Show Notes
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. We're continuing our series of conversations about data education and in this episode we spoke to Richie Cotton.
Richie is a data evangelist at DataCamp. He started his career as a data scientist, working in industries from chemical health and safety to debt collection to proteomics. After joining DataCamp in 2016, he switched to teaching data and AI skills. He has created ten courses on data science that have been taken by over 700k learners, and worked with instructors to create over 50 courses that have been taken by millions of learners. Richie has also written two books and R programming, Learning R and Testing R Code.
In his current role, Richie hosts the DataFramed podcast and runs the DataCamp webinar program, as well as creating tutorials and cheat sheets for data and AI skills.
We spoke to Richie about how DataCamp's offering and focus has changed over time to meet market demands, with some inevitable comments about Python vs R, what the impact of generative AI has been on data education, and what the future holds.
You can find Richie and his work on various parts of the internet:
Connect with Richie on LinkedIn: https://www.linkedin.com/in/richierocks
Listen to the DataFramed podcast: https://www.datacamp.com/podcast
Attend DataCamp webinars: https://www.datacamp.com/webinars
More from Half Stack Data Science
In this episode, we tackle the question of learning in the age of AI. Among other things, we talked about: whether worrying about AI is the same as worrying about calculators why David gets all his students to turn AI features off while learning why rising token prices might end up being a great thing whether AI slop is worse than human slop what we can learn from sailing as we think about our future in an AI world
In this episode, we discuss: - Will people really just write all their own software instead of buying it? - Is the change management around GenAI projects any different from other technologies? - What is the right approach when giving people freedom to vibe code internal tools? - Is there room for a new role to emerge as a bridge between vibe coding and useful internal tools, a technical connector of AI capability and business value?
In the first episode of the new season, we discuss: whether it's a good thing that we can produce more with GenAI, how GenAI will force us to consider the purpose of education, how we are supposed to develop wisdom if GenAI can just build everything for us, how AI-written code introduces "cognitive debt", and in a roundabout way we discuss whether GenAI will kill software companies --- David’s book, The Well-Grounded Data Analyst is out! https://www.manning.com/books/the-well-grounded-data-analyst If you want to find out more, we have a whole episode about it: https://halfstackdatascience.com/s3-finale-the-well-grounded-data-analyst-with-david-asboth
In this episode, we wrapped up 2025 by reflecting on what we talked about on the podcast, where AI is and where it's heading, and looked ahead to 2026. We also discussed some of our favourite sci-fi books we read last year!
In this episode, we spoke to Kirsten Hill. Dr Kirsten Hill is a researcher, writer, and the founder of bisque — a survey platform that actually cares if you get good data. She has a Ph.D. from the University of Pennsylvania, has led research for the Bill & Melinda Gates Foundation, and has worked with over 100 mission-driven teams on measurement & evaluation. This past year, she authored her first book, Ask Better Questions, a top release on survey design — and realized that writing the book wasn’t enough. If she really wanted to change how people do research, she had to build the tools that would make it easier to do it right. With real-time AI feedback, intuitive design, and built-in best practices, bisque makes it easy to create surveys that get you the answers you actually need. We spoke to Kirsten about how and why surveys are often bad, why she believes the major survey platforms aren't fit for purpose, why she's building her own survey platform "bisque", how she's using Large Language Models to develop a working prototype, and what advice she has for other non-programmers who want to build things with AI. You can find her on: LinkedIn @kirstenleehill TikTok @kirstenleehill Substack kirstenleehill.substack.com