Data Science Podcast Reviews

23 May 2020 -

When I decided to teach myself data science about six weeks ago, I thought that listening to podcasts would be a helpful way to learn more about what I needed to learn. I didn’t think that I would learn the techniques I needed through listening to a podcast while on a walk; but, I thought that it would help me build up a set of concepts and approaches that I would need to learn. That turned out to be the case. But what helped most was that I gained a lot of confidence along the way. Here are my thoughts on the three main podcasts that I listened to.

Towards Data Science

This is where I started and I listened to an episode a day until I ran out of new episodes. At first, I found myself adding to my to-learn lists based on the concepts I was hearing about. But after about a dozen episodes, the additions to the list got more rare and I found myself focusing more on the process of doing data science and the consistent message I was hearing from practitioners about the importance of people skills, domain expertise, and explainability. I’m hoping that my experience as an educator and principal has given me a strong foundation in those areas.

Overall, I really appreciate the interviewing approach at TDS. The interviewers remind me of Marc Maron as they share a lot of their own insights and push more towards a conversation than an interview. There were a handful of interviews by a different guy that I didn’t like as much because it lacked this back and forth and sounded as if he had sent a recording of his questions to the guest and had them send back their responses as recordings. I’m glad they went back to the original format after only five episodes or so.

Chai Time Data Science

I appreciate this podcast for its focus on guest diversity. While the host has on several occasions lamented about a lack of women on the podcast, he seems to be actively seeking out a variety of contributors and he’s been asking for feedback along the way. He also does subtitles for each episode for non-native English speakers and has lots of guests that are still in the early stages of their process of learning. All that together makes it feel like I’m listening to guests that are only a few months or years ahead of me in their process and a better representation of everyone trying to learn data science. This is comforting and makes the listening process more enjoyable.

Adversarial Learning

If Towards Data Science is the WTF/Marc Maron of data science podcasts, Adversarial Learning is the Howard Stern. And if you are into hosts that make the episodes more about showing off how funny they think they are or how interesting their opinions are, then this is the podcast for you. I decided to try three episodes before giving up because I thought I might have just gotten unlucky with my first episode. After they essentially created a tech bro culture within the episode with a Twitter data science manager/DJ, I built up a little hope with my next episode. But, then on the third they spent an episode giving bland opinions about education just to make fun of Neil Degrasse Tyson for expressing the same opinions but in a slightly more vague way. Finishing that episode by sharing an outdated perception of the AP US History exam showed how poorly informed their opinions were in the first place.