Certified Artificial Intelligence Security Professional

Who Should Attend?

This training course is intended for:

• AI and machine learning engineers responsible for developing, deploying, or maintaining AI systems
• Cybersecurity and information security professionals looking to extend their expertise to AI-specific threats and defenses
• SOC analysts and threat intelligence professionals working in AI-enabled security environments
• IT security architects and consultants designing or reviewing AI system architectures
• Risk management and compliance professionals working with AI governance frameworks and regulatory requirements
• Data scientists and AI developers seeking to apply security practices throughout the AI development life cycle
• Technology managers and technical leads responsible for AI security strategy and program management

Learning objectives

By the end of this training course, participants will be able to:

• Explain the architecture and operation of machine learning, deep learning, LLMs, and AI agents, and identify risks arising from their design, training, and deployment
• Analyze threats to AI and LLM systems using MITRE ATLAS and the OWASP LLM Top 10 across the AI attack life cycle
• Apply AI security controls, monitoring strategies, and threat intelligence workflows to detect, contain, and investigate adversarial activity
• Design and evaluate an AI security program covering incident response, supply chain governance, regulatory compliance, secure architecture, and red teaming

Educational approach

• This training course combines instructor-led lectures, hands-on lab exercises, and real-world scenarios to reinforce learning.
• Hands-on lab exercises give participants direct experience with real-world AI security tools, reinforcing the theoretical content of each section.
• The quiz structure within the course closely mirrors that of the certification exam, ensuring participants are well-prepared.

PECB offers various training course delivery formats, from traditional classroom settings to modern, technology-driven solutions. To learn more about these formats, please click here.

Prerequisites

Candidates are expected to have a solid foundation in core cybersecurity and information security concepts. Familiarity with general security principles, including threat modeling, access control, incident response, and security monitoring, is expected. A basic understanding of how machine learning systems work, including awareness of concepts such as model training, data pipelines, and API-based services, is also expected.