Strategic Data Project Convening 2025

This session is for any data analyst who wants to build a foundation for machine learning and AI using what they already know with traditional analytic methods. It provides a broad overview and motivating examples across different tasks including analyzing responses to open-ended survey questions, predicting which of two or more groups individuals will belong to in the future, and forecasting future metrics plus next word prediction just like fancy generative AI models. Importantly, the information will be presented in a way to build a bridge between traditional analytic methods and artificial intelligence: spelling out what is common and what is unique, “translating” AI jargon, and pointing out where AI methods are similar to other tried-and-true methods familiar to data analysts. For the areas covered, the session will show how the methods have evolved to reach their current state, what AI is doing behind the scenes with the data, and how these methods can be useful when working with educational data. The session will end with worked examples featuring simple code in Python, but no prior experience in Python is needed. Although the session covers a lot of ground, attendees can work at their own pace thanks to instructions, code examples, and other resources that they can return to after convening. Facilitators are data scientists with a combined 15 years of industry experience working with real world data—primarily K-12 educational data—who want to prove that if you have written code in any language to analyze quantitative data before, you are well situated to apply methods used in machine learning and AI.  This is the session for data analysts who have wanted to try their hand at using AI in their work but would like guidance in determining how, where, or when to start.