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Metis Blog

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Infographic: Metis Bootcamp Alumni By The Numbers

By Metis • March 26, 2020

In this infographic, we break down a data set that’s near and dear to our hearts: one that represents our Data Science Bootcamp alumni. Find out where our grads are working and within what industries, where many of them call home across the United States and the world, what they studied pre-bootcamp, and much more.

alumni
Made at Metis: Space Audio Classification & The Art of Hiring Offshore Talent

By Metis • March 24, 2020

This post features two projects from recent graduates of our data science bootcamp. Take a look at what's possible to create in just 12 weeks.

news
Letter From Our Founder: Metis COVID-19 Update

By Jason Moss • March 18, 2020

Bob Dylan once sang, “Yesterday's just a memory. Tomorrow is never what it's supposed to be.” It’s hard to imagine more prescient words as the world grapples with the difficult, unprecedented, and global impact of the Coronavirus (COVID-19). Our thoughts are with those directly and indirectly impacted. In this post, I share some of the steps we’ve taken as a company to guarantee that we continue to deliver on our promise to help the world find value in data, while keeping our students and staff safe.

alumni
The Trifecta: From Bootcamp Prep Course to Bootcamp to New Career

By Emily Wilson • March 05, 2020

For Kari Davis, there’s before the bootcamp, and there’s after. A clear demarcation between two paces of professional life – one slower and more bureaucratic, the other fast-paced and constantly changing. Learn how a Metis Bootcamp Prep Course helped her prepare for the bootcamp and then land a new data science job.

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Free Webinar: Exploring the Adoption of Python in the Workplace

By Metis • March 04, 2020

During this upcoming (free!) webinar, hear Mike Galvin, Metis Executive Director of Corporate Training & Kevin Birnbaum, Metis Sr. Data Scientist, break down Python for data science and analytics, explain what's driving adoption in the field, and discuss how industries and companies are reacting to the shift.

data science
Data Scientist Roundup: Improving Recommendation Systems, Math for Data Science, & Pizza + Data Viz

By Emily Wilson • February 28, 2020

When our Data Scientists aren't teaching the intensive 12-week bootcamps or corporate training courses, they're working on a variety of other projects. This monthly blog series tracks and discusses some of their recent activities and accomplishments.

alumni
Made at Metis: Smarter Pricing for Airbnb & a Karaoke Recommendation Engine

By Metis • February 26, 2020

This post features two projects from recent graduates of our data science bootcamp. Take a look at what's possible to create in just 12 weeks, including a project to improve Airbnb's smart pricing tool and another to enhance a karaoke app by creating an added recommendation engine.

data science
Deep Dive: Math for Data Science Webinar on Course Report

By Metis • February 24, 2020

In partnership with Course Report, Metis Sr. Data Scientist Kimberly Fessel recently hosted a Math for Data Science webinar. During the 40-minute conversation, Kimberly highlights why you need math skills to be a Data Scientist and goes in-depth into which types of math you need to know in order to launch your career and find lasting success.

alumni
One Grad's Cross-Country Journey to Data Science Consulting

By Emily Wilson • February 21, 2020

Bootcamp graduate Carlie Badder wondered if she’d thrown her career off track by moving cross-country, leaving behind a solid research job. Read how she then found her way to the bootcamp and to a fulfilling career in data science consulting.

business resource
Simulating Business Outcomes With Monte Carlo Simulations

By Tony Yiu • February 20, 2020

Too often in the business world, we think deterministically. We plan our finances, inventories, etc. for the base case – and it usually works out alright. (After all, the base case is the scenario that is most likely to unfold.) A better way to forecast and think about the future is probabilistically - and an intuitive way to do this is via Monte Carlo simulations. Read why here.