Operationalizing Responsible AI with Azure AI Foundry

Deploying generative AI requires more than just functional code; it demands rigorous safety, privacy, and compliance standards. Moving from reactive risk patching to proactive, responsible-by-design AI development is essential for building trustworthy applications. This course guides you through operationalizing responsible AI practices using Azure AI Foundry, helping you integrate safety evaluations, content filtering, and continuous monitoring directly into your development lifecycle. You will learn to: Understand foundational responsible AI principles, including fairness, reliability, privacy, and transparency; Configure content safety filters within Azure AI Foundry to block harmful inputs and outputs; Evaluate generative AI models for quality, groundless outputs, and vulnerability to prompt injection attacks; Implement robust data privacy measures and access controls to protect sensitive organizational data; Monitor deployed AI models in real time to ensure ongoing compliance and operational observability. The course begins with core ethical AI frameworks and terminology before guiding you through practical configuration steps in Azure AI Foundry. You will read through detailed technical explanations, architectural patterns, and structured scenarios designed to build your operational confidence. This course is designed for software developers, IT professionals, and AI enthusiasts who want to learn responsible AI governance from the ground up, with no prior experience in AI safety required. Start reading today to build AI systems that are secure, compliant, and trusted by design.