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In your quest to become a data scientist you’ve already done a deep dive into statistics and linear algebra. You’ve enrolled in a rigorous data science bootcamp or completed an online course in order to learn the necessary coding skills, and you’ve even started structuring your projects in an organized way. You’re feeling good about your choices, but you can sense that something still isn’t right. You’ve noticed that sometimes when you go back to use a function that worked days or even hours ago it throws an error. What’s more, when your data science project partners use…

Photo by Markus Spiske on Unsplash

The Problem
In the middle of my last data science project, I realized that I had a real problem. After staying up late the night before to clean a particularly disorganized dataset, I woke up to discover that much of my hard work had been lost. What’s worse, I had simultaneously been working in a number of different jupyter notebooks, so the code I did have was disordered and unclear. …

I recently accepted a Data Science Fellowship at the Flatiron School in Washington D.C. For 4 months, I will be immersed in data science and machine learning, honing my skills in Python and SQL and deepening my understanding of linear algebra and statistical analysis. But, why would a policy analyst need to study data science?

Over the course of my public policy graduate program at the University of Chicago, I learned not only what public policy is and what good policy looks like, but — more significantly — I discovered a new way to organize information and think about the…

Misha Berrien

Data Scientist & Policy Analyst in Chicago, IL.

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