Find your next data science listen from this list of current podcasts.
There's a data science podcast for almost every goal, from building up your data science vocabulary and keeping up with the latest developments in the field, to learning new data skills and getting advice on landing your first data science job.
Listening to some of these 17 podcasts can be a great way to improve yourself as a data professional, whether you’re just starting out or are already a seasoned pro. The best part? You can squeeze in some listening when you’re cleaning the house, grocery shopping, exercising, or otherwise on the go.
We’ve divided this list into a few broad categories to make it easier for you to find what you’re looking for.
Read more: What Is a Data Scientist? Salary, Skills, and How to Become One
Whether your interest in data science is academic or professional, these podcasts offer a broad, high-level overview of a range of data topics. This is a good place to start if you’re new to data science or if you want a little of everything in your podcast listening.
Episode duration: About an hour
Frequency: Biweekly
The premise of this podcast is that the best, most informative discussions happen around drinks after an event, like a conference or show. Co-hosts Michael Helbling, Tim Wilson, and Moe Kiss share their thoughts on a different data topic each week, from the psychology of data analytics to making statistics more accessible.
Recommended episode: The Curiosity of the Analyst with Dr. Debbie Berebichez
Episode duration: 30 to 40 minutes
Frequency: Weekly
This popular data science podcast, hosted by Kyle Polich, covers a wide range of topics, including machine learning and artificial intelligence, and statistics. The library of more than 370 episodes alternates between mini episodes that cover high-level topics and longer, more in-depth interviews with practicing data scientists as expert guests.
Recommended episode: Data Science Hiring Processes
Episode duration: 45 minutes to an hour
Frequency: Weekly
In this podcast from DataCamp, host Adel Nehme interviews data leaders working in both industry and academia about all things data science—its past, present, and future, as well as the types of problems data science can solve. Older episodes were hosted by data scientist and writer Hugo Bowne-Anderson.
Recommended episode: The Past and Present of Data Science (with Sergey Fogelson)
Episode duration: 30 to 40 minutes
Frequency: Monthly
Professor Margot Gerritsen from Stanford University and Chisoo Lyons with Women in Data Science Worldwide host a series of conversations with other leading women in the data science field. Listening gives you an overview of how data science is applied across a range of industries, from music streaming to health care, along with career advice and commentary on the role of women in this field.
Recommended episode: Lillian Carrasquillo | Using Human-Centric Data Science at Spotify
Episode duration: Two to five hours
Frequency: Varies
This podcast, once called “The AI Podcast”, is no longer all about data science, but it does offer a broader perspective of data science and how it fits into the bigger picture of philosophy, history, health, and technology. Lex Fridman interviews luminaries from various industries—figures like Elon Musk (CEO of Tesla), Vitalik Buterin (co-founder of Ethereal), and Saagar Enjeti (political correspondent).
Recommended episode: Elon Musk: Neuralink, AI, Autopilot, and the Pale Blue Dot
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If you’re thinking about starting a career as a data analyst or data scientist, or if you’re working toward advancing in your current role, these podcasts are for you. While they don't all focus exclusively on job tips, they do lean toward the pragmatic.
Episode duration: Five minutes (mini episodes) to an hour (full episodes)
Frequency: Twice weekly
This lighthearted podcast features conversations around the tools, techniques, and data-driven processes involved in real-world data science. Learn more about the history of data, knowledge graphs, or time series analysis, or get job ready with episodes focused on resume tips and myths about pursuing a data science career.
Recommended episode: How to Thrive as an Early-Career Data Scientist
Episode duration: 30 to 45 minutes
Frequency: Weekly
Data science executive Felipe Flores hosts this podcast, where he interviews some of the world’s leading data practitioners. While the show focuses on the leadership side of artificial intelligence (AI), the content often includes useful bits of advice for how to get started—and excel—in the wide world of data.
Recommended episode: Machine Learning: Getting the Skills Needed to Work as a Data Scientist or Machine Learning Engineer with Alexey Grigorev
Episode duration: An hour to 90 minutes
Frequency: Weekly (or more)
This podcast focuses exclusively on self-development for data scientists. Each episode comes full of advice on how to develop professionally, stay informed, and practice good data ethics. Episodes are divided between interviews and “happy hours” where listeners can ask questions on anything related to data science.
