Proprietary Data and LLMs
Build a data-secure application
- Date: Friday, December 15th
- Time: 8am-2:30pm PT
- Cost: $500 for individuals | $1,500 for teams of 4
Building an enterprise application using current available LLMs can introduce security and privacy risks. Maintaining data privacy is a crucial step while building generative AI applications.
In this workshop you will learn to build and deploy an LLM-powered application while maintaining data privacy. You’ll learn to host your own LLMs, fine-tune them for domain-specific and privacy-sensitive enterprise use cases, and explore the best evaluation methods to validate and monitor performance.
Understand strategies for preserving data privacy and security
Adapt pre-trained models to specific industries and domains
Evaluate and deploy fine-tuned models effectively
This workshop includes one 6-hour live class session.
- Overview of LLMs and the current tech landscape
- Guidance for when fine-tuning is appropriate (or not!)
- Strategies for preserving data privacy in fine-tuning (federated p-tuning, differential privacy, etc.)
This workshop is for you if:
How to Prepare
Many employers offer reimbursement for programs like ours. Check out our tips for getting reimbursed.