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There are several informative data science podcasts out there right now, giving you everything you need to stay up to date on what’s happening. We previously covered many of the best podcasts in this blog, but there are lots more that you should be checking out. Here are 10 more excellent podcasts to try out.
10 data science podcasts
10 Best Podcasts on Data Science You Must Listen To
1. Analytics Power Hour
Every week hosts, Michael Helbling, Tin Wilson, and Moe Kiss cover a different analytics topic that you may want to know about. The show was founded on the premise that the best discussions always happen at drinks after a conference or show.
Recent episodes have covered topics like analytics job interviews, data as a product, and owning vs. helping in analytics. There are a lot to learn here, so they’re well worth a listen.
2. DataFramed
This podcast is hosted by DataCamp, and in it, you’ll get interviews with some of the top leaders in data. “These interviews cover the entire range of data as an industry, looking at its past, present, and future. The guests are from both the industry and academia sides of the data spectrum too” says Graham Pierson, a tech writer at Ox Essays and UK Top Writers.
There are lots of episodes to dive into, such as ones on building talent strategy, what makes data training programs successful, and more.
3. Lex Fridman Podcast
If you want a bigger picture of data science, then listen to this show. The show doesn’t exclusively cover data science anymore, but there’s plenty here that will give you what you’re looking for.
You’ll find a broader view of data, covering how data fits in with our current worldview. There are interviews with data experts so you can get the best view of what’s happening in data right now.
4. The Artists of Data Science
This podcast is geared toward those who are looking to develop their career in data science. If you’re just starting, or are looking to move up the ladder, this is for you. There’s lots of highly useful info in the show that you can use to get ahead.
There are two types of episodes that the show releases. One is advice from experts, and the others are ‘happy hours, where you can send in your questions and get answers from professionals.
5. Not So Standard Deviations
This podcast comes from two experts in data science. Roger Peng is a professor of biostatistics at John Hopkins School of Public Health, and Hilary Parker is a data scientist at Stitch Fix. They cover all the latest industry news while bringing their own experience to the discussion.
Their recent episodes have covered subjects like QR codes, the basics of data science, and limited liability algorithms.
Released twice a month, this podcast will give you all the ins and outs of machine learning, showing you how this tech is used in real-life situations. That allows you to see how it’s being used to solve problems and create solutions that we couldn’t have before.
Recent episodes have covered high-stress scenarios, experience management, and autonomous checkouts.
7. In Machines We Trust
This is another podcast that covers machine learning. It describes itself as covering ‘the automation of everything, so if that’s something you’re interested in, you’ll want to make sure you tune in.
“You’ll get a sense of what machine learning is being used for right now, and how it impacts our daily lives,” says Yvonne Richards, a data science blogger at Paper Fellows and Boom Essays. The episodes are around 30 minutes long each, so it won’t take long to listen and get the latest info that you’re looking for.
8. More or Less
This podcast covers the topic of statistics through noticeably short episodes, usually 8 minutes or less each. You’ll get episodes that cover everything you could ever want to know about statistics and how they work.
For example, you can find out how many swimming pools of vaccines would be needed to give everyone a dose, see the one in two cancers claim debunked, and how data science has doubled life expectancy.
9. Data Engineering Podcast
This show is for anyone who’s a data engineer or is hoping to become one in the future. You’ll find lots of useful info in the podcast, including the techniques they use, and the difficulties they face.
Ensure you listen to this show if you want to learn more about your role, as you’ll pick up a lot of helpful tips.
10. Data viz Today
This show doesn’t need a lot of commitment from you, as they release 30-minute episodes monthly. The podcast covers data visualization, and how this helps to tell a story and get the most out of data no matter what industry you work in.
Share with us Exciting Data Science Podcasts
These are all great podcasts that you can check out to learn more about data science. If you want to know more, you can check out Data Science Dojo’s informative sessions on YouTube. If we missed any of your favorite podcasts, do share them with us in the comments!
These interviews cover the entire range of data as an industry, looking at its past, present, and future. The guests are from both the industry and academia sides of the data spectrum too, says Graham Pierson, a tech writer at Academized.
