Name: ML RAG, Fine-tuning and Security
Start: 2026-02-18
End: 2026-02-18

This webcast explores the evolution of machine learning context-based prompting, RAG, Agentic AI, and fine-tuning and associated risks.&nbsp;Learning Objectives<ul><li>Understand the architectural evolution from prompting to RAG to fine-tuning</li><li>Recognize the technical and security risks at each layer</li><li>Gain practical insights into implementing secure fine-tuning &nbsp;</li></ul>Prerequisite KnowledgeCode samples in Python will be shown during the presentation. Basic knowledge of these could be helpful but is not required.<ul><li>Python programming language&nbsp;</li><li>Google colab / Jupyter lab environment</li><li>Prior experience in using Chatbots like ChatGPT, Gemini, or others</li></ul>

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

ML RAG, Fine-tuning and Security

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