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Big Data Hadoop_Online

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    Big Data/ Hadoop Analyst +Coop(Online)   Spring 2018    Quality is never an accident; it is always the result of good planning, intellient direction and skillful execution  –   John Ruskin  Page 2 Contents 1. Introduction .......................................................................................................................................... 4 2. Objective ............................................................................................................................................... 4 3. Schedule ................................................................................................................................................ 4 4. Cost ....................................................................................................................................................... 5 5. Career Roadmap ................................................................................................................................... 5 6. Course Outline ...................................................................................................................................... 5 7. Contact Us ........................................................................................................................................... 10    Quality is never an accident; it is always the result of good planning, intellient direction and skillful execution  –   John Ruskin  Page 3 Copyright Notice Copyright © 2018, busyQA Inc All   rights reserved   No part of this document may be reproduced in any form, including photocopying or transmission electronically to any computer,  without prior written consent of busyQA. The information contained in this document is proprietary to busyQA Inc and may not be used or disclosed except as expressly authorized in writing by busyQA. Trademarks   Company name, logo and other products mentioned in this document are registered trademarks of busyQA.    Quality is never an accident; it is always the result of good planning, intellient direction and skillful execution  –   John Ruskin  Page 4 1.   Introduction This training course is a professional development program design to give students the theoretical background and practical knowledge and skills required to succeed in the Big Data field as Hadoop Big Data test analyst and Big Data Engineer. The course covers various components of Hadoop, MapReduce, HDFS, Pig, Hive, Sqoop, Flume, Spark along with NoSQL Databases. 2.   Objective The primary objectives of this course are to:    Help students master the concepts of the Hadoop   framework.      Show students how the Hadoop ecosystem  fits into the Big Data processing lifecycle.    Help students gain in-depth knowledge of spark , HDFS , YARN , and MapReduce.      Teach students on how to use Pig , Hive , and Impala  to process and analyze large dataset    Train on how to use Sqoop  and Flume  for data ingestion with big data training    Master real-time data processing, functional programming and parallel processing in Spark      Master big data hadoop testing activities    Run a resume and career workshop that will aid students with career opportunities as a Big Data Analyst. 3.   Schedule The course is a 75hours (10 weeks) program with 1 ½ hrs daily Monday- Friday online training. Students are advised to spend more time learning class materials and gaining hands on experience during their personal time. Module 1 Data warehousing, ETL & Big Data concepts Module 2 Linux & Shell scripting Module 3 Java/Python essentials for Hadoop Module 4 Hadoop HDFS, MapReduce & Yarn Module 5 Querying Data using Hive/Impala Module 6 Ingesting data using Apache Sqoop Module 7 Streaming data using Apache flume Module 8 Processing and Transforming data using Apache Pig Module 9 NoSQL Database (MongoDB/Cassandra) Module 10 Apache Spark Module 11 Scala Module 12 Hadoop/Big Data testing Co-op (bonus) 1 - 3 month Hands on work experience Resume Workshop, Mock Interview
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