With Big Data soaring in popularity as a strategic tool for business, companies of all sizes are looking for employees with data science skills. The result is an increased demand for courses that equip one with Big Data knowledge and skill set.
There are a lot of internet resources that can come to your rescue if you want to acquire data science skill set without spending much time or money. Several online courses, books, blogs and social media accounts are dedicated to Big Data in a broad sense. They discuss big data not only in a business context but also mentioning its health, science or real-life applications.
This time we throw light on Big Data podcasts to provide you with easily digestible resources. Whether you commute and want to set your mind on something creative instead of procrastinating, or you are intentionally looking for informative content to boost your knowledge, we give you the best Big Data podcasts. You might be a total beginner or a business intelligence pro, you’ll find here some podcasts that will help you grow in your field and understand it better. Thanks to that knowledge, you can exploit the potential of analytics to identify new business opportunities, sharpen your business intelligence strategy, or create and customize professional dashboards.
Start your journey of expanding your skills for a minimal cost today.
The Best Big Data Podcasts To Sharpen Your Data Science Knowledge
Udacity offers interactive online courses that seek to empower students on their way to becoming Web Developers, Data Analysts, Mobile Developers, Machine Learning Engineers etc. They boast courses developed in cooperation with industry leaders (Google, Facebook, Salesforce, Cloudera, etc.) and offer Nanodegree programs with credentials, designed to bridge the gap between academia and real-life business needs.
Udacity courses are highly interactive with activities, such as quizzes and exercises, interspersed between short videos and interviews with instructors and industry experts. Courses also include a project that you can add to your portfolio. Whether it is a blog, search engine, game or app, Udacity leaves you with a tangible proof to demonstrate what you have learned.
Make sure to check out: the free Intro to Descriptive Statistics course. This beginner friendly course will teach you the basic concepts and ideas you need to understand in order to describe data. Think of this as your “Data Science 101” course.
2. IBM Big Data & Analytics Hub
IBM Analytics Insights podcasts are available for free via iTunes and provide insightful content on big data, analytics, visualizations and their implications for the enterprise, delivered by a range of experts spanning multiple industries. These podcasts break down complicated concepts into clear and concise definitions. The hosts also feature various experts in every episode, which gives listeners a wide range of opinions and views on the subject matter.
To be fair, this series may not be the best starting point for beginners. This big data podcast can often be quite technical, as the guests are some well known people who assume that you know the underlying terminology of big data quite well. However, if you want to hear from some of the top players who are in the trenches of big data as it relates to business, you’re in the right place.
In short, if you’re a big data veteran who wants to dive deep into what the “big players” are talking about, this is the series for you. However, if you’re newer to the game, there’s a lot to be said for diving straight into the deep end with a series like this one. All this knowledge comes in a snackable package of 15 minutes long audio tracks so you can listen on the fly.
Make sure to check out: Data science for real-time streaming analytics. In this episod, Roger Rea, Senior Offering Manager for IBM Streams, breaks down how data scientists can create real-time applications using IBM Streams.
3. National Public Radio (NPR)
On the National Public Radio website you can listen to stories dedicated to Big Data in the broad context of technology advancements – in business, public health, medicine or security. NPR is a conglomerate of different public radio stations, which doesn’t run any strictly big data podcast. However, tech channels like All Tech Considered or 13.7 Cosmos and Culture, are high-quality, interdisciplinary food for thought for any data-minded person. These channels discuss links between technology, society, and culture.
Make sure to check out: A Remote Chinese Province Uses Its Climate To Grow A Big-Data Industry. A report on how the Guangzhou province in China is using big data to jump to the forefront of China’s tech industry.
And also: How Will Big Data Change The Way We Live? A TED radio hour special where Kenneth Cukier of the Economist examines what’s next for machine learning and human knowledge.
4. Data Skeptic
Data Skeptic is a big data podcast featuring the host Kyle and Linda Polich. Data Skeptic produces mini-episodes explaining concepts from data science, statistics, machine learning, and artificial intelligence. They also put out longer interviews featuring practitioners and experts talking about interesting topics related to data. This is all through the eye of scientific skepticism.
Data Skeptic is a great source of knowledge, whether you want to start learning some basics of data science and machine learning or you want to deepen your knowledge on particular topics, for example, k-means clustering, natural language processing or decision tree learning. Many topics of the mini-episodes are inspired by the show’s parrot, who is a frequent background commentator.
Thanks to the intellectual, offbeat tone of the show, it’s easier to follow than other, more technical big data podcasts. Due to the fun nature and a dose of skepticism that permeates the show, you can emerge with some new insights and knowledge related to data. Finally, the series has great production quality. The radio-friendly voices of the show’s hosts don’t hurt either.
Make sure to check out: Big Data Tools and Trends. This episode features an interview with Raghu Ramakrishnan, CTO for Data at Microsoft. In it, they talk about new trends and developments in big data as well as the reasons these innovations came about.
5. Partially Derivative
Partially Derivative is not just a big data podcast. They describe themselves as a podcast about the data of everything, and rightly so. Their subjects range from big data of sports, journalism, love, space and zombie migration patterns.
