Python Spark Certification Training using PySpark

This training is designed to provide you the knowledge and skills that are required to become a successful Spark Developer using Python and prepare you for the Cloudera Hadoop and Spark Developer Certification Exam (CCA175).  

Python Spark Certification Training using PySpark
Цена
449 $
Кэшбэк до 5%
6 недель6 недель
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АнглийскийАнглийский
Edureka
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Описание:

PySpark Certification Training Course is designed to provide you with the knowledge and skills to become a successful Big Data & Spark Developer. This Training would help you to clear the CCA Spark and Hadoop Developer (CCA175) Examination.
You will understand the basics of Big Data and Hadoop. You will learn how Spark enables in-memory data processing and runs much faster than Hadoop MapReduce. You will also learn about RDDs, Spark SQL for structured processing, different APIs offered by Spark such as Spark Streaming, Spark MLlib. This course is an integral part of a Big Data Developer’s Career path. It will also encompass the fundamental concepts such as data capturing using Flume, data loading using Sqoop, messaging system like Kafka, etc.

Spark Certification Training is designed by industry experts to make you a Certified Spark Developer. The PySpark Course offers:

  • Overview of Big Data & Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator)
  • Comprehensive knowledge of various tools that falls in Spark Ecosystem like Spark SQL, Spark MlLib, Sqoop, Kafka, Flume and Spark Streaming
  • The capability to ingest data in HDFS using Sqoop & Flume, and analyze those large datasets stored in the HDFS
  • The power of handling real time data feeds through a publish-subscribe messaging system like Kafka
  • The exposure to many real-life industry-based projects which will be executed using Edureka’s CloudLab
  • Projects which are diverse in nature covering banking, telecommunication, social media, and govenment domains
  • Rigorous involvement of a SME throughout the Spark Training to learn industry standards and best practices

Spark is one of the most growing and widely used tool for Big Data & Analytics. It has been adopted by multiple companies falling into various domains around the globe and therefore, offers promising career opportunities. In order to take part in these kind of opportunities, you need a structured training that is aligned as per Cloudera Hadoop and Spark Developer Certification (CCA175) and current industry requirements and best practices. 

Besides strong theoretical understanding, it is quite essential to have a strong hands-on experience. Hence, during the Edureka’s PySpark course, you will be working on various industry-based use-cases and projects incorporating big data and spark tools as a part of solution strategy.

Edureka’s PySpark Training is curated by Industry experts and helps you to become a Spark developer. During this course, you will be trained by Industry practitioners having multiple years of experience in the same domain. During Apache Spark and Scala course, you will be trained by our expert instructors to:

  • Master the concepts of HDFS
  • Understand Hadoop 2.x Architecture
  • Learn data loading techniques using Sqoop
  • Understand Spark and its Ecosystem
  • Implement Spark operations on Spark Shell
  • Understand the role of Spark RDD
  • Work with RDD in Spark
  • Implement Spark applications on YARN (Hadoop)
  • Implement machine learning algorithms like clustering using Spark MLlib API
  • Understand Spark SQL and it’s architecture
  • Understand messaging system like Kafka and its components
  • Integrate Kafka with real time streaming systems like Flume
  • Use Kafka to produce and consume messages from various sources including real time streaming sources like Twitter
  • Learn Spark Streaming
  • Use Spark Streaming for stream processing of live data
  • Solve multiple real-life industry-based use-cases which will be executed using Edureka’s CloudLab

Программа курса:

  • Introduction to Big Data Hadoop and Spark
  • Introduction to Python for Apache Spark
  • Functions, OOPs, and Modules in Python
  • Deep Dive into Apache Spark Framework
  • Playing with Spark RDDs
  • DataFrames and Spark SQL
  • Machine Learning using Spark MLlib
  • Deep Dive into Spark MLlib
  • Understanding Apache Kafka and Apache Flume
  • Apache Spark Streaming - Processing Multiple Batches
  • Apache Spark Streaming - Data Sources
  • Implementing an End-to-End Project
  • Spark GraphX (Self-Paced)