The eAIS Learning Path is designed for cybersecurity professionals, penetration testers, red teamers, SOC analysts, DevSecOps practitioners, and technical leaders who need to understand how modern AI-enabled systems are built, how they fail, and how to secure them. As organizations rapidly adopt LLMs, copilots, RAG applications, and autonomous AI agents, traditional application security knowledge is no longer sufficient. This path provides a structured, practical approach to AI security from an attacker, defender, and engineering perspective. Learners will build understanding of AI/LLM architecture — including model endpoints, orchestration layers, retrieval pipelines, vector stores, and agentic workflows — then move into hands-on offensive and defensive techniques covering prompt injection, RAG manipulation, data extraction, secure design patterns, least-privilege controls, and safe operationalization. Graduates will be equipped to assess, exploit, and secure enterprise AI deployments in real-world environments.
