Anand S

In this talk, we will explore how Large Language Models (LLMs) can autonomously perform tasks traditionally handled by data scientists. Using live coding, we will demonstrate how LLMs can explore a dataset, generate hypotheses, write and test code, and fix issues as they arise.

We'll also cover how LLMs can test statistical significance, draw charts, and interpret results-capturing the essence of what a data scientist does. Additionally, we'll discuss the evolving role of human data scientists in a world where LLMs can handle so much of the data science workflow, and examine where human expertise will still be essential in the process.

What happens when developers hand off part of the heavy lifting to AI? In the Vibe Coding Showdown, three panelists-from different technical backgrounds-set out to solve the same ambitious app challenge using AI-powered coding assistants. The result? Three applications, each built with a mix of human intent and machine-generated code.

This session walks you through how they did it-how AI helped brainstorm, build, debug, and refine complex apps using just natural language, iterative feedback, and smart tooling. Whether you’re a developer or just AI-curious, you’ll see how AI is shifting the way we approach software creation.