FourthBrain Workshop
Building with Open Source LLMs
Keep your data private
An advanced workshop for ML engineers, tech leads and managers on using LLMs with sensitive data. You'll learn to get frontier model performance using your own infrastructure to leverage LLMs for domain-specific requirements.
- Date: Coming Soon!
- Time: 8am-2:30pm PT
- Cost: $500 for individuals | $1,500 for teams of 4
"The lab demo and discussions were phenomenal."
"All of the context setting data was fantastic, the coding example work was also very helpful."
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 using open source and self-hosted LLMs while maintaining data privacy. You'll learn about the best open-source LLMs for different use cases and domains that leverage fine-tuning, prompt engineering, and RAG.
Key Outcomes
Understand strategies for preserving data privacy and security
Adapt pre-trained models to specific industries and domains
Evaluate and deploy fine-tuned models effectively
Workshop Schedule
This workshop includes one 6-hour live class session.
- Overview of open-source LLMs and the current tech landscape
- Advanced Prompt Engineering techniques and entity extraction
- Comparing frontier models to open-source
- Advanced RAG techniques including hybrid search, query decomposition/re-writing, RAFT, and evaluation best practices)
This workshop is for you if:
You have some familiarity with deep learning concepts; intermediate knowledge of Natural Language Processing is recommended.
As a Team
Many employers offer reimbursement for programs like ours. Check out our tips for getting reimbursed.
Register Here
Interested in this program for your team? Reach out!
FAQs
