ML RAG, Fine-tuning and Security

This webcast explores the evolution of machine learning context-based prompting, RAG, Agentic AI, and fine-tuning and associated risks.

Learning Objectives

• Understand the architectural evolution from prompting to RAG to fine-tuning
• Recognize the technical and security risks at each layer
• Gain practical insights into implementing secure fine-tuning

Prerequisite Knowledge

Code samples in Python will be shown during the presentation. Basic knowledge of these could be helpful but is not required.

• Python programming language
• Google colab / Jupyter lab environment
• Prior experience in using Chatbots like ChatGPT, Gemini, or others