This is the 5th and final installment of a series by Metis Sr. Data Scientist Zach Miller dedicated to investigating how Monte Carlo can be a great tool. In it, he discusses using Monte Carlo to measure business impact.
In Part 4 of our ongoing series on the Monte Carlo Simulation, Metis Sr. Data Scientist Zach Miller asks and answers the question: "How do physicists use Monte Carlo to simulate particle interactions?"
In the second installment of our Demystifying Data Science Video Series, you'll hear talks from three working data scientists about their roles, their ideas of what makes a data scientist, and what you should know about the complex, evolving, exciting field.
In this month's edition of the Made at Metis blog series, we're highlighting two recent student projects that focus on the act of (non-physical) fighting. One aims to use data science to fight the problematic political practice of gerrymandering and another works to fight the biased algorithms that attempt to predict crime.
You may already know the basics about our bootcamp. It's intensive, lasts 12 weeks, and is project-focused, for instance. But did you know there are many hidden benefits of the bootcamp? This post will give you a better idea of everything the bootcamp has to offer.
Back in September 2017, we hosted a free, live online conference featuring 12 straight hours of data science talks from more than 25 of the industry's best and brightest speakers. Demystifying Data Science was an awesome day of insights, advice, information, and interaction for aspiring data scientists. To share it all, we've broken the collection of recordings into a six-part blog series, of which this is the first.
One of the most powerful techniques in any data scientist's tool belt is the Monte Carlo Simulation. It's flexible and powerful since it can be applied to almost any situation if the problem can be stated probabilistically. However, Metis Sr. Data Scientist Zach Miller has found that for many, the concept of using Monte Carlo is obscured by a fundamental misunderstanding of what it is. To address that, he's put together a series of small projects demonstrating the power of Monte Carlo in a few different fields.
Andrew Savage has been managing career placement and employer partnerships at Metis for the past two years. He's helped hundreds of our alumni get jobs as Data Scientists, Machine Learning Engineers, and increasingly, AI Engineers. Read his sound advice on navigating the related job market.