Big Data

10 Must-Listen Data Science Podcasts for Every Enthusiast


In an era where data powers innovation, staying updated is paramount. Fortunately, data science podcasts have emerged as an engaging way to tap into the collective wisdom of experts. From beginners seeking a foothold to seasoned professionals aiming to stay ahead, these podcasts offer insights, anecdotes, and trends, all delivered through the power of voice.

Delve into our curated list of the top 10 data science podcasts, each catering to a specific audience and shedding light on the multifaceted world of data.

1. Data Skeptic

In the bustling realm of data science podcasts, “Data Skeptic” stands out as a guiding light for beginners & intermediate learners. This conversational and educational podcast takes on the task of demystifying intricate data science concepts in a relatable manner.

Data Skeptic
Source: Data Skeptic Podcast

Format: Conversational, Educational

“Data Skeptic” adopts a friendly, conversational tone that fosters engagement and understanding. The hosts expertly move through complex subjects, breaking them into manageable chunks without sacrificing depth. This format guarantees that listeners won’t be confused by technical jargon, making it the best option for those just entering the field of data science.

Target Audience: Beginners and Intermediate Learners

Catering to novices & learners at an intermediate level, “Data Skeptic” provides a solid foundation while delving deeper into advanced concepts. This dual approach ensures newcomers and those with some background can find value in each episode.

Content: Simplifying Complex Concepts

At the heart of “Data Skeptic” lies its mission to simplify complex data science topics. The podcast covers a broad spectrum from machine learning algorithms to artificial intelligence applications and the nuances of data ethics. The content is carefully curated to provide insights without overwhelming the listener, fostering a gradual learning curve.

Find this Data Science podcast on SpotifyApple Music, and YouTube.

2. Not So Standard Deviations

For data enthusiasts seeking a refreshing take on the world of data science, “Not So Standard Deviations” is a podcast that stands out. Hosted by the dynamic duo of Hilary Parker and Roger D. Peng, this podcast breaks away from the conventional by infusing data science discussions with humor and relatability.

Not so standard deviations

Format: Conversational, humorous

The podcast’s conversational style promotes friendship between hosts and listeners. Roger and Hilary, two prominent members of the data science community, contribute their knowledge while keeping a friendly demeanor. This enables even those without extensive subject knowledge to understand complex subjects.

Target Audience: Data scientists, statisticians

While the podcast’s primary audience is data scientists and statisticians, its appeal extends beyond those borders. The witty banter and lighthearted approach make it engaging for anyone interested in data-related fields. From dissecting data science challenges to delving into the nuances of data analysis and visualization, the podcast covers a wide spectrum of topics.


Moreover, “Not So Standard Deviations” isn’t just about the technical aspects; it also offers insights into career growth in the data science realm. The hosts share their personal experiences, providing valuable guidance for professionals navigating their careers.

Hilary and Roger manage to humanize data science in a field often associated with complexity. Their humor-infused conversations make learning enjoyable and provide a sense of community for data practitioners. Whether you’re a seasoned statistician or just dipping your toes into data, “Not So Standard Deviations” offers a unique blend of education and entertainment.

You can listen to this podcast on Spotify and YouTube.

3. Linear Digressions

“Linear Digressions” is a data science podcast that serves as an enlightening avenue for individuals passionate about data analysis and machine learning. Tailored for data science enthusiasts and analysts, the podcast adopts an educational and analytical format, delving deep into a spectrum of data-driven topics.

Linear Digressions | data science podcast
Source: Spotify


The educational podcast offers listeners a platform to comprehend intricate data science concepts. “Linear Digressions” deconstructs the complexity of data-related topics through systematic analysis and explanation, making them understandable to a larger audience. This analytical method enables listeners to comprehend theoretical foundations and the practical implications.

Target Audience: 

“Linear Digressions” is tailored to meet the needs of data science enthusiasts and analysts. The podcast offers content that bridges the gap between theoretical concepts and real-world scenarios, whether you’re an aspiring data scientist looking to broaden your knowledge or an analyst looking to improve your skill set. Both novices and seasoned professionals will find it to be a welcoming environment thanks to the hosts’ capacity to simplify complicated concepts.


The podcast’s content is multifaceted. It delves into the art of analysis, unraveling techniques that transform raw data into meaningful insights. Moreover, “Linear Digressions” probes into machine learning algorithms, demystifying their functionality and significance in the data science realm. The real-world applications of these concepts further ground the podcast’s insights in practicality, highlighting their relevance across industries.

This Data Science podcast is available on Apple Podcasts and Spotify.

4. The O’Reilly Data Show

A podcast called “The O’Reilly Data Show” connects data professionals with the rapidly changing fields of data science and artificial intelligence. This podcast, hosted by Ben Lorica, is a gold mine of business insights from in-depth interviews with top data scientists and AI authorities. The podcast, which focuses on interviews, provides a distinctive forum for listeners to learn firsthand from those at the forefront of data-driven innovation.

