James Blair: Part 1 — Portfolios, practice, and staying curious
In Part 1 of our conversation with James Blair, we trace his delightfully non-linear path from childhood robotics dreams to journalism to R, with a few stops in between. We hear about the Shiny app that changed his career, plus a candid roundtable with Michael, Hadley, and Wes about whether a data-science master’s still pays off in the age of AI. Episode notes This is a story about staying hands-on and fiercely inquisitive — whether analyzing bike telemetry or in teaching data science. James shares how early experimentation with Shiny helped shape his career, and how curiosity (not credentials) still powers meaningful work in data science. What’s inside A winding path from robotics to journalism to psychology to data science Discovering the power of applied stats The value (and limits) of a data-science master’s in a shifting AI landscape Fighting confirmation bias: good analysis resists the answer you want