What can be a better way to spend your days listening to interesting bits about data science? Here's a list of the 18 best data science podcasts.
My commute to work every day is roughly one hour (+/- 15 minutes depending on the day). It’s safe to say I cruise through A LOT of podcasts. The subjects I listen to range from True Crime, NFL Fantasy Football, Major League Baseball, and Data Science.
This is my personal ranking/list of the best data science podcasts on SoundCloud, Apple Podcast, and Spotify. I found the descriptions of each podcast to be pretty true to what I would have written myself, which is why you won’t see a whole lot of my own writing in the descriptions (why reinvent the wheel?). Because most, but not all, are available on all three platforms, I decided not to rank the same podcast twice.
Have fun listening to the top 18 data science podcasts!
Data skeptic
“Data Skeptic is your source for a perspective of scientific skepticism on topics in statistics, machine learning, big data, artificial intelligence, and data science. Our weekly podcast and blog bring you stories and tutorials to help understand our data-driven world.”
277 Episodes
Data science ethics
This podcast focuses on “Discussing Model Behavior”. Everything you need to know is in the name. You’ll be taken through current and past events with insights on how we can make sure to remain ethical data scientists.
10 Episodes
Data science at home
In this podcast, host, Francesco Gadaleta, covers “technology, machine learning, and algorithms.”. He will break everything down so it feels like he is having a casual conversation with you. In a very podcast-like fashion, special guests will join to discuss their expertise.
35 Episodes
Data crunch
“If you want to learn how data science, artificial intelligence, machine learning, and deep learning are being used to change our world for the better, you’ve subscribed to the right podcast. We talk to entrepreneurs and experts about their experiences employing new technology—their approach, their successes, their failures, and the outcomes of their work. We make these difficult concepts accessible to a wide audience.”
43 Episodes
SuperDataScience
“(Host) Kirill Eremenko is a Data Science coach and lifestyle entrepreneur. The goal of the Super Data Science podcast is to bring you the most inspiring Data Scientists and Analysts from around the world to help you build a successful career in Data Science. Data is growing exponentially and so are the salaries of those who work in analytics.
This podcast can help you learn how to skyrocket your analytics career. Big Data, visualization, predictive modeling, forecasting, analysis, business processes, statistics, R, Python, SQL programming, tableau, machine learning, Hadoop, databases, data science MBAs, and all the analysis tools and skills that will help you better understand how to crush it in Data Science.”
253 Episodes
DATACAST
“Raw conversations with practitioners from the worlds of artificial intelligence, machine learning, statistics, and data science.”
18 Episodes
Data science imposters
“Explore data science, analytics, big data, and machine learning as we discuss these topics. Join us on our journey.”
50 Episodes
Women in data science
“Data science is improving outcomes in a wide range of domains, from healthcare to seismology to human rights and more. Hear from women leaders across the data science profession, as they share their advice, career highlights, and lessons learned along the way.”
10 Episodes
Linear digressions
“In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications.”
238 Episodes
Data futurology
“In Data Futurology, experienced Data Science Leaders from around the world tell us their stories, challenges, and lessons learned throughout their careers.
We also ask them:
What makes a great data scientist? What skills are required?
How do I become a great data science leader?
How should I grow and get the most out of my team?
What is a good data strategy? and how do I best implement it?
What are interesting applications of ML/AI that I should be considering in my industry?”
61 Episodes
Data science in production
“Data Science in Production is a podcast designed to help Data Scientists and Machine Learning Engineers get their models into production faster. We focus on the tools, techniques, and people of machine learning.”
6 Episodes
Cyentia podcast
“This podcast explores cybersecurity through use-inspired and data-driven research. Join hosts Jay and Wade as they discuss topics with those working to find incredible insights, tell awesome data-driven stories, and are willing to share their work with the larger community.”
