The Five Principles of Data Science Education

on YouTube ↗05m

" summary

Argues five core principles that should appear across courses: reproducibility, communication, version control, practical application, and data ethics. Recommends R and RStudio tooling—R Markdown and Shiny for explainable outputs, built‑in git integration for tracking changes, student‑built R packages and client practicum projects that produce deployable artifacts—and reports these practices produce runnable, parameterized pipelines and clearer handoffs rather than buried analysis.

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" chapters (8)

1. 0:00Intro
2. 1:04Data Science Education
3. 1:55What are you looking for
4. 2:42Communication
5. 3:37Resilience
6. 4:13Practicum
7. 4:40Data Ethics
8. 5:03Outro

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