AI Red Teaming transforms your approach to AI safety and security by teaching systematic methods for adversarially testing machine learning models, generative systems, and agentic workflows to uncover vulnerabilities before malicious actors exploit them. Instead of treating red teaming as informal probing or relying solely on automated scanners, it provides structured frameworks for threat modeling, attack surface mapping, jailbreak engineering, data poisoning simulation, and bias amplification testing aligned with NIST AI RMF, OWASP Top 10 for LLMs, and industry best practices. You get hands-on experience designing and executing controlled adversarial evaluations that produce actionable findings for model hardening, policy refinement, and responsible deployment across research, product, and compliance contexts.

This Course Offers

• Adversarial methodology mastery: Learn scoping engagements, defining success criteria, selecting appropriate attack vectors (prompt injection, model inversion, membership inference), and documenting reproducible test cases with ethical boundaries
• Generative AI-specific testing techniques: Master crafting multi-step jailbreaks, evaluating guardrail bypasses, testing tool-use exploits in agents, and assessing output harmfulness across text, image, and code generation modalities
• Bias and fairness stress-testing: Understand amplifying latent biases through targeted prompts, measuring disparate impact under adversarial conditions, and distinguishing robust failures from edge-case anomalies
• Reporting and remediation collaboration: Develop skills translating technical findings into risk-rated recommendations, communicating effectively with ML engineers and policymakers, and validating fixes through retesting cycles

Why We Love This Course

1. The focus on disciplined, ethical adversarial testing makes this highly relevant beyond hackathon-style probing. It feels like learning from an AI safety researcher who has led red teams at major labs and knows that credible findings require rigor, reproducibility, and respect for dual-use concerns.
2. Real engagement case studies make abstract threats tangible. You execute a prompt injection campaign against a customer service bot, simulate training data contamination, and evaluate multimodal model robustness, seeing how methodology determines whether results drive improvement or just noise.
3. Coverage of technical execution and governance alignment provides complete professional readiness. This is useful whether you’re embedded in an AI product team, supporting regulatory compliance, or conducting independent safety research.
4. The instructor brings credible experience in AI security and responsible innovation. The approach emphasizes proportionality, transparency, and constructive intent, ensuring you learn to expose weaknesses responsibly—not performatively.

Trustworthy AI isn’t built in isolation; it’s forged under adversarial scrutiny. The question is whether you want to assume safety or master the disciplined testing that validates it empirically. This course provides the essential foundation to excel in AI red teaming, helping you strengthen systems with integrity and impact.

• AI safety researchers and engineers building internal red team capabilities for model validation
• Security professionals expanding into AI-specific threat assessment and risk management
• Compliance and policy specialists needing technical grounding to evaluate AI governance claims
• Academics and auditors conducting independent evaluations of commercial or open-source AI systems

• Foundational AI/ML knowledge including model architectures, training paradigms, and common failure modes is required
• Familiarity with cybersecurity concepts and basic scripting (Python preferred) supports hands-on exercises
• Access to target models via APIs or local deployments enables practical testing within authorized boundaries
• Strong ethical commitment and understanding of responsible disclosure norms are non-negotiable prerequisites

Interested in exploring more lessons? Check out our full course library to continue building your skills and advancing your learning journey.