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Saturday, March 8, from 2:15 - 5:45 p.m.

Room: Excelsior Bay, 8th floor

Cost: $40

Instructor: Ben Welsh, Reuters, Derek Willis, University of Maryland

Learn how journalists use large-language models to organize and analyze massive datasets.

Take this three-hour class to get hands-on experience creating a machine-learning model that can classify the text recorded in campaign contributions, crime reports, legislative bills, consumer complaints and other newsworthy data.

You will learn how to:
* Replace a complex machine-learning system with a simple LLM system
* Write a prompt that classifies text into predefined categories
* Evaluate your results using a rigorous, scientific approach
* Improve your prompt by training it with rules and examples

By the end, you will understand how the new class of LLM classifiers can outperform traditional machine-learning methods with significantly less code, and you will be ready to write one yourself.

Anyone who has dabbled with code and AI is qualified for this class. A curious mind and good attitude are all that’s required.

Preregistration is required and seating is limited. Laptops will be provided.