For the Data Science Chicago meetup I shared about the Metis Data Science Bootcamp that I have developed with Irmak Sirer and other members of the Datascope team, which we'll be teaching the first cohort in New York City this Autumn (2014).
Here's the original abstract/announcement:
Data Science Bootcamp: like the regular kind of bootcamp but with data science instead of running and pushups.
The best data scientists are insanely curious people who are good at thinking in systems, are comfortable with the quantitative, and aren't intimidated by new things. They write code. They know stats, machine learning, and all the relevant languages, tools, and packages (or at least they know how to google the doc pages). If that weren’t enough, they also have a knack for communicating results and for understanding and resolving poorly-posed questions, usually involving some combination of talent in verbal and visuospatial communication. Making new, high-quality data scientists is a non-trivial endeavor.
Recently Datascope has been in cahoots with Metis (part of Kaplan) to develop and launch a data science bootcamp, a 12-week training program to get new data scientists ready to hit the job market, land a job, and survive and thrive in their new careers. Metis Data Science Bootcamp is only the second data science training program using the bootcamp model, and we’re really excited about what we’ve created. Laurie Skelly will share some of the choices and models her team has made to determine who to admit, what to require, what to teach, and what to blow off. She will discuss the relative merits of bootcamps vs master’s degrees, MOOCs, and self-teaching, and she'll answer your questions.
