Scala Tutorial | Scala Tutorial For Beginners | Scala Programming | Spark Training | Edureka

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( Apache Spark Training - https://www.edureka.co/apache-spark-scala-training )
This Scala Tutorial will help you get started with Scala Programming language. This tutorial explains why you should choose Scala language and covers the basics of Scala Programming with hands-on. Below are the topics covered in the tutorial:

1) What is Scala?
2) Why Scala?
3) Scala REPL
4) Scala Variable Types
5) Basic Scala Operations
6) Lazy Values and Control Structures in Scala
7) For Loop in Scala
8) Scala Collections - Array, ArrayBuffer, Map, Tuple

Related Blogs:
5 Reasons to Learn Spark: https://goo.gl/7nMcS0
Apache Spark vs Hadoop MapReduce: https://goo.gl/DkoUU0
Apache Spark with Hadoop, Why it matters: https://goo.gl/I2MCeP

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#ScalaTutorial #ScalaProgramming #WhatIsScala #LearnScala #Scala

How it Works?

1. This is a 4 Week Instructor led Online Course, 32 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to work on a project, based on which we will provide you a Grade and a Verifiable Certificate!

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About the Course

This Spark training will enable learners to understand how Spark executes in-memory data processing and runs much faster than Hadoop MapReduce. Learners will master Scala programming and will get trained on different APIs which Spark offers such as Spark Streaming, Spark SQL, Spark RDD, Spark MLlib and Spark GraphX. This Edureka course is an integral part of Big Data developer's learning path.

After completing the Apache Spark and Scala training, you will be able to:

1) Understand Scala and its implementation
2) Master the concepts of Traits and OOPS in Scala programming
3) Install Spark and implement Spark operations on Spark Shell
4) Understand the role of Spark RDD
5) Implement Spark applications on YARN (Hadoop)
6) Learn Spark Streaming API
7) Implement machine learning algorithms in Spark MLlib API
8) Analyze Hive and Spark SQL architecture
9) Understand Spark GraphX API and implement graph algorithms
10) Implement Broadcast variable and Accumulators for performance tuning
11) Spark Real-time Projects

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Who should go for this Course?

This course is a must for anyone who aspires to embark into the field of big data and keep abreast of the latest developments around fast and efficient processing of ever-growing data using Spark and related projects. The course is ideal for:

1. Big Data enthusiasts
2. Software Architects, Engineers and Developers
3. Data Scientists and Analytics professionals

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Why learn Apache Spark?

In this era of ever growing data, the need for analyzing it for meaningful business insights is paramount. There are different big data processing alternatives like Hadoop, Spark, Storm and many more. Spark, however is unique in providing batch as well as streaming capabilities, thus making it a preferred choice for lightening fast big data analysis platforms.
The following Edureka blogs will help you understand the significance of Spark training:

5 Reasons to Learn Spark: https://goo.gl/7nMcS0
Apache Spark with Hadoop, Why it matters: https://goo.gl/I2MCeP

Please write back to us at [email protected] or call us at +91 88808 62004 for more information.

Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka

Customer Review:

Michael Harkins, System Architect, Hortonworks says: “The courses are top rate. The best part is live instruction, with playback. But my favorite feature is viewing a previous class. Also, they are always there to answer questions, and prompt when you open an issue if you are having any trouble. Added bonus ~ you get lifetime access to the course you took!!! Edureka lets you go back later, when your boss says "I want this ASAP!" ~ This is the killer education app... I've taken two courses, and I'm taking two more.”
Category
शिक्षा - Education

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