Master AI threat modeling, SDLC integration, and compliance for enterprise-grade systems
Sub Category
- Other IT & Software
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Objectives
- Identify modern GenAI risks and understand how attackers target LLM and RAG pipelines
- Apply a layered AI security design to strengthen every component of an AI application
- Create detailed AI threat models and link each threat to concrete control measures
- Configure AI firewalls and runtime guardrails to manage prompts, responses, and tool actions
- Embed security practices into AI development workflows, including dataset checks and eval automation
- Implement robust identity, authorization, and scoped access for AI endpoints and integrations
- Enforce data governance for RAG systems through access rules, tagging, and secure retrieval patterns
- Use SPM platforms to maintain visibility over models, datasets, connectors, and policy violations
- Build observability pipelines to track prompts, responses, decisions, and model quality metrics
- Assemble a unified AI security strategy and translate it into clear 30, 60, and 90 day actions
Pre Requisites
- Some background in tech, engineering, or system development
- Optional exposure to machine learning concepts or LLM based tools
- Basic understanding of common security practices is a plus
- Ability to interpret high level architecture and process diagrams
- No previous experience with specialized AI security solutions 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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