In this workshop, participants will learn how to build a Perplexity Agent using Gemini 2.0. The session will cover key concepts like perplexity in natural language processing, which measures how well a language model predicts text. Attendees will get hands-on experience developing a conversational agent using Gemini 2.0, including generating text and calculating perplexity scores. They will also learn how to fine-tune the language model to optimize response quality by reducing perplexity. Basic knowledge of Python and NLP is recommended, and participants will use Gemini 2.0, Python, and cloud resources for development.