Few people need further convincing that data science is hard. The well-known and oft quoted Sean J. Taylor says it well:

One more reason why data science (and most other STEM fields) is tough to master

For the sake of argument, however, lets try creating a list of what you might need to master in order to become a world-class data scientist:

  • Mathy stuff: Linear algebra, basic probability & statistics, bayesian statistics, calculus, maybe discrete math, likely graph theory (at least at some point)
  • Programming expertise: Python, R, possibly some Julia, perhaps Scala, maybe C or C++ for embedded systems…

Seth Clark

Co-founder and Head of Product at Modzy, product enthusiast, and serial hobbyist.

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