Moving Beyond Language Loyalty to Achieve More

How often have you heard the phrase “X is better than Y for data science”? This is a very common misconception among data scientists and a very broad definition of data science as a whole. For data science to be impactful, it must be credible, agile, and durable. To be able to do this, we need to embrace the differences between R and. Python. Maybe you prefer R for data wrangling and Python for modeling – that’s great! Why should serious data science be stifled for the sake of language loyalty? Data science teams need to use the wealth of tools available to deliver the most impactful results. This webinar will be a discussion among data science leaders, debunking this common myth that you have to make a choice between R and Python.

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