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Any group of students or professionals or startups may form teams. Team size of 1-4 is allowed

We advise you to make a cross-disciplinary team (Eg: Data Scientist, Big Data Engineer, Coder, Full Stack Developer). The teams should have the capability to analyze a huge amount of data, churn insights and develop data model prototypes.

  • Team sizes from 1-4 are allowed.
  • Please click on start stage button form a team.
  • You may proceed with a 1 member team or invite others via email.
  • You may also invite pre-registered candidates.
  • After the team formation is complete, please click on the end stage button at the top right corner of the screen and select “submit and end challenge” Please wait for qualification.

Once qualified from the team formation stage click on “start stage” button on the next stage. After the stage starts participants would have 2 days to finish the stage and make a submission. The details of the Problem & Evaluation will be shared on the day of Challenge.

All data sets shared by YES BANK will encrypted and anonymized to ensure highest level of customer security but will still be real data

Participants should code on their local machine and use any process as they feel it to be suited. The submission is to be uploaded as a file on the Skillenza platform. Please check the sample submission format to see how the submission file should be uploaded.

The Data will be hosted on AWS environment and the top 50 teams who qualify for the second round will get free AWS Credits.

The participants will get AWS Credits along with access to tools & Services from AWS & Cloudera.

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Watch the tutorial to complete the team formation stage


The selected 50 teams have received mails informing that they are now a part of the data race. We are really happy with the level of commitment and knowledge that all the teams have demonstrated. We would like to thank everyone for their participation and considering the level of participation we have seen, we would engage all of the participants who have demonstrated skills to solve analytics problems.


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