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.
Here, Daniel talks about his upcoming book, whether to start learning python or R for data science, the best paths to becoming a data scientist and much more. Daniel is a Software Carpentry instructor and a doctoral student in Genetics, Bioinformatics, and Computational Biology at Virginia Tech, where he works in the Social and Decision Analytics Laboratory under the Biocomplexity Institute. He received his MPH at the Mailman School of Public Health in Epidemiology and is interested in integrating hospital data in order to perform predictive health analytics and build clinical support tools for clinicians. An advocate of open science, he aspires to bridge data science with epidemiology and health care.
Dhavide Aruliah is Director of Training at Anaconda, the leading Open Data Science platform powered by Python. Dhavide was previously an Associate Professor at the University of Ontario Institute of Technology (UOIT). He served as Program Director for various undergraduate & postgraduate programs at UOIT. His research interests include computational inverse problems, numerical linear algebra, & high-performance computing. Together with Hugo, Dhavide goes over the process of designing a course, his work at Anaconda, his path to Python and more.
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