All DataChats


Justin Bois, 14 August 2017

Justin Bois is a lecturer in the Division of Biology and Biological Engineering at the California Institute of Technology. He teaches nine different classes there, nearly all of which heavily feature Python. He is dedicated to empowering students in the biological sciences with quantitative tools, particularly data analysis skills. Beyond biologists, he is thrilled to develop courses for DataCamp. In this DataChat, Hugo and Justin discuss different aspects of data science, including data science education, and Justin shares his advice to those getting started in the field.


Chester Ismay, 9 August 2017

Chester builds (and helps instructors build) R and SQL courses for DataCamp. Chester has experience working as an actuary, as a professor, and as a statistical/data scientist consultant in academia. In addition, he has worked as a consultant for actuarial firms and the Portland Trailblazers NBA team. He is co-author of the fivethirtyeight R package and author of the thesisdown R package. He is also a co-author of ModernDive, an open source textbook for introductory statistics and data science students using R.


Brett Lantz, 7 Aug 2017

Brett Lantz is a data scientist at the University of Michigan and the author of Machine Learning with R. After training as a sociologist, Brett has applied his endless thirst for data to projects that involve understanding and predicting human behavior.


Charlotte Wickham & Oliver Keyes, 30 July 2017

Richie chats to Oliver and Charlotte about the importance of web data, how Oliver isn’t a data scientist, how Charlotte uses data on the web for teaching, web APIs and R packages to access them, web scraping for social good, and data in the cloud vs. computing in the cloud.


Nina Zumel & John Mount, 20 June 2017

Richie chats to Nina and John about their favorite types of regression, statistics vs. machine learning, running Win-Vector, interacting with data scientists vs. interacting with managers, business constraints on models, the vtreat R package, bangra dancing, and life in San Francisco.


Katharine Jarmul, 12 June 2017

Katharine Jarmul runs a data analysis company called kjamistan that specializes in helping companies analyze data and training others on data analysis best practices, particularly with Python. She has been using Python for 8 years for a variety of data work -- including telling stories at major national newspapers, building large scale aggregation software, making decisions based on customer analytics, and marketing spend and advising new ventures on the competitive landscape.

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