Recommended episode: Your Job Doesn't Define YOU | Eleanor Tweddell
No matter where you are in your data science career, it’s always a good idea to stay current with the latest in data and how it’s impacting the world. Subscribe to these podcasts to stay in the know.
Episode duration: 20 minutes to an hour+
Frequency: Two to three per month
Roger Peng (professor of biostatistics at Johns Hopkins Bloomberg School of Public Health) and Hilary Parker (data scientist at Stitch Fix) co-host this discussion of industry news that weaves in their own personal experiences working with data.
Recommended episode: Data Gunslingers
It’s hard to talk about data science without some mention of machine learning and AI. If you’d like to learn more about these critical fields of data science, take a listen to one of these podcasts.
Episode duration: 20 to 40 minutes
Frequency: Once or twice a week
In Data Science at Home, Dr. Francesco Gadaleta discusses topics in machine learning, artificial intelligence, and algorithms and interviews top minds in the field of AI. Past episodes have covered how to work with unbalanced data, what true machine intelligence might look like, and why we don’t get paid for our data, even though it’s worth thousands of dollars each year.
Recommended episode: True Machine Intelligence just like the human brain
Episode duration: 45 minutes to an hour
Frequency: Twice weekly
During this podcast, formerly This Week in Machine Learning & Artificial Intelligence, analyst Sam Charrington interviews researchers, data scientists, engineers, and IT leaders on a broad range of topics related to machine learning and AI. Learn more about the latest in autonomous driving, haptic intelligence, and how AI might be used to map the human immune system.
Recommended episode: Machine Learning for Equitable Healthcare Outcomes with Irene Chen
Episode duration: 45 minutes to an hour
Frequency: Twice monthly
This machine learning podcast gives a behind-the-scenes look at how leaders across a variety of industries are using machine and deep learning models to solve real-world problems. Guests on the show have included Wojciech Zaremba (co-founder of OpenAI), Sean Taylor (data scientist at Lyft), and Chris Mattmann (Chief Technology and Innovation Officer at the NASA Jet Propulsion Laboratory).
Recommended episode: Alyssa Simpson Rochwerger on responsible machine learning in the real world
Episode duration: 20 to 30 minutes
Frequency: Biweekly
When it was active, this show billed itself as “a podcast about the automation of everything,” and it examined the impact of AI on our daily lives. Jennifer Strong with the MIT Technology Review guided listeners through discussions on the ways we entrust technology with some of our most sensitive decisions.
Although you can still listen to episodes of this podcast, Jennifer Strong now runs a new podcast called SHIFT.
Recommended episode: Hired by an algorithm
Podcasts are a great way to take a deep dive into a particular topic in the data world, whether to learn a new skill or pick up some tips on a data task you perform regularly. Each of these podcasts focuses on a specific element of data science.
Episode duration: 8 to 30 minutes
Frequency: Weekly
This podcast from Tim Harford and the BBC helps make sense of statistics through short and snappy episodes. Topics are wide ranging—everything from how data has helped to double life expectancy to calculating how many swimming pools of vaccine we’ll need to give everyone on the planet a dose.
Recommended episode: Delta cases, blue tits and that one-in-two cancer claim
Episode duration: An hour to 75 minutes
Frequency: Weekly
Python’s versatility as a programming language is on full display in this podcast, which has already recorded more than 320 episodes about Python and related technologies. The show, hosted by Michael Kennedy, splits its time between how Python is applied by data scientists, software developers, and even the casual hobbyist.
Recommended episode: Python for Astronomy with Dr. Becky
Episode duration: 40 minutes to an hour
Frequency: Twice weekly
If you’re interested in the specialized role of data engineer, this podcast is for you. The show focuses on the tools and techniques associated with data engineering, as well as the difficulties engineers might face when managing workflow, automation, and data manipulation. This one’s full of insightful advice.
Recommended episode: Moving Machine Learning Into The Data Pipeline at Cherre
Episode duration: 30 minutes to an hour
Frequency: Monthly
Data is at its most powerful when it tells a compelling story, and visualizations can help achieve that end. In this podcast, data visualization designer Alli Torban shares the latest methods and tools through her own work and interviews with other top data designers.
Recommended episode: How to Turn Data Into an Experience
These podcasts are no longer (or infrequently) producing episodes, but as industry favorites, we thought they were still worth mentioning. If you’re looking for your next data science listen, go ahead and dig into the archives of these longstanding favorites.
5. Data Stories
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