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Course Duration

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8 Weeks

100%

Description:

The Spark with Scala Essentials course provides participants with a comprehensive understanding of Apache Spark and Scala, two widely-used technologies in big data processing and analytics. Participants will learn about key concepts such as distributed computing, data processing, and data analysis using Spark with Scala. Through a combination of theoretical learning and hands-on exercises using Spark shell and Scala programming language, participants will gain proficiency in developing and deploying big data applications with Spark.

Key Topics :

• Introduction to Apache Spark and Scala

• Spark Architecture and Components (Spark Core, Spark SQL, Spark Streaming, Spark MLlib)

• Setting up Spark Development Environment

• Working with RDDs (Resilient Distributed Datasets)

• Spark SQL for Data Analysis and Data Manipulation

• Spark Streaming for Real-time Data Processing

• Machine Learning with Spark MLlib

• Graph Processing with GraphX

• Performance Optimization Techniques in Spark

• Spark Deployment Modes (Standalone, YARN, Mesos)

• Integrating Spark with Hadoop and other Big Data Technologies

• Best Practices for Spark Development

Prerequisites:Basic understanding of programming concepts and familiarity with any programming language (preferably Java or Python) would be beneficial. Some knowledge of big data concepts would also be helpful but not mandatory.

Upon completion of the course, participants will have a solid understanding of Apache Spark and Scala and be able to develop and deploy big data applications for data processing, analytics, and machine learning. They will be equipped with the skills necessary to work effectively with Spark and Scala in various big data projects and initiatives.

• Data engineers, data analysts, and software developers interested in learning big data processing with Spark and Scala.

• IT professionals seeking to enhance their skills in big data technologies and analytics.

• Students and enthusiasts looking to build a career in big data and data engineering.

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