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Offered By: LightBend

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.

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Course

Scala

1.43k+ Enrolled
4.7
(29 Reviews)

At a Glance

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.

About This Course

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.
There are 5 modules to this course.
1. What is Spark
2. Introduction to RDDs
3. Introduction to DataFrames
4. Advanced Spark Topics
5. Introduction to Spark MLlib

Requirements

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

Course Staff

Jamie Allen

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.

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Estimated Effort

8 Hours

Level

Beginner

Skills You Will Learn

Big Data, Scala

Language

English

Course Code

SC0103EN

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