Mastering Complex Data Ingestion with Open Source AI | PyData Vermont 2025 🎯

www.pydata.org If you have worked with AI in any capacity, you'll know that AI is only as valuable as the data in can leverage. Data is the cornerstone of AI, and developers need better ways to transform complex documents into structured data ready for model training and inference. In this session we will learn how to turn common, real-world documents and scans into structured data for search and RAG. In this 90-minute, code-along workshop, you’ll learn all about Docling, an open-source toolkit for advanced document conversion, allowing you to leverage your data more effectively into AI workflows. We’ll complete three labs; Conversion, Chunking, and RAG, and you’ll leave with runnable notebooks from a public GitHub repo. Audience: Python practitioners shipping document-centric apps. Prereqs: basic Python/Jupyter. PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps