Python Spark Certification Training using PySpark

COURSE DESCRIPTION

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. you will be working on various industry-based use-cases and projects incorporating big data and spark tools as a part of solution strategy. The Course offers: 1.Overview of Big Data & Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) 2.Comprehensive knowledge of various tools that falls in Spark Ecosystem like Spark SQL, Spark MlLib, Sqoop, Kafka, Flume and Spark Streaming 3.The capability to ingest data in HDFS using Sqoop & Flume, and analyze those large datasets stored in the HDFS 4.The power of handling real time data feeds through a publish-subscribe messaging system like Kafka 5.The exposure to many real-life industry-based projects which will be executed using Edureka’s CloudLab 6.Projects which are diverse in nature covering banking, telecommunication, social media, and govenment domains 7.Rigorous involvement of a SME throughout the Spark Training to learn industry standards and best practices

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)