TAISE · Trusted AI Safety Expert

TAISE is tailored for IT and security professionals interested in expanding their knowledge of AI best practices. This includes AI developers, practitioners, auditors, compliance and governance professionals, and others who are committed to integrating safety protocols into AI technologies.

Ideal for professionals who:

● Develop, manage, or audit AI systems
● Oversee compliance, ethics, or governance programs
● Lead AI adoption strategies in enterprises
● Secure AI/ML pipelines and data systems

TAISE covers ten core domain/modules of AI safety, equipping professionals with the frameworks, tools, and practical methods needed to navigate regulatory requirements, defend against emerging AI threats, and build organizational trust in AI.

Module 1: Introduction to AI

Provides foundational knowledge of AI concepts, modalities, and their historical evolution.

Module 2: Generative AI Architecture & Design

Explores the technical components, training methods, and deployment considerations of generative AI.

Module 3: AI Use Cases: GenAI, Multimodal & AI Agents

Examines real-world applications of generative AI across industries while addressing ethical implications such as deepfakes, misinformation, and bias.

Module 4: Ethics, Transparency, & Explainability in AI

Introduces key ethical principles and practical explainability methods to promote fairness, accountability, and transparency in AI systems.

Module 6: Governance, Risk Management, & Compliance

Focuses on governance structures, regulatory frameworks, and compliance models for managing AI systems responsibly at the organizational level.

Module 7: Introduction to AI Safety & Security

Differentiates between AI safety and AI security, highlighting the unique challenges of securing GenAI.

Module 8: Cloud & AI Security

Details cloud security fundamentals for AI, including deployment strategies, monitoring, Zero Trust, and incident response planning

Module 9: Data Security & Privacy in AI Systems

Explains techniques for ensuring data quality, privacy, and governance in AI systems, with a focus on authenticity, minimization, and secure handling.

Module 10: Continuous Learning & Adaptation

Emphasizes ongoing monitoring, feedback loops, and MLSecOps practices to keep AI systems accurate, resilient, and safe over time.

The Trusted AI Safety Expert (TAISE) certificate, developed by the Cloud Security Alliance (CSA) and Northeastern University, is a rigorous, research-backed program for professionals who build, manage, or audit intelligent systems.

Through 10 comprehensive modules and a final exam, learners gain the skills to evaluate AI risks, apply AI safety and security controls, and lead responsible AI adoption.