Kyle Polich is the co-host of the incredibly popular Data Skeptic podcast, which he has been churning out since 2014. He studied computer science and focused on artificial intelligence in grad school. His general interests range from areas like statistics, machine learning, data viz, and optimization to data provenance, data governance, econometrics, and metrology.

 

The Data Skeptic Podcast features conversations on topics related to data science, statistics, machine learning, and artificial intelligence. The podcast breaks down into two different episode formats. One is a short form podcast where Kyle explains complex data science concepts in a way that non-data scientists can understand. In these episodes he's joined by his co-host and wife, Linh da Tran. The second format is a long form interview format where Kyle interviews experts in various data science and skepticism related arenas about their work.

 

In this episode of the Data Journeys Podcast, I pick Kyle's brain for patterns noticed and lessons learned through interviewing and teaching his way through nearly 400 episodes of the Data Skeptic Podcast. Some of the topics covered include:

 

1. How the Data Skeptic podcast became the only podcast to be endorsed by the Pope.
2. Kyle's approach to teaching complex subject matter for entry level comprehension.
3. What patterns and lessons Kyle has taken from interviewing nearly 400 guests on his show over the last four years.
4. Advice for listeners who are considering starting their own podcasts, colored by lessons Kyle has learned in his tenure.
5. Kyle and I get a little meta in trading lessons, best practices, and common experiences learned from their time hosting podcasts.

 

Enjoy the show!

 

Show Notes: https://ajgoldstein.com/podcast/ep20

AJ's Twitter: https://twitter.com/ajgoldstein393/

Kyle's LinkedIn: https://www.linkedin.com/in/kyle-polich-5047193