Learn to identify, analyze, and mitigate GenAI threats using modern security playbooks
Sub Category
- Network & Security
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Objectives
- Understand the full GenAI threat landscape and how modern attacks target LLMs and RAG systems
- Apply the AI Security Reference Architecture to design secure AI applications
- Perform threat modeling for GenAI systems and map risks to concrete mitigations
- Implement AI firewalls, filtering rules, and runtime protection controls
- Build a secure AI SDLC with dataset security, evals, and red-teaming practices
- Configure identity, access, and permission models for AI tools and endpoints
- Apply data governance techniques for RAG pipelines, embeddings, and connectors
- Use SPM platforms to monitor drift, violations, and AI asset inventory
- Deploy observability and evaluation tooling to track model behavior and quality
- Assemble an end-to-end AI security control stack and build a 30/60/90 day roadmap
Pre Requisites
- Intro level understanding of how modern applications or cloud systems work
- Optional familiarity with machine learning or LLM based tools
- Some exposure to security fundamentals is useful but not mandatory
- Comfort with technical documentation and architectural schematics
- No background in AI security or specialized tooling required
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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