Create a full-stack AI defense strategy across model, data, and infrastructure layers
Sub Category
- Network & Security
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Objectives
- Analyze the unique attack surface of GenAI systems and see how LLMs and RAG apps are exploited
- Use a structured AI security architecture to plan protections across all layers of an AI solution
- Build complete threat models for AI workloads and connect identified risks with practical defenses
- Deploy AI gateways and guardrail engines to filter inputs, outputs, and tool executions
- Integrate security into every AI development stage, including data sourcing, evaluations, and safety reviews
- Set up strong authentication, scoped permissions, and regulated tool access for AI components
- Govern sensitive data in RAG pipelines with structured policies, metadata rules, and controlled retrieval flows
- Operate AI SPM tools to track models, datasets, connectors, and detect risk or drift over time
- Implement logging, telemetry, and evaluation pipelines to observe how AI behaves in production
- Construct a complete AI security control stack and define an actionable plan for short and long term adoption
Pre Requisites
- General experience with IT, software, or engineering environments
- Helpful but optional familiarity with AI workflows or retrieval systems
- Basic awareness of cybersecurity ideas like access control or data protection
- Ability to follow technical explanations and architectural breakdowns
- No prior hands on work with AI security platforms or evaluations needed
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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