Overview of Course

This Apache Spark training course is designed to provide learners with an in-depth understanding of Apache Spark, a big data processing tool. The course covers the fundamentals of distributed computing, Spark architecture, and the key concepts of Spark RDDs (Resilient Distributed Datasets) and Spark SQL.

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Course Highlights

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Industry-relevant curriculum with practical examples

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Expert-led training with customized learning paths

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Flexibility to learn at your own pace with self-paced modules

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Skills You’ll Learn


Understanding of distributed computing and Spark architecture


Proficiency in Spark programming using RDDs and Spark SQL


Expertise in building and deploying Spark applications


Knowledge of Spark streaming, machine learning, and graph processing

Training Options

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1-on-1 Training

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  • Option Item Access to live online classes
  • Option Item Flexible schedule including weekends
  • Option Item Hands-on exercises with virtual labs
  • Option Item Session recordings and learning courseware included
  • Option Item 24X7 learner support and assistance
  • Option Item Book a free demo before you commit!
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Corporate Training

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  • Option Item Everything in 1-on-1 Training plus
  • Option Item Custom Curriculum
  • Option Item Extended access to virtual labs
  • Option Item Detailed reporting of every candidate
  • Option Item Projects and assessments
  • Option Item Consulting Support
  • Option Item Training aligned to business outcomes
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Course Reviews


  • Introduction to Big Data
  • Challenges with Big Data
  • Batch Vs. Real Time Big Data Analytics
  • Batch Analytics – Hadoop Ecosystem Overview
  • Real Time Analytics Options
  • Streaming Data – Storm
  • In Memory Data – Spark
  • What is Spark?
  • Modes of Spark
  • Spark Installation Demo
  • Overview of Spark on a cluster
  • Spark Standalone Cluster

  • Invoking Spark Shell
  • Creating the Spark Context
  • Loading a File in Shell
  • Performing Some Basic Operations on Files in Spark Shell
  • Building a Spark Project with sbt
  • Running Spark Project with sbt
  • Caching Overview
  • Distributed Persistence
  • Spark Streaming Overview
  • Example: Streaming Word Count

  • RDDs
  • Spark Transformations in RDD
  • Actions in RDD
  • Loading Data in RDD
  • Saving Data through RDD
  • Spark Key-Value Pair RDD
  • Map Reduce and Pair RDD Operations in Spark
  • Scala and Hadoop Integration Hands on

  • Why Shark?
  • Installing Shark
  • Running Shark
  • Loading of Data
  • Hive Queries through Spark
  • Testing Tips in Scala
  • Performance Tuning Tips in Spark
  • Shared Variables: Broadcast Variables
  • Shared Variables: Accumulators
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Target Audience:

  • Data analysts and scientists
  • Software developers
  • Big Data professionals
  • IT professionals seeking to learn Spark
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  • Knowledge of programming languages such as Java, Python, or Scala
  • Familiarity with SQL
  • Basic understanding of Big Data concepts
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Benefits of the course:

  • Comprehensive understanding of Apache Spark and its practical applications
  • Hands-on experience in building and deploying Spark applications
  • Industry-relevant curriculum with practical examples
  • Expert-led training with customized learning paths
  • Flexibility to learn at your own pace with self-paced modules
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Exam details to pass the course:

  • There is no exam to pass the Apache Spark training course.
  • Learners will receive a certificate of completion upon finishing the course.
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Certification path:

  • Cloudera Certified Spark and Hadoop Developer
  • Databricks Certified Associate Developer for Apache Spark
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Career options:

  • Big Data Developer
  • Data Analyst
  • Data Scientist
  • Hadoop Developer
  • Spark Developer

Why should you take this course from Skillzcafe:

Why should you take this course from Skillzcafe:
  • Bullet Icon Industry experts as trainers with years of experience in Big Data and Spark
  • Bullet Icon Self-paced learning with 24x7 access to course material
  • Bullet Icon Real-life examples and use cases
  • Bullet Icon Interactive sessions with trainers and peers
  • Bullet Icon Affordable pricing with flexible payment options


Yes, learners are required to have prior programming experience in languages such as Java, Python, or Scala.

While some prior programming experience is necessary, this course is designed to provide learners with a comprehensive understanding of Apache Spark, even if they are relatively new to the field.

Learners will have the opportunity to work on real-life projects and assignments, giving them hands-on experience in building and deploying Spark applications.

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