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data science

"A Prelude to Pyro" by Metis Sr. Data Scientist Chad Scherrer

By Metis • August 31, 2018

Metis Sr. Data Scientist Chad Scherrer has been exploring Pyro, a recent development in probabilistic programming from Uber AI Labs. In this post, he breaks down the meaning of it all and remarks on the potential.

alumni
Meet Dangaia Sims, Metis Bootcamp Grad and Sr. Data Scientist at IBM

By Emily Wilson • August 23, 2018

In this brief interview, hear Metis grad Dangaia Sims tell the story of her transition from academia (Ph.D., Kinesiology) to industry and how the bootcamp helped her get there.

data science
Sr. Data Scientist Roundup: Climate Modeling, Deep Learning Cheat Sheet, & NLP Pipeline Management

By Emily Wilson • August 21, 2018

When our Sr. Data Scientists aren't teaching the intensive, 12-week bootcamps , they're working on a variety of other projects. This monthly blog series tracks some of their recent activities and accomplishments. This month, read about projects covering climate modeling, deep learning, & NLP pipeline management.

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Metis Seattle Graduate Susan Fung's Journey from Academia to Data Science

By Emily Wilson • August 08, 2018

Always passionate about the sciences, Susan Fung earned her Ph.D. in Neurobiology from the University of Washington before even thinking about the existence of data science bootcamps . In a recent (and excellent) blog post , she wrote: "My day to day involved designing experiments and making sure I had ...

interviews
Course Report Interview: Why Student Chose Part-Time Python Course Before Bootcamp

By Metis • August 07, 2018

In an interview with Course Report, current Metis bootcamp student Carolina Gonzalez discussed her decision to take the Metis Beginner Python & Math for Data Science part-time course before applying to the full-time immersive bootcamp.

alumni
Made at Metis: Waste Analysis + Building Data Science Solutions

By Emily Wilson • August 01, 2018

Take a look around and you might notice some waste. It could come in the form of something physical that you can see or feel or smell. Or it might be invisible to the eye, like wasted time or resources due to lapses in efficiency. Two recent Metis graduates took an interest in these different forms of waste and used data science to come up with ways to minimize negative impact and maximize positive solutions.

data science
The Value of a Bootcamp Education (vs. Academia & MOOCs)

By Metis • July 30, 2018

Data science is booming and the appeal of positions in the field is eliciting unprecedented interest. But as many across disciplines are trying to maneuver into the field, they quickly find a skills-gap they need to overcome – and the job search will be a significant challenge even after those skills are acquired. Metis Senior Admissions Manager Josh Shaman tackled his weighty topic in a recent article for SwitchUp, through which he compares the value of an immersive bootcamp experience to university programs to massive open online classes (MOOCs).

data science
Impact of Sample Size on Transfer Learning

By Roberto Reif • July 05, 2018

In this post, Metis Sr. Data Scientist Roberto Reif explores transfer learning, a method of using a deep learning model that has already been trained to solve one problem containing large amounts of data, and applying it (with some minor modifications) to solve a different problem that contains small amounts of data. He analyzes the limit for how small a data set needs to be in order to successfully apply this technique.

alumni
Academia to Data Science: Where Does a Bootcamp Fit into the Equation?

By Emily Wilson • July 05, 2018

To transition from academia to industry, many choose bootcamps as a way to bridge the gap between the theory-heavy rigor of academia and the practicality of industry experience. In this post, hear from three such students who made the transition via bootcamp and who are now working in the field.

data science
Check Out Five Passion Projects Created by Metis Sr. Data Scientists

By Metis • June 21, 2018

Metis Sr. Data Scientists teach our 12-week data science bootcamps, work on curriculum development, present at conferences, perform corporate training, and more throughout a rotating yearly schedule. Built into that is a passion quarter, during which each works on a project that suits their interests and allows them to dig deeply into a facet of data science. Read here to learn about two recently wrapped three and three ongoing passion projects.