17 Data Science Podcasts to Listen to in 2025
Listening to a data science podcast can help you explore new topics, hear the latest insights, and find inspiration about the field. Discover your next favourite data science podcast with this curated list of top recommendations.
![[Featured Image] A person stands outside a building holding a to-go coffee and listening to a podcast on his phone.](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://images.ctfassets.net/wp1lcwdav1p1/2TzjKsVJYNiuylHrNiWRlx/9b0e024e30bcb71cb9f8af8889b595a8/iStock-1210526452.jpg?w=1500&h=680&q=60&fit=fill&f=faces&fm=jpg&fl=progressive&auto=format%2Ccompress&dpr=1&w=1000)
You can find a data science podcast for almost every goal, from expanding your data science vocabulary to staying up-to-date with the latest developments in the field and mastering new technical skills or seeking advice on how to land 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 working in the field. Even better, you can listen while you're cleaning the house, commuting to work, or going for a walk.
Explore the following data science podcasts, conveniently divided into a few broad categories.
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Average time: 5 month(s)
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Podcasts to get an overview of data science
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.
1. Analytics Power Hour
Episode duration: About an hour
Frequency: Biweekly
The premise of this podcast is that the best, most informative discussions often happen during informal conversations after an event. To bring the insights from these types of discussions to the public, this podcast has a ‘happy hour’ style feel to it, with friends sharing insights, questions, and current happenings. Co-hosts Michael Helbling, Tim Wilson, Moe Kiss, July Hoyer, and Vall Kroll—and often a guest—share their thoughts on a different data topic each week, from the psychology of data analytics to making statistics more accessible.
Recommended episode: Professional Development, Analytically Speaking with Helen Crossly
2. Data Skeptic
Episode duration: 20 to 40 minutes
Frequency: Weekly
This popular data science podcast, hosted by Kyle Polich, covers a wide range of topics, including machine learning, artificial intelligence, adtech, natural language processing, statistics, and more. The library includes hundreds of episodes that take a variety of formats from covering high-level topics to hosting longer, more in-depth interviews with practising data scientists as expert guests.
Recommended episode: Computing Toolbox
3. DataFramed
Episode duration: 40 minutes to an hour
Frequency: Weekly
In this podcast from DataCamp, hosts Adel Nehme and Richie Cotton interview 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: High Performance Generative AI Applications with Ram Sriharsha, CTO at Pinecone
4. Women in Data Science Worldwide
Episode duration: 30 to 40 minutes
Frequency: Monthly to every 2 months
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 environmental issues to health care, along with career advice and commentary on the role of women in this field.
Recommended episode: Beyond Borders: Elevating Women in Data Science and Leadership
5. Lex Fridman Podcast
Episode duration: Two to five hours
Frequency: Varies, two to four episodes per month
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 is an AI researcher at the Massachusetts Institute of Technology (MIT) who interviews luminaries from various industries—figures like Elon Musk (CEO of Tesla), Andrew Huberman (Stanford researcher and podcast host), and Sam Altman (CEO of OpenAI).
Recommended episode: Elon Musk: SpaceX, Mars, Tesla Autopilot, Self-Driving, Robotics, and AI
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Average time: 5 month(s)
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Podcasts for career advice
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.
6. SuperDataScience: AI & ML Podcast with Jon Krohn
Episode duration: Up to an hour
Frequency: Twice weekly
This lighthearted podcast, hosted by Dr. Jon Krohn, features conversations around the tools, techniques, and data-driven processes involved in real-world data science. Learn more about the history of data, consider current industry trends, explore how to integrate AI into your business, or get job ready with episodes focused on resume tips and myths about pursuing a data science career.
Recommended episode: How to Thrive in Your (Data Science) Career, with Daliana Liu
7. Data Futurology
Episode duration: 30 to 45 minutes
Frequency: Not currently bringing new episodes
While not currently producing new episodes, this podcast has a library of 266 episodes you can explore around artificial intelligence, how to be a leader in this field, and how to use this technology to your advantage. 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 world of data.
Recommended episode: Machine Learning: Getting the Skills Needed to Work as a Data Scientist or Machine Learning Engineer with Alexey Grigorev
8. Plumbers of Data Science
Episode duration: 20 to 40 minutes
Frequency: Weekly (or more)
This podcast focuses on a range of data engineering topics, including practical processes like data cleaning and essential softwares to learn, alongside career tips like how to find the best learning method for you, how to launch your career, and how to build a personal brand in data science.
Recommended episode: Bootcamps vs Coaching
Podcasts for data science news and trends
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.
9. Not So Standard Deviations
Episode duration: 45 minutes to an hour
Frequency: Varies
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: LLMs and Data Science
Podcasts about machine learning and AI
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.
10. Data Science at Home
Episode duration: 20 to 50 minutes
Frequency: Varies
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, challenges you might run into when protecting data, and why we don’t get paid for our data, even though it’s worth thousands of dollars each year.
