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

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…

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