So, you want to be a data scientist- 7 fundamental questions you can ask yourself

  1. ๐’๐จ, ๐ฒ๐จ๐ฎ ๐ฐ๐š๐ง๐ญ ๐ญ๐จ ๐›๐ž ๐š ๐ƒ๐š๐ญ๐š-๐ฌ๐œ๐ข๐ž๐ง๐ญ๐ข๐ฌ๐ญ? ๐‹๐ž๐š๐ซ๐ง๐ข๐ง๐  ๐’๐ค๐ข๐ฅ๐ฅ๐ฌ ๐ญ๐ก๐š๐ญ ๐ฒ๐จ๐ฎ ๐œ๐š๐ง๐ง๐จ๐ญ ๐›๐ž ๐ญ๐ซ๐š๐ข๐ง๐ž๐ ๐Ÿ๐จ๐ซ ๐ข๐ฌ ๐ฐ๐ก๐š๐ญ ๐ฆ๐š๐ค๐ž๐ฌ ๐ฒ๐จ๐ฎ ๐ข๐ง๐๐ข๐ฌ๐ฉ๐ž๐ง๐ฌ๐š๐›๐ฅ๐ž

There is an abundance of online content/MOOC’s that talk about technical skills that need to be picked up around Math, Programming and ML

They are good skill-sets – Absolutely.

But picking up skills that cannot be trained for is what makes you irreplaceable.

How do you build that knowledge?

I put together 7 fundamental questions you can ask yourself that makes you unique for today’s #2MinExplainer series

[That rarely is 2 mins long]

#datasciences
#SkillsThatCantBeTrainedFor
#reviewswithranjani

TL:DR :

  1. Why choose Data sciences โ€“ Why does it matter to you?
  2. โ€œNot all Data scientists are the sameโ€ – How do identifying areas that align to your strengths
  3. Did you know? – Day in the life of a data scientist
  4. Be an artist, not a painter
  5. Create a portfolio
  6. Making a transition or a break into the space as a beginner
  7. Solve Problems

โ€œYou get paid in direct proportion to the difficulty of problems you solveโ€

ย 

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