GenAI Ops: Running Powerful Generative AI Systems

Organizations deploying generative AI at scale face complex challenges spanning governance, infrastructure, security, and cost management that traditional IT approaches can't solve. This comprehensive program equips you with the end-to-end operational skills to run powerful GenAI systems reliably, securely, and cost-effectively in production environments. You'll develop expertise across the complete GenAI operations lifecycle: optimizing model performance through governance frameworks and ensemble methods, deploying resilient AI systems with automated rollback capabilities, architecting scalable cloud infrastructure across multi-cloud environments, implementing zero-trust security with compliance validation, and maintaining high-performance operations while controlling costs through intelligent automation. Through hands-on projects using real enterprise scenarios, you'll build monitoring dashboards for AI performance drift, create infrastructure-as-code templates for secure deployments, design cost optimization models that reduce cloud spending by 30%, and establish governance workflows that balance innovation velocity with regulatory compliance. These practical skills prepare you for leadership roles as GenAI platform engineers, AI operations managers, and enterprise architects who ensure AI systems deliver business value while meeting security, compliance, and performance standards at scale

• Optimize GenAI performance with governance frameworks, ensemble models, and automated testing for reliable user operations
• Deploy and maintain production AI systems using MLOps best practices, infrastructure automation, and observability frameworks to ensure 99.9% uptime
• Architect scalable multi-cloud infrastructure with cost optimization, automation, and resilient microservices supporting enterprise AI workloads
• Implement zero-trust security with automated compliance enforcement and regulatory validation for enterprise AI

• Basic familiarity with the topic and its common terminology
• Readiness to practice through applied exercises or case-based work