During one of the recent data science hangouts a question was raised about attendees’ favorite data science podcasts. It was interesting to see all the recommendations coming in, so many poscasts out there! After a quick online search I found two posts that list their podcasts recommendations. One published on Towards Data Science, the other is on Medium. Both list excellent recommendations, but neither mentions the podcasts I listen to or have learned about during the data science hangout. So here’s a list of additional great data science podcasts.
Hosted by Libby Heeran, the podcasts focuses on versatile meaning of data science professionally and the people behind those titles. Each episode is an interview with a data professional about their background, their introduction to the data science world, their views and perspectives on the field, and their approach to their jobs. The discussions are always deep and rich.
While writing this I discovered that Libby had created a list data science hangout book recommendations, which is incredibly amazing!
Hosted by David Keyes. The podcast focuses on R uses beyond statistical analysis. His guests are often (but not exclusively) from professional backgrounds far from any field that uses coding as a primary skill but have learned R and used it in creative ways. What I like most about this podcast is that the episodes are concise and relatively short. Each episode is a nice balance between their personal story with R and their work and contribution to the community.
Founded and hosted by Kyle Polich. Though it’s not particularly focused on R or coding, the podcast is a comprehensive source for data science, artificial intelligence, machine learning, and statistical analysis. Each season dives deep into a certain topic with engaging experts in the season’s respective field. I love Kyle’s innovative ways of explaining concepts and I love how the show is a one stop shop for all concepts and technologies in the data science world.
Each episode, Jon Krohn, interviews a professional in the field. Each episode is a fascinating and engaging conversation about a specific topic, and the data science world is rich with interesting topics!
This podcast is a weekly summary of R resources for R issues. What’s unique about this podcast is that it’s a collaborative community project.
This podcast is hosted by three analytics professionals. Each episode discusses a specific topic and usually hosts a guest or several guests. Though it’s not a coding specific podcast and it rather focuses on business analytics, the topics are relevant to anyone working in industry at any analytics capacity. One of my favorite episodes is the one where they discuss impostor syndrome, which I listened to twice and has helped me gain new tools to deal with impostor syndrome and has given me a boost of confidence when I needed it.
“A podcast about all things data”. This podcast focuses on data and the data science industry as a whole. Each episode is an intriguing and critical discussion about an industry related hot topic with an industry expert guest.
Another podcast on all things data and data science. This one is from datacamp, the coding learning platform. In the podcast the hosts share industry discussions with guest data professionals, best practices, use cases, insights, and overall how the data and technology is changing the world around us.
Build a Career in Data Science
This podcast was one of the most valuable resources for me when I was making my way into the data science world. The podcast is a compliment to the book with the same title where each episode is a discussion a deeper dive into a chapter of the book. Both the book and the podcast are a guide to navigating and understanding the data science industry, largely based on the experiences of the authors and hosts Emily Robinson and Jaqueline Nolis and their interviews with other professionals in the field. It’s like having two mentors guiding an early-career data professional. The podcast and book were also on Oscar Baruffa’s DIY mentorship guide.