The O'Reilly Data Show
Source: Deezer


The interviews that make up “The O’Reilly Data Show” are its core component. The podcast offers a unique window into the most recent trends, difficulties, and advancements in data science and AI through open discussions with top experts. These interviews delve deeper than the surface, exploring the specifics of cutting-edge technologies, creative applications, and the success factors in this quickly evolving industry.

Target Audience: 

With a target audience comprising data professionals and AI practitioners, the podcast serves as a platform to connect listeners with thought leaders and experts in the field. Through engaging discussions, Ben Lorica engages with leading data scientists and AI experts, creating a space where listeners can access firsthand knowledge and perspectives.


The topics covered in this podcast are those that data professionals and AI practitioners care about most. Each episode features discussions that examine current trends and problems and highlight advancements in the industry. These insights give listeners a thorough understanding of the data science landscape, enabling them to make wise decisions and maintain their competitiveness in a world that is becoming more and more data-driven.

You can listen to this podcast on Apple Podcast and YouTube.

5.”Data Science at Home”

A podcast called “Data Science at Home” explores the complex and technical facets of the data science industry. This podcast, which Dr Francesco Gadaleta presents, delves deeply into machine learning algorithms, data preprocessing methods, and various AI-related topics. The podcast provides educational and technical content for data scientists and machine learning enthusiasts looking to advance their knowledge.

Data Science at Home
Source: Data Science at Home


The podcast has an educational focus and aims to give listeners a thorough understanding of how data science operates. Dr. Francesco Gadaleta assumes the role of an educator by decomposing complex ideas into manageable parts. Listeners can fully immerse themselves in the complexities of machine learning and data processing thanks to the content’s technical nature.

Target Audience: 

“Data Science at Home” serves as a primer for people who already have a basic understanding of the subject and are eager to explore its technical facets. This includes machine learning practitioners, enthusiasts, and data scientists who want to go beyond the basics in their knowledge.


The podcast’s subject matter spans a wide range of data science-related topics. Deep discussions on various machine learning algorithms, their uses, and the underlying mathematical ideas can be expected from listeners. The podcast also discusses data preprocessing methods, emphasizing their value in raising the standard and applicability of data analysis. Additionally, “Data Science at Home” goes beyond preprocessing and algorithms. The podcast delves into artificial intelligence-related topics, looking at how machine learning and AI interact. The listeners thoroughly understand how these fields are interconnected thanks to this holistic approach.

Find this Data Science podcast on Spotify and Apple Podcasts.

6. Data Science Imposters

The podcast “Data Science Imposters” emerges as a beacon of relatable experiences in the bustling realm of data science, where complexities intertwine with innovation. With its unique conversational and anecdotal format, the podcast aims to address a prevalent issue that affects both data professionals and beginners – the feeling of being an imposter in the field.

Data science imposters
Source: Data science imposters


“Data Science Imposters” uses a conversational tone that resonates with its audience, allowing for an open dialogue about common challenges encountered during the data science journey. The podcast fosters a sense of community among listeners through personal narratives and casual discussions. Hosts Renee Teate and Curtis Harris weave a tapestry of relatable anecdotes that unveil the highs and lows of navigating the world of data science.

Target Audience: 

The podcast’s inclusive nature caters to a wide spectrum of listeners. For data professionals, it offers a space to acknowledge and share the hurdles they’ve overcome, fostering a sense of unity within the community. Simultaneously, beginners find solace in the stories shared, realizing that challenges are an inherent part of growth in this dynamic field.


“Data Science Imposters” confronts the prevalent impostor syndrome head-on. Through stories of doubt, failure, and eventual triumph, the podcast debunks the misconception that success in data science comes without setbacks. By candidly discussing the roadblocks encountered, the hosts dismantle the notion of an effortless ascent in the field, providing a realistic portrayal of the data science journey.

You can listen to this podcast on Spotify and YouTube.

7. The SuperDataScience Podcast

“The SuperDataScience Podcast” offers a candid and relatable exploration of the challenges within the data science realm. Renee Teate and Curtis Harris host the podcast and take a conversational and anecdotal approach to connect with seasoned data professionals and newcomers to the field.

The SuperDataScience Podcast
Source: YouTube


The podcast adopts a conversational tone, fostering an open and relatable environment. Both hosts and guests share their journeys through personal anecdotes and stories, highlighting moments of doubt, challenges, and victories. This format resonates with listeners, creating a sense of camaraderie among data professionals who may often feel like “imposters” due to the field’s complex and rapidly evolving nature.

Target Audience: 

“Data Science Imposters” speaks to a dual audience. Data professionals find solace in the shared struggles of fellow experts, realizing that self-doubt and challenges are universal. The podcast serves as a reality check for beginners entering the data science realm, dispelling the notion that imposter syndrome is exclusive to them. The podcast encourages newcomers to persevere and continue learning by addressing these concerns.


