DataTalks.Club

The ABC’s of Data Science - Danny Ma

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Did you know that there are 3 types different types of data scientists? A for analyst, B for builder, and C for consultant - we discuss the key differences between each one and some learning strategies you can use to become A, B, or C.


We talked about:


  • Inspirations for memes 
  • Danny's background and career journey
  • The ABCs of data science - the story behind the idea
  • Data scientist type A - Analyst 
  • Skills, responsibilities, and background for type A
  • Transitioning from data analytics to type A data scientist (that's the path Danny took)
  • How can we become more curious?
  • Data scientist B - Builder 
  • Responsibilities and background for type B
  • Transitioning from type A to type B
  • Most important skills for type B
  • Why you have to learn more about cloud 
  • Data scientist type C - consultant
  • Skills, responsibilities, and background for type C
  • Growing into the C type
  • Ideal data science team
  • Important business metrics
  • Getting a job - easier as type A or type B?
  • Looking for a job without experience
  • Two approaches for job search: "apply everywhere" and "apply nowhere"
  • Are bootcamps useful?
  • Learning path to becoming a data scientist
  • Danny's data apprenticeship program and "Serious SQL" course 
  • Why SQL is the most important skill
  • R vs Python
  • Importance of Masters and PhD


    • Links:


    • Danny's profile on LinkedIn: https://linkedin.com/in/datawithdanny
    • Danny's course: https://datawithdanny.com/
    • Trailer: https://www.linkedin.com/posts/datawithdanny_datascientist-data-activity-6767988552811847680-GzUK/
    • Technical debt paper: https://proceedings.neurips.cc/paper/2015/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html


      • Join DataTalks.Club: https://datatalks.club/slack.html

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