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You can master Hadoop, irrespective of your IT background. While basic knowledge of Core Java and SQL might help, it is not a pre-requisite for learning Hadoop.

Course Objectives By the end of the course, you will: 1. Master the concepts of HDFS and MapReduce framework 2. Understand Hadoop 2.x Architecture 3. Setup Hadoop Cluster and write Complex MapReduce programs 4. Learn data loading techniques using Sqoop and Flume 5. Perform data analytics using Pig, Hive and YARN 6. Implement HBase and MapReduce integration 7. Implement Advanced Usage and Indexing 8. Schedule jobs using Oozie 9. Implement best practices for Hadoop development 10. Work on a real life Project on Big Data Analytics 11. Understand Spark and its Ecosystem 12. Learn how to work in RDD in Spark

Topics Name
Online Session
Online Session
Hadoop_Pig_Hive_Sqoop

Hadoop,Pig,Hive,Sqoop

Lab Set Up ( For all Machines ) Hardware : Intel Core 5 processor with 16GB Recommended RAM. OS : Ubuntu Server ( Latest Version ) or Cent OS or Mac OS or Windows 64 bit 7/8/10 ( Latest preferable version ) High Speed Internet Connection ( Open Port for Installations ) Software Prerequisites Java ( Latest Version ) , Scala ( Latest Version) Apache Spark [ Latest Version ] (Downloadable from http://spark.apache.org/downloads.html) A Python distribution containing IPython, Pandas and Scikit-learn Anaconda with Python3.6, PySpark Local Environment www.anaconda.com [ Local Machine ] Hadoop, PySpark PySpark on Hadoop Cloud Environment OR Cloudera Hadoop or Online Databriks Cloud

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