$550 – $650

Introduction to Apache Spark training for beginners in Toledo, OH | End to...

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Entirety Technology

Toledo, OH 43613.0

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Refund Policy

Refund Policy

Refunds up to 1 day before event

Event description

Description

In this course we start at foundational level with Apache Spark technical essentials where you can learn the foundations of Apache Spark, master real-time data processing using Spark streaming, Spark SQL, Spark Machine Learning Libraries (Spark MLib)


Course Schedule


Prerequisites

  • Exposure to knowledge of databases, SQL (Structured query language).
  • Basic knowledge of object-oriented programming.
  • Knowledge of Scala.


Course Features

  • 4 weeks, 8 sessions, 16 hours of total LIVE Instruction
  • Training material, instructor handouts and access to useful resources on the cloud provided
  • Practical Hands on Lab exercises on cloud workstations provided
  • Actual code and scripts provided
  • Real-life Scenarios


Course Outline

  1. Introduction to Spark
  2. Spark Vs MapReduce
  3. Spark Vs Hadoop
  4. Spark Installation, Configuration, Shell
  5. Spark and Resilient Distributed Datasets (RDD)
  6. Batch and Real-Time Analytics with Apache Spark
  7. Functional Programming
  8. Spark Architecture
  9. Collections
  10. Object-Oriented Programming
  11. Integrations
  12. Spark Core
  13. Persistence
  14. Cassandra (NoSQL database)
  15. Spark Integration with NoSQL (Cassandra) and Amazon EC2
  16. Spark Streaming
  17. Spark SQL
  18. Spark MLLib
  19. How to write and deploy Spark Applications
  20. Spark Parallel Processing
  21. Kafka
  22. Spark performance
  23. Scheduling and Partitioning


Refund Policy

  • 100% refund can be applied if request is initiated 24 hours before the 1st course session.
  • If a class is rescheduled/cancelled by the organizer, registered students will be offered a credit towards any future course or a 100% refund.










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Date and Time

Location

Entirety Technology

Toledo, OH 43613.0

View Map

Refund Policy

Refunds up to 1 day before event

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