The heart of the podcast lies in its content. Episodes feature authentic stories that expose misconceptions and demystify the seemingly unattainable pedestal of expertise. Misconceptions around “knowing it all” and unrealistic expectations are dismantled. The hosts candidly discuss challenges faced by data professionals, emphasizing that these challenges are not indicators of incompetence but stepping stones towards growth.

You can listen to their AI podcast on their website and YouTube!

8. Data Engineering Podcast

The “Data Engineering Podcast” stands as a beacon of knowledge and inspiration within the realm of data science. This podcast is a useful tool for both experienced data professionals and aspiring data scientists due to its insightful content and knowledgeable interviews.

Data Engineering Podcast
Source: Data Engineering Podcast


The structure of the podcast is intended to offer a wealth of knowledge and insights. Through informative discussions and in-depth conversations, listeners are given a comprehensive overview of the data science landscape. The podcast assists its audience in staying current with the most recent trends, technologies, and advancements in the industry by taking an educational stance.

Target Audience:

“The SuperDataScience Podcast” caters to a diverse audience, including seasoned data professionals and individuals who aspire to venture into the world of data science. The podcast provides a platform to delve deeper into complex ideas and market trends for those already working in the field. It offers a clear introduction to the vast field of data science for those unfamiliar with it.


The podcast’s captivating interviews with top figures in the field of data science are a particular strength. These interviews offer a special chance to hear from practitioners who have successfully handled the difficulties and victories of real-world data projects. The interviews offer a holistic view of the data science landscape, from discussing emerging trends to dissecting intricate methodologies.

This Data Science podcast is available on Apple Podcasts and Spotify.

9. DataFramed

“DataFramed” is a captivating podcast that bridges data science theory and its real-world applications. Hosted by the knowledgeable Hugo Bowne-Anderson, the podcast provides a conversational and educational platform that resonates with data scientists and analysts seeking to expand their insights and understanding.

DataFramed | data science podcast
Source: DataFramed


In a conversational tone, “DataFramed” adopts an educational approach that makes intricate data science concepts accessible to a broad audience. This format makes it equally appealing to both seasoned professionals and those new to the field. By presenting complex ideas in a relatable manner, Hugo Bowne-Anderson successfully breaks down barriers to entry for those who might find the subject daunting.

Target Audience:

The podcast is specifically for data scientists and analysts eager to learn more about the subject. “DataFramed” has something to offer everyone, whether seasoned professionals looking for new ideas or nascent enthusiasts trying to understand the nuances of data science.


At the core of “DataFramed” lies an exploration of data science stories, concepts, and applications across various industries. Through insightful discussions, Hugo delves into the practical relevance of data science in today’s world. Listeners are treated to enlightening conversations that shed light on how data-driven insights impact fields as diverse as healthcare, finance, marketing, and beyond. From understanding the role of machine learning in medical diagnoses to uncovering the mysteries of data visualization techniques, “DataFramed” consistently delivers valuable content that sparks curiosity and prompts deeper exploration.

Find this Data Science podcast on Spotify, Apple Podcasts, and YouTube.

10. Learning Machines 101

In the vast landscape of data science & AI, machine learning is a captivating field that fuels technological innovation across industries. For those seeking a comprehensive yet accessible understanding of machine learning, the podcast “Learning Machines 101” emerges as a beacon of knowledge. Tailored for both enthusiasts and beginners, this podcast is a valuable resource that demystifies the intricate world of machine learning.

learning machines 101 | data science podcast
Source: Audible


“Learning Machines 101” adopts an educational and informative format to break down complex concepts into digestible portions. Hosted by Richard M. Golden, a recognized authority in the field, each episode is designed to guide listeners through the multifaceted aspects of machine learning. The podcast’s engaging format ensures that even intricate ideas are presented clearly and understandably.

Target Audience: 

This podcast’s primary target audience comprises machine learning enthusiasts eager to delve deeper into the subject and beginners taking their initial steps into this dynamic field. “Learning Machines 101” offers something for everyone regardless of prior knowledge. The episodes are carefully structured to cater to a diverse range of listeners, from curious novices to those already familiar with the basics of machine learning.


At the heart of “Learning Machines 101” lies a treasure trove of content that covers fundamental concepts, theories, and real-world applications of machine learning. Richard M. Golden’s expertise shines as he navigates through topics such as neural networks, regression analysis, decision trees, and more. Each episode guides listeners through various machine-learning techniques’ theoretical underpinnings and practical significance.

This Data Science podcast is available on Apple Podcasts and Spotify.


In the ever-evolving realm of data science, staying informed and inspired is paramount. These 10 podcasts cater to a diverse range of data science enthusiasts, from beginners seeking foundational knowledge to experienced professionals aiming to stay updated. By delving into these podcasts, you can gain insights, knowledge, and a sense of community that will undoubtedly enrich your journey in data science.

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