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Open Up the Open Source Mindset
Tapping Into the Data Scientist’s Toolbox to Solve Research Challenges

Workshop overview

Join us in an "encore" hands-on tutorial that will prime you on the macro forces at play in the world of open source and give you the tools to apply your learnings. Get inspired, hear firsthand accounts and then jump right into a four-phase practicum to embrace foundational open source tools to solve traditional research challenges in real-time. Bring your laptops and be ready to learn how to 1) install R and Python and read in data; 2) clean and restructure the data with Python; 3) leverage R to mine the data for insights; 4) visualize data using these tools.

Coming out of this immersive all-day session (group exercises, breakouts, real-world examples), you will gain confidence in accessing and applying open source tools to your own data-driven challenges. Specifically, you will have the step-by-step instructions and code needed to install and begin working in essential open source languages, as well as the structure of code required to perform standard data cleaning and analysis. Throughout the day, we will pepper in examples of the advantages of open source in our ongoing work to underscore the impact of these tools in an industry that has long relied on proprietary software and technologies.

Opening up the open source mindset in your organization will encourage innovation, collaboration and efficiencies, and arm you with the contagious spirit necessary to remain relevant in a changing industry.


Intermediate to Advanced

Workshop leaders

Claire Gilbert

Claire Gilbert

Senior Statistical Analyst
Gongos, Inc.

As a Data Scientist, Claire is responsible for translating data into actionable insights and providing data-driven recommendations to clients. With a rigorous statistical background and enthusiasm for applying path to purchase across varied markets, she is heavily involved in segmentation and shopper journey work at Gongos. Claire is particularly interested in segmentation, consumer profiling, and explaining statistical methods.

She holds a BS and MS in Statistics from Miami University with specializations in Actuarial Science and Anthropology.

Troy Burmeister

Data Scientist

As a Senior Statistical Analyst, Troy is responsible for building statistical models, mining for critical insights and providing data-driven recommendations to clients. He is integral in infusing new tools to coalesce primary research data with big data. By leveraging open source tools, such as R and Python, Troy has brought both opportunity and efficiencies in solving traditional insights challenges.
He has BS in Statistics from Michigan State University; and specialization in Actuarial Science.