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🔎 Overview Neuroscience and life science teams are working with bigger, more complex datasets than ever, often in messy notebooks and fragile scripts that are hard to reuse. By watching the recording of this workshop, you'll learn how to use large language models (ChatGPT and Claude Code) to: – Clean up and refactor existing analysis code – Make notebooks easier to understand and share – Ultimately move faster on grant proposals, publications, and discovery work 🌐 Speakers – Stephen Larson | CEO & Co-founder, MetaCell – Phil Dong | Data Scientist, MetaCell 🎯 Who is it for? This workshop is for you if you: – Work with imaging, electrophysiology, calcium imaging, photometry, or behavioral data – Maintain or rely on Python, MATLAB, R, Jupyter analysis notebooks – Want to use AI tools without sacrificing rigor or reproducibility – Need to extract insights from data with visual charts but are not yourself a data scientist ✅ What you'll learn By the end of the session, you'll know how to: – Use ChatGPT and Claude Code to debug, refactor, and document your analysis code – Turn messy exploratory notebooks into clearer, reusable pipelines – Get better prompts and more reliable outputs for scientific workflows 🚀 About MetaCell MetaCell has spent the last 14 years helping neuroscience and life science teams analyze complex datasets, acting as an on-demand extension of the lab with part-time data scientists and engineers. We work with researchers at institutions such as Yale, Princeton, Stanford, UCSD, UCL, University of Edinburgh, CAMH, CZI, and the Allen Institute, helping them move faster from data to results.