W10: Stepping Into Data Science
Share this Session:
  Charlie Vollmer   Charlie Vollmer
Senior Statistician
ML Engineering


Sunday, April 17, 2016
02:30 PM - 05:45 PM

Level:  Introductory

What exactly is Data Science and what does it take to become a Data Scientist?

It's an amalgamation of analytical, computational, and statistical skills that enable one to draw well-founded inference from data and glean truly actionable insight. It's what all companies will need to take advantage of in order to survive in the new millennium, and why the demand and median salaries for Data Scientists continues to rise.

This tutorial is an introduction for all those interested in learning about the field of Data Science and - more specifically - those interested in delving into that world. We will overview various use cases commonly found in the workplace where data provides an opportunity to inform decision making from customer base growth and customer churn to product pricing and risk evaluation. We will then discuss the tools and techniques used to approach and, ultimately, solve these problems.

Attendees will leave with sufficient knowledge and hands-on experience to get started becoming a Data Scientist, along with the resources to take subsequent steps in the field.

All of the tools will come from the open-source community, using Python and R in Jupyter Notebooks. This enables fast and easy analysis and collaboration, along with free access for all attendees to develop their skills (not to mention the same tools that all Data Scientists use from Silicon Valley to London).

Charlie Vollmer is a Minnesota boy, at home in the mountains. When he is not teaching his seven-year-old how to ski powder, he is using mathematics to tell computers how to discover patterns in data. He believes anyone can do machine learning, and that by sharing information on computer science, we are all better off. He thinks that if you only give him the chance, he can teach you any statistical concept, and that you'll walk away actually thinking positively about math.

Close Window