Responsible AI: Mitigating Risks in Azure AI Foundry

As generative AI applications become central to modern software, ensuring their safety, reliability, and ethical alignment is more critical than ever. Building these systems requires a structured approach to identifying vulnerabilities and implementing robust guardrails. This written course guides you through the essential principles of responsible AI, showing you how to systematically assess and secure your language model applications. You will learn to use Azure AI Foundry to detect potential harms, evaluate model outputs, and apply effective mitigation strategies. What you'll learn: - Understand foundational responsible AI principles and the lifecycle of risk mitigation - Identify common generative AI vulnerabilities, including prompt injection and hallucinations - Configure content filters and safety settings within Azure AI Foundry to block harmful outputs - Measure model performance and safety using automated evaluation metrics - Implement system-level prompts to guide model behavior and maintain application boundaries - Monitor deployed applications to ensure ongoing compliance and user safety The course begins with core definitions of AI safety and the responsible AI framework, then progresses to hands-on risk assessment methodologies and practical mitigation configuration. You will read through detailed architectural explanations, code snippets, and step-by-step configuration workflows. This course is designed for software developers, product managers, and technology enthusiasts who want to build safer AI applications. No prior experience with machine learning or cloud security is required. Start reading today to build generative AI solutions that are safe, reliable, and trustworthy.