I have a special episode for you this time around. We're coming to you live from PyCon 2024. I had the chance to sit down with some amazing people from the data science side of things: Jodie Burchell, Maria Jose Molina-Contreras, and Jessica Greene. We cover a whole set of recent topics from a data science perspective. Though we did have to cut the conversat ... Show More
Nov 10
#527: MCP Servers for Python Devs
Today we’re digging into the Model Context Protocol, or MCP. Think LSP for AI: build a small Python service once and your tools and data show up across editors and agents like VS Code, Claude Code, and more. My guest, Den Delimarsky from Microsoft, helps build this space and will ... Show More
1h 6m
Nov 1
#526: Building Data Science with Foundation LLM Models
Today, we’re talking about building real AI products with foundation models. Not toy demos, not vibes. We’ll get into the boring dashboards that save launches, evals that change your mind, and the shift from analyst to AI app builder. Our guide is Hugo Bowne-Anderson, educator, p ... Show More
1h 7m
Dec 2024
849: 2025 AI and Data Science Predictions, with Sadie St. Lawrence
Sadie St Lawrence returns for her 4th annual prediction episode on the Super Data Science Podcast. Together with host Jon Krohn, they reflect on 2024’s most transformative trends—like agentic AI and enterprise AI monetization—and predict what's coming in 2025, from AI-driven scie ... Show More
1h 18m
Aug 5
911: The Future of Python Notebooks is Here, with Marimo’s Dr. Akshay Agrawal
Reproducibility, Python notebooks, and data science communities: Software developer Akshay Agrawal speaks to Jon Krohn about Marimo, the next-generation computational notebook for Python, how he built and fostered a thriving community around the product, and what makes this noteb ... Show More
58m 20s
Feb 2025
The Future of Data Engineering: AI, LLMs, and Automation
Summary
In this episode of the Data Engineering Podcast Gleb Mezhanskiy, CEO and co-founder of DataFold, talks about the intersection of AI and data engineering. He discusses the challenges and opportunities of integrating AI into data engineering, particularly using large langua ... Show More
59m 39s
Oct 1
179: How I Use PRIVATE Data ETHICALLY In the New Era of AI
<p>There is an impossible choice most organizations face. Companies building modern AI face a brutal, binary-feeling decision: either ship a privacy-first model that “kinda low key sucks,” or ship a high-performing model that likely exposes sensitive personal data. Luckily, there ... Show More
7m 17s
Sep 9
176: I Asked 7 Data Analysts What Tools They ACTUALLY Use
<p>Before you start cramming tools to land a data job, ask yourself this: What tools are data analysts actually using every day? In this episode, I went straight to the pros—analysts at Google, Amazon, Apple, Tesla, Humana, Veterans United, 7-Eleven, and more—to hear which tools ... Show More
18m 20s
