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AI Cybersecurity Solutions: Overview of Applied AI Security
Learn to identify, analyze, and mitigate GenAI threats using modern security playbooks
Topics: Cybersecurity
Coupon code
OCTOBERFREE2026
Verified 2026-11-01. The price should show as Free at checkout.
About this course
AI security is no longer optional. Modern LLMs, RAG pipelines, agents, vector databases, and AI powered tools introduce entirely new attack surfaces that traditional cybersecurity does not cover. Organizations face prompt injection, data leakage, model exploitation, unsafe tool calls, drift, misconfiguration, and unreliable governance.
This course gives you a complete, practical, architecture driven guide to securing real GenAI systems end to end. No fluff, no theory for theory’s sake. Only actionable engineering practices, proven controls, and real world templates.
What this course delivers
A full AI security blueprint , including:
AI Security Reference Architecture for model, prompt, data, tools, and monitoring layers
The complete GenAI threat landscape and how attacks actually work
AI firewalls, runtime guardrails, policy engines, and safe tool execution
AI SDLC workflows: dataset security, red teaming, evals, versioning
RAG data governance: ACLs, filtering, encryption, secure embeddings
What you'll learn
- 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
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