Linkedin Learning – Securing Generative AI-Strategies Methodologies Tools And Best Practices
English | Tutorial | Size: 81.76 MB
This course offers a comprehensive exploration into the crucial security measures necessary for the deployment and development of various AI implementations, including large language models (LLMs) and retrieval-augmented generation (RAG). Discover key considerations and mitigations to reduce the overall risk in organizational AI system development processes. Author and tech trainer Omar Santos covers the essentials of secure-by-design principles, focusing on security outcomes, radical transparency, and building organizational structures that prioritize security. Along the way, learn more about AI threats, LLM security, prompt injection, insecure output handling, red team AI models, and more. By the end of this course, you’ll be prepared to wield your newly honed skills to protect RAG implementations, secure vector databases, select embedding models, and leverage powerful orchestration libraries like LangChain and LlamaIndex.
RAPIDGATOR:
rapidgator.net/file/e5c618e7d350fb92564b78aa23e212e7/Linkedin.Learning.Securing.Generative.AI-Strategies.Methodologies.Tools.And.Best.Practices.BOOKWARE-SCHOLASTiC.rar.html