4 min listen
#58 Critical Thinking in Data Science
FromDataFramed
ratings:
Length:
59 minutes
Released:
Mar 25, 2019
Format:
Podcast episode
Description
This week, Hugo speaks with Debbie Berebichez about the importance of critical thinking in data science. Debbie is a physicist, TV host and data scientist and is currently the Chief Data Scientist at Metis in NY.In a world and a professional space plagued by buzz terms like AI, big data, deep learning, and neural networks, conversations around skill sets and less than productive programming language wars, what has happened to critical thinking in data science and data thinking in general? What type of critical thinking skills are even necessary as data science, AI and machine learning become even more present in all of our lives and how spread out do they need to be across organizations and society? Listen to find out!LINKS FROM THE SHOWDATAFRAMED GUEST SUGGESTIONSDataFramed Guest Suggestions (who do you want to hear on DataFramed?)FROM THE INTERVIEWDebbie on TwitterDebbie's WebsiteDebbie Berebichez- Media Reel (Video)Deborah Berebichez' Keynote at Grace Hopper Celebration 2017 (Video)Debbie Berebichez on Perseverance and Paying it Forward (Video)Things about the Future and the Future of Things (By Debbie Berebichez, Video)FROM THE SEGMENTSData Science tools for getting stuff done and giving it to the world (with Jared Lander ~21:55)Lander Analytics WebsiteDocker Websiteplumber WebsiteStatistical Distributions and their Stories (with Justin Bois ~39:30)Probability distributions and their stories (By Justin Bois)The History of Statistics (By Stephen M. Stigler)The Evolution of the Normal Distribution (By Saul Stahl)Original music and sounds by The Sticks.
Released:
Mar 25, 2019
Format:
Podcast episode
Titles in the series (100)
#0 Introducing DataFramed: We are super pumped to be launching a weekly data science podcast called DataFramed, in which Hugo Bowne-Anderson, a data scientist and educator at DataCamp, speaks with industry experts about what data science is, what it’s capable of, what it looks l... by DataFramed