teaching-bilingual-classes-tidymodels-scikit.md

talk_id	talk_slug	talk_type	talk_tags	session_slug	talk_title	talk_title_short	talk_materials_url	speakers
22047	teaching-bilingual-classes-tidymodels-scikit	regular	interop python teaching	teaching-data-science	Teaching "bilingual" classes with {tidymodels} and scikit-learn	Teaching "bilingual" classes with {tidymodels} and scikit-learn		name affiliation url username photo bio Kelly Bodwin California Polytechnic State University webpage twitter github linkedin affiliation https://www.kelly-bodwin.com https://twitter.com/kellybodwin https://github.com/kbodwin statistics.calpoly.edu kelly_bodwin /assets/img/2022Conf/_talks/22047_kelly-bodwin.jpg Kelly Bodwin is an Assistant Professor of Statistics and Data Science and an RStudio Certified Instructor. She is passionate about developing R tools (especially choosing names for packages) and about creating innovative ways to teach computing to data scientists. Although her love for R is eternal and unwavering, she is currently begrudgingly allowing a little python into her heart.

The friendly competition between R and python has gifted us with two stellar packages for workflow-style predictive modeling: tidymodels in R, and scikit- learn in python. If you've ever wondered which one to use in classrooms and trainings, I say: ¿Porque no los dos? (Why not both?)

The first half of this talk will be focused on pedagogy and philosophy. I will compare and contrast the infrastructures of the two packages, primarily in the context of how they enforce or support conceptual understanding.

The second half will provide some practical insight and tips - and some helpful R functions - for running a class in a "bilingual" way, where students choose which language(s) to use on assignments.