AI Security & Governance Masterclass: Build, Attack & Defend

Source: https://www.udemy.com/course/ai-security-governance-masterclass-build-attack-defend/

What you’ll learn

Identify major AI security threats across chatbots, RAG systems, tools, memory, and autonomous agents.
Build and secure AI applications using Python, Ollama, RAG, tool calling, memory, and agents.
Perform and defend against prompt injection, jailbreaks, document poisoning, and memory poisoning.
Apply the OWASP Top 10 for LLM Applications to real-world AI systems.
Implement prompt validation, risk scoring, guardrails, content filtering, and policy enforcement.
Secure AI tool use with input validation, least-privilege permissions, and human approval workflows.
Build an integrated AI Security Gateway for prompts, RAG, tools, memory, and agent actions.
Create AI governance dashboards for inventory, usage, cost, risk, evaluation, drift, and compliance.
Map AI controls to NIST AI RMF, ISO/IEC 42001, and the EU AI Act.
Build an Enterprise AI Governance Command Center with audit trails, incidents, controls, evidence, and executive metrics.

Requirements

No prior AI security or AI governance experience is required.
Basic computer skills and a willingness to learn through hands-on projects.
Some familiarity with Python is helpful, but beginners can follow the guided demonstrations.
A Windows, macOS, or Linux computer capable of running Python development tools.
Permission to install Python, Visual Studio Code, Git, Ollama, and Docker.
Basic understanding of AI, chatbots, or generative AI is useful but not mandatory.
An interest in cybersecurity, AI development, governance, risk, or compliance.
Internet access may be required for downloading software, libraries, and course resources.