When you’re really passionate about something, you tend to meticulously plan your time, don’t you? You subconsciously find ways to work on your passion or goal while doing redundant or regular tasks. That’s how I got used to audiobooks and podcasts.
Being someone who is truly passionate about data science and emerging technologies, I found myself seeking newer insights on tools, techniques, market trends, and more every day. This quest for knowledge appeared perpetual. That’s when I started listening to data science podcasts while doing regular tasks. It takes a solid one hour for me to get to work from where I live. I ditched the habit of listening to random songs that music players curated for me and resorted to podcasts on data science.
This led me to discover one gem after the other, each of which has a permanent spot in my playlist. I felt it would be great to share my list with someone like you who is passionate and keen about data science as well.
So, here’s the list.
I was keen that I should start the list with this show. Towards Data Science is one of the most popular podcasts in this space, and there’s a solid reason for this. The host, Jeremie Harris, ensures his guests are highly relevant and that they bring in their distinct voices and expertise in Data Science.
There is a flow to his conversations that keep us hooked on the topic. Besides, Jeremie also breaks down complex jargon and technical details in the middle of conversations to ensure we, as listeners, don’t disconnect at any given point in time. This gives us a more holistic understanding of the topic under discussion. If you’re looking for solid takeaways on Data Science, this is your go-to podcast.
Firstly, this podcast boasts of an incredible library with over 370 episodes curated and compiled as mini and regular episodes. One of the reasons for this abundant repository is the fact that this show has been on air since 2014. That’s also the time when the data revolution happened. The seasons are classified to mark the diverse aspects of data science, such as K-means, ad-tech, time series, consensus, NLPs, and more.
Kyle Polich is the host of the podcast, and she has given us a unique perspective on Data Science by discussing fake news as well. Binge-worthy!
Data is of no use if you can’t infer insights and takeaways from it. And how does one do it? Through data visualization. Storytelling is an integral aspect of data science, and this is done effectively through data visualization. While most of the podcasts talk about key and regular topics in data science, Data Stories discusses the visualization part of it.
The hosts, Moritz Stefaner and Enrico Bertini, extensively talk about data analysis and visualization topics and curate airtight questions for their guests. This ensures solid responses that are enlightening. If you intend to understand how data practically influences our lives on a daily basis, tune into this podcast whenever you can.
As the name suggests, this is one super series on everything data science. From tools and techniques to processes and career paths in data science, the host Kirill Eremenko does a spectacular job of curating topics and explaining them. The best part about the series is not just your interviews. It’s the motivating stories and bytes on the topic that help you improve as a data scientist.
If wisdom had an online address, it would be the Lex Fridman Podcast. His episodes will take you on a guilt trip once you realize that so much knowledge and wisdom is available for free. What started as the AI Podcast evolved into an all-encompassing series where the very nature of consciousness, philosophy, and even abstract concepts are discussed with guests. From singularity and superintelligence to tech and astrophysics, there is abundant knowledge for you.
These podcasts have been my most ideal companions during my commute, lunch, and runs. They have given me tremendous insights on not just the topics but how it overlaps into diverse yet intricate aspects of our everyday lives.
Start listening to them if you haven’t already. Also, list down your recommendations. Would love to update my playlist.
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