8 Best Data Science Podcasts Recommended By Data Scientists
Working in AI/ML is a constant cycle of learning. Here are some of the best Data Science Podcasts that can help practitioners in their daily roles & career paths.
Working in AI/ML can often feel like a constant cycle of learning, the speed of innovation across the industry is only accelerating and it can be difficult to keep track. Fortunately for listeners, the episodic nature of podcasts means the shows and their conversations keep pace with the changing landscape, meaning if a topic or innovation becomes outdated there’s always new and exciting content on the way.
In this article, we highlight eight of the best data science podcasts that can help new and experienced practitioners in their day-to-day roles and also in their career paths. The recommendations provide insights into a range of topics from diversity and the role of women in the workplace to the application of machine learning in business. The shows and their conversations touch on different disciplines that play an integral role in the multi-specialist world of analytics. Each podcast offers something different.
Gradient Dissent Podcast
What the podcast is about: A deep dive into the minds of industry leaders helping to steer data and tech policy at the likes of some of the big tech players. The podcast explores how some of the brightest minds in the field take a hands-on approach to solving business problems with machine learning or developing products for data scientists and engineers.
Why you should listen: The podcast empowers leaders to discuss technical policy, its effects and their learnings through the prism of real-world projects and case studies across a range of industries from drug discovery and development to sustainable farming. With more than 60 episodes and a wide range of topics, everyone can find insightful episodes that share stories, tricks, and tips on how to run an analytics project and how to set up a technical environment.
Late Nights
What the podcast is about: Each episode features fresh ideas for creative design professionals, debates over best practices, industry secrets from experienced practitioners and interviews with leading analytics role models. The show covers topics from personal growth and development to how a designer should participate in a wider multidisciplinary team.
Why you should listen: This is a useful listen for designers early in their careers looking to develop skills and better understand what it means to be a design professional. The hosts’ candid conversations and personal anecdotes serve as inspiration on what to do — and perhaps more importantly, not to do — as a young designer. The focus on working as an integrated team offers great insight to any designer on how to maximise impact, whether you’re working in a start-up or global enterprise.
Women in Data Science
What the podcast is about: Every episode profiles a woman who has built a career in data science, sharing her experiences and what she learned along the way. Alongside these personal journeys, listeners are treated to anecdotal insight into how AI and machine learning is being applied across a range of sectors, from cosmology to human rights.
Why you should listen: For anyone working in data science, this podcast offers insightful conversations about the experiences of women working in the sector, including inspiring stories about how trailblazers built their careers and the challenges they faced along the way. The different stories offer unique insights into women’s lived experiences both in industry and academia, while providing a platform to hear about female role models and the creative projects they’ve worked on.
99% Invisible
What the podcast is about: From award-winning producer Roman Mars, this podcast dives into the everyday design of the world around us, focusing intently on the elements that often go unnoticed. Though frequently focusing on architecture, episodes delve into a range of other topics, from a great short series on fashion, to how Florence Nightingale pioneered data visualisation back in 1854.
Why you should listen: Regardless of what you’re designing — be it a building, a business, or a data platform — the practice of considering in detail how things are designed results in a highly enjoyable experience for the end-user. All analytics practitioners can benefit from thinking about the intent behind the design and the steps put in place to consider how an end product will be used — and which elements make it attractive to users.
Data Engineering Podcast
What the podcast is about: A more technical show, this podcast focuses predominantly on software tools and methodologies, with each episode providing a deep dive on a single topic. The show features a broad range of interviews from CTOs to engineers from a software vendor. Each guest speaks in-depth about their domain, the challenges they face and the solution they’ve built.
Why you should listen: The podcast covers a healthy mix of conceptual, classic, and emerging technologies and trends in data. It’s also well established, having recorded nearly 300 shows, and is, therefore, able to attract a range of guests that provide tremendous insight for new and experienced practitioners alike. Due to the pace of innovation, many of us try to learn a lot about a particular domain or topic in a short amount of time and this podcast is a great resource. The show frequently discusses new cutting-edge topics, meaning it’s a great source of emerging tools and trends in the data engineering space.
TWIML (This Week In Machine Learning) AI Podcast
What the podcast is about: The podcast is all about facilitating deep insightful discussions between industry-leading practitioners. It combines the top minds and ideas from the world of ML and AI with a broad and influential community of researchers, data scientists, engineers and tech-savvy business and IT leaders.
Why it’s relevant: A long-running podcast with over 500 episodes, TWIML has the credibility and name recognition to frequently attract high profile guests. The show features interviews with many of the leading minds in AI/ML such as Andrew Ng, Jeff Dean, Yoshua Bengio, and Ian Goodfellow. Conversations range from technical discussions that pique the interest of data engineers to more business-oriented interviews from C-Suite executives providing insight into the business case and the application of ML.
Software Engineering Daily
What the podcast is about: A technical show with a focus on software engineering that goes into significant depth in each episode. With daily uploads, this podcast provides a wealth of content, with a broad array of highly technical interviews any practitioner can learn from.
Why it’s relevant: The podcast features senior engineers who have helped build key technologies, explaining first-hand the details, challenges and unique solutions they created. The show has been publishing content consistently for five years and has a huge archive of both podcasts and written articles. It offers a unique perspective that combines the technical with the commercial, offering guests from practitioner level to C-suite, so it’s an excellent resource for anyone working in software engineering in an enterprise.
MLOps.community
What the podcast is about: Host Demetrios Brinkmann and colleagues conduct fireside conversations with leading thinkers and doers in the MLOps (Machine Learning Operations) space, from technical to product and VC.
Why you should listen: These often-informal conversations are an excellent introduction to the quickly-maturing field of MLOps, whether your interest lies in tooling, workflows or the start-up ecosystem. QuantumBlack’s own Ivan Danov has previously featured to discuss Kedro and its capacity to build data apps in the spirit of the 12-Factor App methodology, as well as advance the MLOps maturity of teams.
Anyone working in AI/ML knows that this industry brings together an array of specialisms, from data science to design and software engineering — so learning about new skills or insights is not just useful, it’s integral. Podcasts offer the opportunity for practitioners to dip into a rich library of knowledge resources and drink in as much insight as needed. The suggestions above are just a glimpse into the wonderful world of AI/ML, but we would like to hear from you. Please do leave your own suggestions in the comment section for top podcasts that offer value to anyone working in the field.
Authored by: Doug Cha, Senior Expert; Diana Montanes, Data Scientist; Barna Pásztor, Data Scientist; Hamza Oza, Designer; Daniel Firth, Data Scientist; Philip Pilgerstorfer, Data Scientist.
