Apache Spark 3 & Big Data Essentials w/ Scala | Rock the JVM

Online Course

Udemy
Apache Spark 3 & Big Data Essentials w/ Scala | Rock the JVM

What is the course about?

Apache Spark 3 & Big Data Essentials w/ Scala | Rock the JVM
The course Apache Spark 3 & Big Data Essentials w/ Scala | Rock the JVM is an online class provided by Udemy. It may be possible to receive a verified certification or use the course to prepare for a degree.

Updated for 3.0: Learn practical Big Data with Scala & Apache Spark, with Spark DataFrames, Datasets, RDDs and Spark SQL

Course description
  • Apache Spark 3 & Big Data Essentials w/ Scala | Rock the JVM
  • apply Spark big data principles
  • practice Spark DataFrames operations with 100+ examples and exercises
  • practice type-safe data processing with Spark Datasets
  • work with low-level Spark APIs with RDDs
  • use Spark SQL for data processing
  • Scala fundamentals, at the level of the Rock the JVM beginners course
  • Scala advanced – implicits
  • 7.5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
  • Daniel Ciocîrlan

Prerequisites & Facts

Apache Spark 3 & Big Data Essentials w/ Scala | Rock the JVM

Course Topic

Personal Success, Teacher Training, Teaching & Academics

University, College, Institution

Udemy

Course Skill Level

Course Language

English

Place of class

Online, self-paced (see curriculum for more information)

Degree

Certificate

Degree & Cost

Apache Spark 3 & Big Data Essentials w/ Scala | Rock the JVM

To obtain a verified certificate from Udemy you have to finish this course or the latest version of it, if there is a new edition. The class may be free of charge, but there could be some cost to receive a verified certificate or to access the learning materials. The specifics of the course may have been changed, please consult the provider to get the latest quotes and news.
Udemy
Apache Spark 3 & Big Data Essentials w/ Scala | Rock the JVM
provided by Udemy

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School: Udemy
Topic: Apache Spark, Development, Software Engineering