From the course: Data Science Team Lifecycle Management

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How to determine when a data scientist should acquire more schooling

How to determine when a data scientist should acquire more schooling

From the course: Data Science Team Lifecycle Management

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How to determine when a data scientist should acquire more schooling

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- Data science is a multifaceted, interdisciplinary field of study that involves continuous education. But not all data scientists progress at the same rate, nor are they uniformly strong in all the same skills. So understanding when additional education and training are needed is important to advancing someone's career as a successful data scientist. Let's look at how to assess someone's skills and thoughtfully determine if more education is required. We learned in a previous video that all data scientists are polymaths and have three specific skill sets, which are math and stats, coding, and machine learning theory. Codifying these skills into a job description is a good place to start if you're a data science manager. Evaluating your staff on these skills is equally important. This is where the skills rubric comes in, which we also discussed in a previous video. Let's say I'm working on a team developing deep…

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