Big Data Camp

As organizational life continues to move online, it is tracked through various electronic media, such as websites, platforms, and social networks. All of our movements are being recorded as billions of digital traces. The ability to analyze the large-scale datasets generated by this digital activity is becoming a necessary skill for social scientists. To ensure that social science students are prepared, I have designed, organized, and led, a weeklong, all-day intensive workshop in big data and computational methods for PhD students called Big Data Camp. In this workshop, we introduce students to Python, SQL databases, the command line, and Python packages such as pandas, Beautiful Soup, Gensim and NLTK. While the first ICOS Big Data Camp occurred in 2013, from 2016-2018 I restructured and redesigned it to be:

1. More comprehensive: I led the expansion of the camp’s material offerings to include text analysis, Map/Reduce, pandas and Matplotlib
2. More research-focused: In camp, I brought in researchers and campus experts to demonstrate the significant potential of computational tools in various research use cases.
3. More replicable: The camp format and materials have been carefully refined. I can now bring this course to social science PhD students anywhere. I could also modify it to be part of an MBA “math camp,” or adapt it into a half-semester course for MBAs or undergraduates.

Everyone is capable of learning and using these tools. And it can be a lot of fun. If you would be interestied in having your students, workers, or community members get familiar with computational tools, please contact me. I would love to talk with you about teaching Big Data Camp as a workshop, adapting it to be a class, or structuring it to fit whatever your needs might be. I can be contacted here. Also please look at the Big Data Camp wesbite or examine the Github repository from the 2018 camp for sample code downloads.