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James Blair: Part 1 — Portfolios, practice, and staying curious

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Manage episode 517632057 series 3678167
Content provided by Posit, PBC and PBC. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Posit, PBC and PBC or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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
  continue reading

9 episodes

Artwork
iconShare
 
Manage episode 517632057 series 3678167
Content provided by Posit, PBC and PBC. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Posit, PBC and PBC or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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
  continue reading

9 episodes

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