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7 Traits a Big Data Scientist Shouldn’t Have - Remember, I’m using data scientist as a bit of a catch-all term to include data analysts, engineers, programmers, and more. But taking into account that we want data scientists to have a balance of common sense, business skills, creativity, a geeky love of statistics, and data skills management skills, I was curious what sorts of traits would be the opposite? What would add up to make a bad data scientist? Click here to read the article.

10 great books about R - Books are a great way to learn a new programming language. Code samples is another great tool to start learning R, especially if you already use a different programming language. You might also want to check our DSC articles about R: they also include cheat sheets. If you are unsure about learning R, read about R versus Python. Click here to read the article.

Python for Data Science vs Python for Web Development - Python programming language might not be an ideal choice for web application development, but is extensively used by many organizations for evaluating large datasets, for data visualization, for running data analysis or prototyping. Python programming language is gaining traction amongst users for data science whilst being outmoded as a web programming language.  Click here to read the article.

An Introduction to Machine Learning Theory and Its Applications - The supply of able ML designers has yet to catch up to this demand. A major reason for this is that ML is just plain tricky. This tutorial introduces the basics of Machine Learning theory, laying down the common themes and concepts, making it easy to follow the logic and get comfortable with the topic. Click here to read the article.

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