Recommended episode: AI: The Bubble That Might Pop—What’s Next?
11. The TWIML AI Podcast
Episode duration: 45 minutes to an hour
Frequency: 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, animal behaviour models, autonomous decision processes, and what might be next in the field of AI.
Recommended episode: Supercharging Developer Productivity with ChatGPT and Claude with Simon Willison
12. Gradient Dissent
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), Clara Shih (CEO of Salesforce AI), and Chris Mattmann (Chief Technology and Innovation Officer at the NASA Jet Propulsion Laboratory).
Recommended episode: Transforming Data into Business Solutions with Salesforce AI CEO, Clara Shih
13. SHIFT
Episode duration: 15 to 30 minutes
Frequency: Weekly
Hosted by Jennifer Strong, this podcast explores how AI is rapidly changing our everyday lives and discusses hot topics related to what the future in this space might hold. You can learn about the history of AI, explore modern devices and how they operate, and listen to thought-provoking interviews with scientists at the forefront of this industry.
Recommended episode: What Makes Us Unique in the Age of AI?
Podcasts on specific data topics
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.
14. More or Less: Behind the Stats
Episode duration: 8 to 30 minutes
Frequency: Twice 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: Do 85% of the world's population practice a religion?
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15. Talk Python to Me
Episode duration: 30 minutes to an hour or more
Frequency: Varies, 2 to 5 episodes per month
Python’s versatility as a programming language is on full display in this podcast, which has already recorded more than 470 episodes about Python and related technologies. The show, hosted by Michael Kennedy, splits its time between several types of topics, including how Python is applied by data science professionals, different packages and processes to explore, and recaps of big events in the space.
Recommended episode: Awesome Text Tricks with NLP and spaCy
16. The Data Engineering Podcast
Episode duration: 40 minutes to an hour
Frequency: Varies, one to four episodes per month
If you’re interested in the specialised 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: How Generative AI is Impacting Data Engineering Teams
17. Data Viz Today
Episode duration: 20 minutes to an hour
Frequency: Varies, typically monthly
Data is at its most powerful when it tells a compelling story, and visualisations can help achieve that end. In this podcast, data visualisation designer Alli Torban shares the latest methods and tools through her own work and interviews with other top data designers. While you won’t find new episodes for June to September 2024, this podcast has nearly 100 episodes to explore with exciting insights about creativity, data, and how the two work together.
Recommended episode: How to Turn Data Into an Experience
Archived podcasts: Gone but not forgotten
These podcasts are no longer (or infrequently) producing episodes, but as industry favourites, 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 favourites.
5. Data Stories
Get started in data science
Listening to a data science podcast can be a fun way to become more involved in the data science field. Whether listening to expert opinions, learning new topics, or gaining career advice, you can find a data science podcast suited for your interests to help you expand your expertise.
Translate your interest in data into a career with the Google Data Analytics or IBM Data Science Professional Certificate on Coursera. With either programme, you can learn the job-ready skills you need from industry-leading companies in less than six months. Get started for free.
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Meta Data Analyst
Launch your career in data analytics. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from Meta in 5 months or less. No degree or prior experience required.
4.7
Beginner level
Average time: 5 month(s)
Learn at your own pace
Skills you'll build:
SQL, Pandas, Generative AI in Data Analytics, Data Analysis, Python Programming, Marketing, Data Management, Data Visualization, Linear Regression, Statistical Analysis, Statistical Hypothesis Testing, Spreadsheet, Tableau Software
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Get on the fast track to a career in Data Analytics. In this certificate program, you’ll learn in-demand skills, and get AI training from Google experts. Learn at your own pace, no degree or experience required.
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Beginner level
Average time: 6 month(s)
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Data Analysis, Creating case studies, Data Visualization, Data Cleansing, Developing a portfolio, Data Collection, Spreadsheet, Metadata, SQL, Data Ethics, Data Aggregation, Data Calculations, R Markdown, R Programming, Rstudio, Tableau Software, Presentation, Data Integrity, Sample Size Determination, Decision-Making, Problem Solving, Questioning
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IBM Data Science
Prepare for a career as a data scientist. Develop in-demand skills and hands-on experience to get job-ready in as little as 5 months. No prior experience required.
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Beginner level
Average time: 5 month(s)
Learn at your own pace
Skills you'll build:
Data Science, Big Data, Python Programming, Github, Machine Learning, Deep Learning, Methodology, SQL, Rstudio, Data Mining, Jupyter notebooks, Model Selection, Data Analysis, Data Visualization, Predictive Modelling, Numpy, Pandas, Dashboards and Charts, dash, Matplotlib, Cloud Databases, Relational Database Management System (RDBMS), Clustering, regression, classification, SciPy and scikit-learn, CRISP-DM, Jupyter Notebook, K-Means Clustering, Data Science Methodology
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