Data science is a multi-disciplinary domain. What it means is, to be a good data scientist you have to be a jack of all trades—statistics, mathematics, computer science and more. Programming underlies all major tasks performed by data scientists – data collection, manipulation, analysis, visualization, etc. Therefore, a handful of programming languages are rudimentary to establish a strong base in data science.
The gist of the tale is – become good at programming. The increasing demand and supply gap in the data science industry is another factor that calls for data scientists to become proficient in programming languages.
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