Should You Be a Data Science Generalist or Specialist?
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In this video I tackle the question of whether you should be a data science GENERALIST or a data science SPECIALIST. I delve into what exactly these actually are in practice, the advantages and shortcomings associated with each of these, and some considerations you should have as you launch a career in data science.
Some articles used to inspire this video:
“Why you should be a Generalist first, Specialist later as a Data Scientist?” – Admond Lee: https://towardsdatascience.com/why-you-should-be-a-generalist-first-specialist-later-as-a-data-scientist-f26d687f8c6
“Generalists vs. Specialists in Data Science and Analytics” – Cameron Warren: https://towardsdatascience.com/generalists-vs-specialists-in-data-science-and-analytics-fe5d8b55f1e6
“Why You Should be a Data Science Generalist – and How to Become One” – Vincent Granville: https://www.datasciencecentral.com/profiles/blogs/why-you-should-be-a-data-science-generalist
“Why Data Science Teams Need Generalists, Not Specialists” – O’Reilly Media: https://medium.com/oreillymedia/why-data-science-teams-need-generalists-not-specialists-955383d0bb1b
“Want a Job in Data Science? Here’s Why You Should Specialize” – Dataquest: https://www.dataquest.io/blog/job-data-science-specialize/
“Generalists Dominate Data Science” – Russell Jurney: https://www.kdnuggets.com/2018/02/generalists-dominate-data-science.html
“Who Can Yield Better Outcomes in Data Science: A Generalist Or a Specialist?” – Smriti Srivastava: https://www.analyticsinsight.net/who-can-yield-better-outcomes-in-data-science-a-generalist-or-a-specialist/
“Why You Shouldn’t be a Data Science Generalist” – Jeremie Harris: https://www.kdnuggets.com/2018/12/why-shouldnt-data-science-generalist.html