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How to Get Hadoop Certified - Step-by-Step Guide

Professional certifications could set you apart in the ever more competitive job market. Big Data has been all the rage recently, so follow this step by step guide on how to get certified as a Big Data professional.
Step 1: Earn $250 for your certification exam through any means necessary.

 To register for the new hands-on exams, create an account at www.examslocal.com, then search for “Hortonworks”. The cost of each exam is $250 USD. You can take the exam anytime, anywhere using your own computer.
These exam would give you an niche when applying for most tech companies.

 Step 2: Sign up for HDP Certified Developer (HDPCD) at Hortonworks website. Follow this link.

Step 3: Install their VM to OracleBox, Follow the lab. Do not learn anything by the end of the labs.

 It's highly recommended to pay $40 for the labs which give you details on how you can use Hadoop. If you only want to learning about Hadoop and don't want to spend your money on the certificate, then you should definitely buy the following digital guides from https://marketplace.mimeo.com/HWAcademicPartners 

 HDP Developer_ Apache Pig and Hive-Student Guide-Rev 6.1
HDP Developer_ Apache Pig and Hive-Lab Guide-Rev 6.1

 Step 4.  Sign up for Amazon Web Service to take HDPCD practice exam. 

 Use the virtual machine with EC2 from Amazon https://aws.amazon.com/ during the exam. It'll charge you a very small amount of money (few cents).

Step 5: Take the exam. Have a terrible experience and think you failed it. 

Step 6: Congratulations! You passed it! Polish your resume and Wear your new badge proudly. 

Comments

  1. AnonymousApril 21, 2017 at 9:51 PM

    Where are the pictures?

    ReplyDelete
    Replies
    1. UnknownApril 22, 2017 at 5:38 PM

      We're doing A/B Testing, so there's a 50% chance of you seeing the post with pictures!

      Delete
  2. likithaNovember 21, 2018 at 10:46 PM

    Thank you for your guide to with upgrade information about Hadoop
    Hadoop admin Online Course

    ReplyDelete

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