Common pitfalls faced when working on a Data Science project and how to avoid them

Common pitfalls faced when working on a Data Science project and how to avoid them

May 6, 2020 Data Science DATAcated Challenge 0

Common pitfalls faced when working on a Data Science project and how to avoid them

I will try to focus on the most common mistakes which people made during the data science projects –

  1. Using too many Data Science Terms in your Resume – People use to copy others resume which they should avoid
  2. Not Spending Enough Time on Exploring and Visualizing the Data (Curiosity) – They don’t try to understand the data before visualization
  3. Not Having a Structured Approach to Problem Solving – They should follow a trusted approach
  4. Trying to Learn Multiple Tools at Once – Don’t Mix with other tools, one tool at one time
  5. Not Studying in a Consistent Manner – Please be consistent about your study and be focussed
  6. Shying Away from Discussions and Competitions – Tyr to take part in more hackathons, competitions, write blogs and try to post questions in communities ( Tableau, SAS, QLIK)
  7. Not working on Communication Skills – Most important try to speak well be specific and to the point, try to relate with your real-life problem then describe
  8. Try to apply the methods which you learn
  9. Focus on the model accuracy – They should focus on the model accuracy ( try to understand the R square and P-value well)

Author – Satyabrata Majhi

 

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