16 Episodes
Best data science podcasts on SoundCloud
Talk Python to me
“Talk Python to Me is a weekly podcast hosted by Michael Kennedy. The show covers a wide array of Python topics as well as many related topics (e.g. MongoDB, AngularJS, DevOps). The format is a casual 30-minute conversation with industry experts.”
“Our methodology is simple: we draw from the wisdom of the alpha geeks in our midst, paying attention to what’s interesting to them, amplifying these weak signals, and seeing where they fit into the innovation ecology. Add to that the original research conducted by our Research team, and you start to get a good picture of what the technology world is thinking about.”
“AI has been described as ‘Thor’s Hammer’ and ‘the new electricity’. But it’s also a bit of a mystery – even to those who know it best. We’ll connect with some of the world’s leading AI experts to explain how it works, how it’s evolving, and how it intersects with every facet of human endeavor. This podcast is produced by NVIDIA, the AI computing company. Multiple episodes are released every month.”
“DataHack Radio is an exclusive podcast series from Analytics Vidhya that features Kunal Jain in conversation with the top data science and machine learning industry leaders and practitioners.”
“This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders.
These creators, builders, makers, and influencers value TWiML as an authentic, trusted, and insightful guide to all that’s interesting and important in the world of machine learning and AI. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning, and more.”
The best data science toolkit to help you succeed. Find leading blogs, podcasts, YouTube channels, project ideas, and numerous other data science resources in one place.
100s of 1000s of people are everyday planning to get started with their data science journey while most of them are actively & continuously looking out for data science resources & sites, to begin with. With tons of resources & sites available, one might wonder where to get the most useful & up-to-date data science material
And, if you are one of those, then you have landed on the correct page because I have curated a list of resources that have helped me a lot to learn data science & should probably help you out too.
Data science blogs
List of Data Science Blogs
Being a data scientist, you would want to stay updated with the recent happenings in data science, machine learning, and artificial intelligence. There are some quality blogs producing engaging and interesting content day in day out. These blogs can also be regarded as excellent data science resources.
1. KDnuggets
It has always been on the top of my list; they provide new blogs on data science, machine learning, artificial intelligence, and analytics on a routine basis. So, if you need a new data science blog frequently or on daily basis then KDnuggets is your option to go with.
With towards data science, you can clarify your data science, ML, and AI basics & fundamentals. Additionally, they provide a wide range of blogs on statistics & mathematics that can further aid your learning journey. Link to site: https://towardsdatascience.com/
4. Data Science Dojo
From big data to data analytics to statistics, Data Science Dojo is providing some useful blogs on several different areas of data science. Though, the blogs are limited in number but are highly recommended for all those who are just getting started with data science. Link to site: https://datasciencedojo.com/blog/
5. R Bloggers
Undoubtedly, you can find some most amazing blogs on R, Python, regression, and statistics here. Hence, if you are looking for clarity in any of the aforementioned areas, then R bloggers is your way to go. Link to site: https://www.r-bloggers.com/
PRO TIP: Join our data science bootcamp program today to enhance your data analysis skillset!
Data science communities
List of Data Science Communities
Online forums and communities can be a really interactive way of learning data science. With a number of enthusiasts all over the world, these online spaces can serve as a resource for staying on track and updated, being a valuable contribution to your data science toolkit.
1. Kaggle
One of the most useful online communities for data scientists & practitioners; with Kaggle you can learn some of the most essential Python, machine learning, and data science concepts.
Need help with mathematics? Then this mathematics forum can help you with it at any level. You can easily find answers to your math-related queries here.
There are a number of YouTube channels sharing the concepts of data science. You, obviously, will not be able to go through all the videos. Here are some of the best data science resources when it comes to YouTube.
1. Ken Jee
Following his channel can make it a lot easier for you to break into the field of data science. Ken Jee shares his own learning experience & makes some useful career-related suggestions.
Are you new to the field of data science? Then Data Science Dojo can help you with learning some of the most significant concepts of machine learning, artificial intelligence, Python programming, and R programming.
To get the know-how of how data science, machine learning, deep learning, and artificial intelligence work in a real-life scenario, follow his amazing tutorials & content.
