Half Stack Data Science podcast | Listen online for free

Available Episodes

5 of 27

S04E02 - Programming with AI - with Simon Willison
In this episode we talked to Simon Willison. Simon is the creator of Datasette, an open source tool for exploring and publishing data. He currently works full-time building open source tools for data journalism, built around Datasette and SQLite.Prior to becoming an independent open source developer, Simon was an engineering director at Eventbrite. Simon joined Eventbrite through their acquisition of Lanyrd, a Y Combinator funded company he co-founded in 2010.He is a co-creator of the Django Web Framework, and has been blogging about web development and programming since 2002 at simonwillison.netWe talked to Simon about his goal of building tools for data journalists, what he's learned about tinkering with, and writing about, AI models for years, his excitement about their code-generating capabilities, how to get the most out of all of these tools, and what generative AI tools have to do with pelicans.You can find Simon at https://simonwillison.netPlease enjoy our conversation with Simon Willison!--David's book, The Well-Grounded Data Analyst is out! ⁠https://www.manning.com/books/the-well-grounded-data-analyst⁠If you want to find out more, we have a whole episode about it: ⁠https://open.spotify.com/episode/5D0iDtQRh3tWiIhokrjz3x?si=AiX6YyRET16lnzXDlvdcfw
--------
50:01
S04E01 - Meaningful uses of AI - with Scott Hanselman
Season 4, all about AI, has launched! In the first episode of the new season we talked to Scott Hanselman.Scott is a programmer, teacher, and speaker. He works out of his home office in Portland, Oregon for Microsoft as the Vice President of Developer Community. He works on .NET, Open Source, and the Azure Cloud Developer Experience, but he also blogs about technology, culture, gadgets, inclusion, code, the web, where we're going and where we've been, and has a number of podcasts and a YouTube channel.We talked to Scott about his role at Microsoft and how he still loves to build things. We talked about AI as a brand, the risks of relying too much on tools like ChatGPT, and how developers can use these technologies meaningfully. We also discussed one of our favourite topics on the podcast, dark matter developers, a term we originally learned from a blog post by Scott himself. See episode 4, Getting Data in our first season for even more about this term.Please enjoy our conversation with Scott Hanselman!You can find Scott at https://www.hanselman.com--David's book, The Well-Grounded Data Analyst is out! https://www.manning.com/books/the-well-grounded-data-analystIf you want to find out more, we have a whole episode about it: https://open.spotify.com/episode/5D0iDtQRh3tWiIhokrjz3x?si=AiX6YyRET16lnzXDlvdcfw
--------
42:55
Season 3 finale - The Well-Grounded Data Analyst - with David Asboth
In this episode, Shaun interviews David about his new book, The Well-Grounded Data Analyst.We talk about the data skill gap between the classroom and the real world that made David want to write this book, the importance of tackling real-world projects for further learning, and the underlying methodology of the book that helps you learn to solve any data problem.If you listen to the end, we also tease our upcoming Season 4 of the podcast.Get your copy here: https://www.manning.com/books/the-well-grounded-data-analystRead more about David's work here: https://davidasboth.com/
--------
49:40
S03E10 - Data science needs you! - with Andrea Jones-Rooy
If you're an aspiring analyst and want to test your existing data skills on real-world problems while learning both new skills and a framework you can apply to any problem, David's book Solve Any Data Analysis Problem is available on the Manning website through the Early Access Program and it's out in print later this year. Find it at https://www.manning.com/books/solve-any-data-analysis-problem In this episode, we welcome back a former guest, Andrea Jones-Rooy, Ph.D. Andrea is the founder of Data Thinking, an organization dedicated to promoting worldwide data literacy and public involvement in data science. Previously, she was the Director of Undergraduate Studies and Visiting Associate Professor at the NYU Center for Data Science, where she developed and taught their flagship course, Data Science for Everyone, as well as advanced courses on Natural Language Processing. Dr. Jones-Rooy believes everyone has a role to play in data science, and you (yes, you!) can get involved at DataScienceNeedsYou.com! We spoke to Andrea about how to teach people the scientific method and to deal with uncertainty, the impact of generative AI on teaching these topics, whether these skills should be called "data thinking" instead of "data science", and how you even convince people these are the skills worth learning. Find Andrea at https://datascienceneedsyou.com or on social media platforms as @jonesrooy
--------
59:53
S03E09 - Statistical rethinking - with Richard McElreath
A reminder that David's book, Solve Any Data Analysis Problem, is out later this year and you can already buy it and read it in its draft form as part of Manning's Early Access Program. If you want to practise your data skills on real world problems and learn a reusable framework to use on any project in the future, this book is for you. Find out more here: ⁠https://www.manning.com/books/solve-any-data-analysis-problem⁠ Now onto today's episode. In this episode, we spoke to Richard McElreath. Richard is an anthropologist focused on the role of culture in human evolution and adaptation. He is currently the Director of the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. A major focus of the department is integrating theory with data analysis and study design, and Richard spends much of his time supporting his colleagues in that way. He is the author of Statistical Rethinking, a popular Bayesian statistics textbook and video course. We spoke to Richard about the state of scientific research, parallels between the problems in scientific research and doing data analysis in the business world, and to quote Richard, how, if we are very careful and try very hard, we might not completely mislead ourselves. Richard's departmental page: https://www.eva.mpg.de/ecology/staff/richard-mcelreath Richard's blog: https://elevanth.org/blog Richard on Twitter: https://twitter.com/rlmcelreath
--------
1:05:22