Super Data Science: ML & AI Podcast with Jon Krohn

“Being a great data scientist” and “being great at a data science interview” are not one and the same. Jon Krohn speaks with Nick Singh about how to strengthen your interviewee skills, and how you can even beat out more senior competition to land a coveted data science role.This episode is brought to you by Datalore (datalore.online/SDS), the collaborative data science platform, and by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.In this episode you will learn:• Nick’s inspiration for writing his bestselling book, Ace the Data Science Interview [06:21]• Why Nick believes in being a work generalist [12:37]• How DataLemur supports emerging data scientists for free [15:43]• Why Nick started DataLemur off the back of his book [21:31]• Portfolio essentials for any data scientist [22:36]• The three most common things data scientists get wrong at the interview [24:33]• How data science introverts can shift their mindset about self-promotion [37:58]• Great responses to end your data science interview on the right foot [42:21]Additional materials: www.superdatascience.com/615

World-leading futurist, author and entrepreneur, Ross Dawson joins us for the first of our extended Five-Minute Friday episodes. As information overwhelm becomes increasingly unavoidable, Dawson is here to share the five powers from his new book 'Thriving on Overload', to help us transition from overwhelm into abundance.  Additional materials: www.superdatascience.com/614Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Dr. Emre Kiciman, Senior Principal Researcher at Microsoft Research joins the podcast to share his world-leading knowledge on causal machine learning.This episode is brought to you by Datalore (datalore.online/SDS), the collaborative data science platform, and by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.In this episode you will learn:• What is causal machine learning? [5:52]• Causal machine learning vs correlational machine learning [10:10]• Emre’s DoWhy open-source library [16:17]• The four key steps of causal inference [21:24]• How and why Emre’s key steps of causal inference will impact ML [26:36]• Emre's thoughts on the future of causal inference and AGI [34:09]• How Emre leverages social media data to solve social problems [38:36]• What's next for Emre's research [46:02]• The software tools Emre highly recommends [55:16]• What he looks for in the data science researchers he hires [58:45]Additional materials: www.superdatascience.com/613

Some exciting changes are coming to our popular Five-Minute Friday series! From longer episodes to new guests, tune in to hear what's next.Additional materials: www.superdatascience.com/612Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Dr. Ken Stanley, a world-leading expert on Open-Ended AI and author of the genre-bending book "Why Greatness Cannot be Planned," joins Jon Krohn for a discussion that has the potential to shift your entire view on life. Tune in now to learn more about the complex topics of genetic ML algorithms, the Objective Paradox, Novelty Search, and so much more.This episode is brought to you by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.In this episode you will learn:• Ken on his book 'Why Greatness Cannot Be Planned" and the Objective Paradox [4:15]• The Novelty Search approach [24:14]• How open-ended algorithms like Novelty Search can be stopped from doing something potentially dangerous [1:00:00]• The future of open-ended AI and its intimate relationship with Artificial General Intelligence [1:07:34]• Ken's new company [1:13:34]• How AI could transform life for humans in the coming decades [1:18:29]Additional materials: www.superdatascience.com/611

On this episode of Five-Minute Friday, host Jon Krohn shares his life motto, “Who dares, wins”, and the sentiment behind it: that to get anywhere in life, it is first necessary to try. Jon believes that “daring”, in this instance, simply means taking action when we have a good idea or when a new opportunity becomes available. Listen to the end for constructive advice on how to be daring in your own life right now.Additional materials: www.superdatascience.com/610Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Jon Krohn speaks with Zhamak Dehghani, the empathetic technologist who coined the term “data mesh”. They explore what a data mesh is, and how its approach toward secure interconnectivity will help solve a roster of data-led business problems.This episode is brought to you by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.In this episode you will learn:• The importance of data meshes [3:29]• How standardizing database interfaces helps tech giants like Amazon [6:40]• Current challenges with data meshes [9:33]• How data meshes give users the freedom to work with data [17:09]• The missing piece of the puzzle for data meshes [22:11]• How data meshes connect with the metaverse and Web3 [33:18]• The times when data meshes aren’t fit for purpose [42:24]Additional materials: www.superdatascience.com/609

Company meetings should be held to solve problems. So, why do we often feel like the weekly stand-ups and check-ins are a waste of everyone’s time? On this episode of Five-Minute Friday, host Jon Krohn brings his habit-making practices into the dreaded meeting room. Make every meeting productive and positive with his five-step method for assigning deliverables.Additional materials: www.superdatascience.com/608

We welcome Dr. Jennifer Hill, Professor of Applied Statistics at New York University, to the podcast this week for a discussion that covers causality, correlation, and inference in data science.This episode is brought to you by Pachyderm, the leader in data versioning and MLOps pipelines and by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts.In this episode you will learn:• How causality is central to all applications of data science [4:32]• How correlation does not imply causation [11:12]• What is counterfactual and how to design research to infer causality from the results confidently [21:18]• Jennifer’s favorite Bayesian and ML tools for making causal inferences within code [29:14]• Jennifer’s new graphical user interface for making causal inferences without the need to write code [38:41]• Tips on learning more about causal inference [43:27]• Why multilevel models are useful [49:21]Additional materials: www.superdatascience.com/607

Four thousand weeks equate to roughly 80 years—a lifetime for those of us lucky enough to get there. What do we choose to do with this time? How can we stop ourselves from feeling like time in general is slipping away? In this episode, host Jon Krohn reviews the book Four Thousand Weeks: Time Management for Mortals by journalist Oliver Burkeman. He outlines how he has personally benefited from this essential reflection on our thirst for productivity and efficiency.Additional materials: www.superdatascience.com/606