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Spark Overview for Scala Analytics

The “Spark Overview for Scala Analytics” course will cover the history of Spark and how it came to be, how to build applications with Spark, establish an understanding of RDDs and DataFrames, and other advanced Spark topics. Apache Spark™ is a fast and general engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning and graph processing. Having finished this class, a student would be prepared to leverage the core RDD and DataFrame APIs to perform analytics on datasets. This course is meant to be an overview of Spark and its associated ecosystem. For deeper understanding of Spark, we recommend that students take the Spark Fundamentals courses I and II.

Course Number

SC0103EN
Classes Start

Anytime, Self-paced
Estimated Effort

08:00
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ABOUT THIS COURSE

Learn the history of Apache Spark™, how it came to be, how to build applications with Spark, how establish an understanding of RDDs and DataFrames, and other advanced Spark topics.

Be prepared to leverage the core RDD and DataFrame APIs to perform analytics on datasets with Scala.
Get an overview of Spark and its associated ecosystem.
Gain enough skills to leverage the Map-Reduce framework with the Scala language.

COURSE SYLLABUS

Module 1 - What is Spark?

Module 2 - Introduction to RDDs

Module 3 - Introduction to DataFrames

Module 4 - Advanced Spark Topics

Module 5 - Introduction to Spark MLlib

GENERAL INFORMATION

This course is free.
It is self-paced.
It can be taken at any time.
It can be audited as many times as you wish.

RECOMMENDED SKILLS PRIOR TO TAKING THIS COURSE

Experience with Java (preferred), Python, or another object-oriented language.
No previous Spark knowledge is required.
No previous experience with Data Science concepts is required. These concepts will be explained as needed.

REQUIREMENTS

Taken the Scala 101 and Spark Fundamentals I course.

COURSE STAFF

Jamie Allen - Spark Overview for Scala Analytics instructor

Jamie Allen

Jamie has worked in consulting since 1994, with top firms including Price Waterhouse and Chariot Solutions. He has a long track record of working closely with clients to build high quality, mission critical systems that scale to meet the needs of their businesses, and has worked in myriad industries including automotive, retail, pharmaceuticals, telecommunications and more. Jamie has been coding in Scala and actor based systems since 2009, and is the author of "Effective Akka" book from O'Reilly.