tap_a=5644-dce66f&tap_s=10907-287229" target="_blank"><img alt="" src="https://i0.wp.com/community.datacamp.com.s3.amazonaws.com/community/production/ckeditor_assets/pictures/644/content_1200x628_new_course_5.png?w=456" data-recalc-dims="1"></a></p>
<p><strong>What you’ll learn:</strong></p>
<h4><strong>Chapter 1 – Light My Fire: Starting To Use Spark With dplyr Syntax</strong></h4>
<p>Starting off you will learn how Spark and R complement each other, how to get data to and from Spark, and how to manipulate Spark data frames using dplyr syntax.</p>
<h4><strong>Chapter 2 – Tools of the Trade: Advanced dplyr Usage</strong></h4>
<p>In the second chapter, you will learn more about using the <code>dplyr</code> interface to Spark, including advanced field selection, calculating groupwise statistics, and joining data frames.</p>
<h4><strong>Chapter 3 – Going Native: Use The Native Interface to Manipulate Spark DataFrames</strong></h4>
<p>In chapter 3, you’ll learn about Spark’s machine learning data transformation features and functionality for manipulating native DataFrames.</p>

<p><strong>Chapter 4 – Case Study: Learning to be a Machine: Running Machine Learning Models on Spark</strong></p>
<p>The final chapter is a case study in which you learn to use <code>sparklyr</code>‘s machine learning routines, by predicting the year in which a song was released.</p>

<p><center><a rel="nofollow" href="https://www.datacamp.com/courses/introduction-to-spark-in-r-using-sparklyr?tap_a=5644-dce66f&tap_s=10907-287229" target="_blank"><strong>Start Learning Spark in R Today!</strong></a></center></p>
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