Start learning programming in the easiest & untaught manner. So, if you are looking for a veracious channel to learn to program, then Code Basics is your channel to trust on.
For more Data Science related information, check out our other blog posts.
Data science podcasts
List of Data Science Podcasts
Podcasts are an excellent way of staying updated in the world of data science. I have listed a few useful data science podcasts on Sound-Cloud, Apple Podcast, and Spotify to help you learn and make the most out of your time.
1. Spotify
a. Data Skeptic
These podcasts from data skeptic will bring amazing tutorials on statistics, machine learning, big data, and data science. Start learning now with them.
With SuperDataScience you can boom your analytics career. It includes podcasts on statistics, R, Python, SQL programming, tableau, machine learning, Hadoop, databases, and other analytical tools.
The world of data science is not just about writing code and building models. Data science has a lot of influence, both directly and indirectly, on the entertainment industry. In fact, movies and tv shows can be used as one of the data science resources by aspiring scientists and engineers. When you need to freshen up or take a break from tough problems, these movies can be of great help.
1. Minority Report (2002)
An action-thriller directed by Steven Spielberg, starring Tom Cruise. We have generally seen data being used to infer new information, but here the data is being used to predict crime predisposition.
2. Interstellar (2014)
Christopher Nolan’s cinematic success won an Oscar for best visual effects and grossed over $677 million worldwide. The movie includes quadrilateral robots like TARS & CASE that are true examples of the that we have made within the AI domain.
3. The Imitation Game (2014)
The move is based on the real-life story of Alan Turing & also describes the process of creating the first-ever machine within the field of cybersecurity & cryptography.
4. The Queen’s Gambit (2020)
One of the most popular Netflix series, with over 62 million viewers, tells the story of Beth Harmon; a made-up chess star who beats all odds in life from being orphaned as a child to battling drug addiction & chess competitions.
Though the series is not really related to data science, but how Beth mentally plays the game by visualizing the chessboard on the ceiling is much like how an AI system works. For the past few years, AI researchers are trying to build a computer-generated bot version of Beth.
Top data science books
List of Top Data Science Books
Books are one of the best additions to any individual’s data science toolkit. There is an immense amount of literature out there, helping aspiring data scientists clarify some concepts and acquire valuable information.
1. An Introduction to Statistical Learning- With Applications in R
This book provides an overview of the field of statistical learning, which covers essential tools that can help in handling vast data sets varying from biology to marketing to finance.
2. The Hundred-Page Machine Learning Book
This book covers a wide range of topics in just 100 pages. Some of machine learning’s core concepts are explained here in just a few words.
3. The Cartoon Guide to Statistics
By using cartoons & humor, the author explains some of the essential statistical concepts that one might find difficult to comprehend. This book is highly recommended if you are just getting started with data science & statistics.
4. Forecasting- Principles & Practice
Making decisions based on the future forecasts is required at several instances, for example, whether to build up a new power plant in the next five years or not? Such decisions can only be based on forecasts. This book can assist you with understanding the basics & principles of forecasting.
Data science newsletters
List of Data Science Newsletters
Similar to blogs and podcasts, Newsletters can be a valuable addition to your data science toolkit. You’ll get curated articles at regular intervals to stay on top of things.
1. Mode Analytics
This collaborative platform combines SQL, Python, and R together in one place. You can subscribe to amazing data science-related newsletters with mode.
You can find curated articles here for data science news, jobs, and blogs for free. So, if you are looking for routine data science stuff, then data science weekly is your way to go with.
They provide a weekly newsletter on a wide array of topics including data, programming, AI, infrastructure, Ops, data science, and ML. With them, you are subscribing to blogs & articles that are relevant to you & your learning.
A weekly dose for you all the top data science picks, covering machine learning, data visualization, analytics, and strategy. Stay up to date in data science with them.
You can find 100-million-time series from UN, World Bank, Eurostat, and other important data providers, which can ultimately help you with visualizing world economies & societies.
3. Datacatalogs.org
It includes a comprehensive list of data portals from around the world i.e. Canada, United States, EU, and more.
