In this masterclass, you'll learn ways to better protect your data when working with LLMs. We'll cover how to architect your systems for better privacy and security, some introductions to red teaming and some basic protections for your text-based inputs (including guardrail models and prompt sanitization). At the end of the course, you'll leave with some practical guides on how to use LLMs more safely with private and sensitive data.
GitHub: https://github.com/kjam/secure-and-private-ai-products-masterclass
Katharine Jarmul is a privacy activist and an internationally recognized data scientist and lecturer who focuses her work and research on privacy and security in data science and machine learning. You can follow her work via her newsletter, Probably Private or in her recently published book, Practical Data Privacy (O'Reilly 2023) now also available in German and Polish.
She is a passionate and internationally recognized data scientist, programmer, lecturer, keynote speaker and writer.
A few of Katharine's books: