Certified - AI Security Audio Course

<p>This episode introduces multimodal and cross-modal security, focusing on AI systems that process images, audio, video, and text simultaneously. For certification readiness, learners must understand that multimodal...

<p>This episode introduces program management patterns for phased AI security adoption, with emphasis on the 30/60/90-day framework. For certification readiness, learners must understand how phased adoption reduces...

<p>This episode focuses on people and process as integral elements of AI security, highlighting how organizational culture and defined responsibilities reinforce technical defenses. For certification purposes, learners...

<p>This episode examines enterprise architecture patterns for secure AI deployments, focusing on how organizations structure systems to balance scalability, performance, and resilience. For certification, learners must...

<p>This episode explores third-party and vendor risk management in AI security, focusing on the challenges of relying on external providers for models, datasets, APIs, and infrastructure. For certification purposes...

<p>This episode introduces the legal and compliance horizon for AI security, giving learners a high-level view of regulatory landscapes without overwhelming them with acronyms. For certification readiness, candidates...

<p>This episode examines content provenance and watermarking as methods to authenticate AI-generated or human-created content, providing assurance of originality and integrity. Provenance involves tracking the history...

<p>This episode explores the risks of deepfakes and synthetic media, examining how generative AI enables the creation of realistic but deceptive audio, video, and images. For certification, learners must understand...

<p>This episode addresses incident response for AI-specific security events, focusing on structured detection, containment, and remediation. Learners must understand that AI incidents differ from traditional security...

<p>This episode examines the secure software development lifecycle (SDLC) for AI, emphasizing integration of security at each stage of system creation. Learners must understand that AI-specific risks require adapting...

<p>This episode introduces the OWASP GenAI/LLM Top 10, a structured list of the most critical risks associated with generative AI and large language models. For certification purposes, learners must understand how OWASP...

<p>This episode covers threat modeling as a structured method for identifying and prioritizing risks in AI systems. Learners must understand the role of frameworks such as MITRE ATLAS, which catalog adversarial...

<p>This episode examines risk frameworks for AI security, focusing on the NIST AI Risk Management Framework and ISO/IEC 42001. These frameworks provide structured approaches to identify, assess, mitigate, and monitor...

<p>This episode introduces governance and acceptable use policies as organizational frameworks that guide secure and ethical AI adoption. Governance defines the processes, roles, and oversight structures for managing AI...

<p>This episode examines keys, encryption, and attestation as core mechanisms for ensuring confidentiality, integrity, and trust in AI systems. Keys form the foundation of cryptographic operations, and encryption...