In this talk, I will outline a unified philosophy of data science education, and provide tips and tools for implementing these principles in the classroom using R and RStudio. Although data science as a professional discipline is well-established, its pedagogy is still in a period of growth. Even within a single university, multiple data science courses may be offered across different departments leading to inevitable redundancy of efforts amidst rich domain-specific innovations. My experience as an instructor in many such courses has lead me to five principles that transcend domain, context, and choice of language: reproducibility, communication, version control, practical application, and data ethics. For each of these full-stack themes, I will share examples of how to leverage tools in R and RStudio to enhance learning.
A 5-minute presentation in our Lightning Talks series
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