The hosts of this show are all experienced technologists and data scientists. Each week Chris Albon, Jonathan Morgan and Vidya Spandana talk about the latest news in data science and look at how data has changed our understanding of the world. This podcast is on the entertaining and light-hearted side but still very informative and insightful. For example, one hilarious episode is called “Can Killer Robots Marry Their Cousins?”.
Adding to the comedic flair, Chris, Jonathan, and Vidya spend the episodes drinking, adding to the light-hearted and fun tone of the episodes, and leading to a fun and enjoyable listening experience. The production value is on point as well, making their voices come through crisp and clear.
If you’re looking for a series that connects “real life” with work life in regards to big data, look no further – Partially Derivative has you covered. Also, a fair warning: most of the episodes have explicit language.
Make sure to check out: Do. Or Do Not. There Is No AI. This episode examines how neural networks can spout wise quotes (and other related topics).
6. Data Stories
Our fifth big data podcast is in a way similar to Data Skeptic. Indeed, Data Stories is an important address for anybody interested in data science with a focus on data visualization. Every other week, Enrico Bertini and Moritz Stefaner provide their followers with extensive coverage of data visualization projects which prove that the line between art and infographics is often fluid. This is a podcast you can also use as an inspiration when you work with your data visualization software.
These podcasts add a philosophical tone to data science, as explained by the show hosts’ belief that “data is beautiful.” They do more than talk about data science or sticking to big data podcasts only – they tell stories about data visualizations. Some cool topics include visualizing your Google search history and talking about data art.
While there are areas of philosophy discussed here, the show manages to keep things invigorating with less of a focus on the extremely technical, as compared to some other data science podcasts.
Make sure to check out: Surprise Maps with Michael Correll and Jeff Heer. This episode talks about Surprise Maps, which display unexpected findings in a dataset rather than just the raw data.
7. The O’Reilly Data Show
The O’Reilly Data Show explores the opportunities and techniques driving big data and data science. There are many episodes available so far, where Ben Lorica, O’Reilly Media’s Chief Data Scientist, is speaking with other experts about the most timely and relevant subjects. Example topics include:
- Graph databases
- Architecting application in the cloud
- Building enterprise data applications with open source components
- Google data flow
Since the O’Reilly name is so well recognized, this podcast boasts a lot of big name, expert guest speakers. Fair warning: this big data podcast can get very technical. However, due to the star power of the guests, it’s well worth your time and energy to soak up what you can. Plus, the topics are relevant and very useful for those serious about the field of data science. If you’ve been in the data science field for a while (or if you intend to be), The Data Show is one podcast you won’t want to miss.
Make sure to check out: A framework for building and evaluating data products. In this episode, Grace Huang, lead data scientist at Pinterest, describes the data challenges her company has faced and lessons from the front lines of launching machine learning related products.
8. Linear Digressions
Hosted by Katie Malone and Ben Jaffe, the Linear Digression podcast covers on a weekly basis diverse topics in data science, including real-life application, data scientists’ career paths or reports on the state of data science. They also cover complex machine learning subjects, like the Hidden Markov Models and how they apply to real-world problems and datasets.
Additionally, this big data podcast often narrows in on very specific ideas in a goofy way, explaining real world problems that you might actually see in your day-to-day life. The episodes are bite-sized, running between 8 and 20 minutes a piece which makes them easy to digest. All of this makes Linear Digressions a great choice for newbies and data scientist veterans alike.
Make sure to check out: Re-Release: Data Mining Enron This episode examines the machine learning advances that came about when hundreds of thousands of executive emails were released from the Enron servers after the company’s infamous scandal.
9. Talking Machines
Talking Machines is not strictly speaking a big data podcast, but it discusses a subset of Big Data: machine learning. Hosts Katherine Gorman and Ryan Adams deliver a professional listening experience, interviewing a variety of industry professionals.
The topics can be quite technical – for example, one episode is called “How to Identify Hallucinating Learning Machines Using Specification Analysis”… not really the morning coffee topic you’d talk about! However, the hosts take pains to keep things accessible to newcomers.
Basically, if you’re interested in machine learning, this is the podcast for you. Since machine learning is one of the fastest growing subfields in data science today, Talking Machines definitely deserves your time and attention.
Make sure to check out: Bias Variance Dilemma for Humans and the Arm Farm This episode features Jeff Dean, Google Senior Fellow in the Research Group, where he leads the Google Brain project. The hosts and Jeff talk about the bias-variance dilemma and answer a listener question about how to make sure your neural networks don’t get tricked.
10. The Freakonomics Radio
Although The Freakonomics Podcast is about much more than data science, it is one of the most popular data related podcasts out there. Indeed, it is consistently one of the most listened to podcasts on all of iTunes.
Hosts Stephen J. Dubner and Steven Levitt use data to explore the “hidden side of everything” in a radio show format. Using the viewpoint of data-loving economists, they break down many problems and their solutions which are often quite different than the answers given by conventional wisdom. With over 4,000 reviews on iTunes, this is one big data podcast you need to have in your rotation.
Make sure to check out: The Fracking Boom, a Baby Boom, and the Retreat From Marriage In this episode, Dubner and Levitt examine the decline in manufacturing jobs, and how fracking is affecting U.S. unemployment rates.
We hope you enjoyed our list of most important voices from the big data field. Combine them with our list of the best Business Intelligence Podcasts and of the best Big Data and data analytics books to build a solid foundation of knowledge for better business decisions.