LinkedIn can serve as another top data science resource, particularly if you’re looking to read short, engaging articles and get inspired by the stories of individuals. The pages listed below are worth following.
1. Machine Learning Mastery
You can find some useful machine learning articles & resources here that can help you to get started with applied ML. So, if you are into ML then Machine Learning Mastery is your place, to begin with.
2. Towards AI
With having 1800+ contributing writers from university professors to industry experts, they have a wide range of articles on tech, science, mathematics, engineering, and the future. If you are looking for some high-quality articles, then start scrolling through them.
3. Machine Learning India
Looking for useful infographics & PDFs? Then start following Machine Learning India because they have a ton of useful infographics, data science PDFs, and cheat sheets.
4. Data Science Dojo
Are you new to data science? Do you need daily content? Then I highly recommend you to start following Data Science Dojo. They share useful data science resources; be it an infographic, a cheat sheet, a blog, or a joke for humor. It doesn’t really matter if you are a beginner or an expert in the field, they have the right mix of content for everyone. Adding on, their weekly polls can help you test your data science skills, while their frequently held online webinars can help you with enhancing your knowledge.
5. Data Science Central
Similar to their blog, they have amazing data science articles on their LinkedIn profile as well. If you are a LinkedIn Freak, then you should start following their page now.
Data science free tools
List of Free Tools for Data Science
A data science toolkit devoid of tools and software is not really a toolkit, to be fair. There are some quality tools out there, including open-source software, that a data scientist can benefit from. Here are the best data science resources in the realm of software applications.
1. TensorFlow
It is a free & open-source software library for machine learning. TensorFlow is commonly used for neural networks, though, it can be used for a wide range of tasks.
It is used for the scientific computing of Python & R programming languages, which helps in package management & deployment. The distribution includes data science packages for Windows, Linux, and macOS.
This amazing product of google allows anyone to write & execute random Python code through the browser. Generally, it is a good fit for machine learning, data analysis, and education. Additionally, colab is a hosted Jupyter notebook that requires no setup & provides free access to computing resources.
The world of data science is nothing without practical experience and real-world projects. In your data science toolkit, therefore, you should have some quality projects. This will not only help you gain valuable experience but also strengthen your portfolio.
1. Beginner Level
a. Fake News Detection
If you are new to data science then this project can assist you to level up your data science career. Using Python, you can detect false & misleading news across social media & online channels.
b. Forest Fire Prediction
Using K-means clustering one can identify the hotspots of forest fires & severity, which can help in lessening & controlling the ecosystem damage.
c. Twitter Sentiment Analysis
One of the widely used text mining techniques, this project includes sentiment analysis of the text (tweets) in form of positive, negative, and neutral.
2. Intermediate Level
a. Recognition of Speech Emotion
Willing to learn on the usage of different libraries? Then you must go with this project idea. With different editor tools, you can tell how the speech emotion is appearing. This program model can be built as a data science project.
b. Gender & Age Detection with Data Science
This type of real-time project can help you grab the recruiter’s attention during an interview. Additionally, with this project, you can also learn convolutional neural networks.
c. Chatbots
One of the highly demanded & crucial elements for all businesses these days. Thereby, working on this data science project can help you uplift your career.
3. Advance-level
a. Credit Card Fraud Detection
Once you are through practicing the beginner & intermediate level of projects, you can move to this level. With the Credit Card Fraud Detection project, you can learn about how to use R with different algorithms like decision trees & logistic regression.
b. Traffic Sign Recognition
The purpose of this project is to achieve a higher level of accuracy in self-driving car technologies using CNN techniques, which can help in identifying different types of traffic signals by the input of an image.
c. Customer Segmentations
One of the most popular & important data science projects that can help marketers to reach the targeted & relevant group of people via marketing activities. Methods of clustering can play a vital role here that can assist in dividing the audience within age brackets, income, gender, and interest.
Whether you are a beginner or an expert in the field of data science, this comprehensive data science toolkit can be your ultimate support at all career levels. Bookmark this post for future assistance & use.
