AI Operations
Run AI systems reliably in production. From deployment and monitoring to incident response and cost management—practical guidance for operating AI at scale. Essential for platform teams, SREs, and anyone responsible for AI system reliability.
AI Cost Management: Controlling AI Spending
IntermediateLearn to manage and optimize AI costs. From usage tracking to cost optimization strategies—practical guidance for keeping AI spending under control.
AI Deployment Lifecycle: From Development to Production
IntermediateLearn the stages of deploying AI systems safely. From staging to production—practical guidance for each phase of the AI deployment lifecycle.
AI Incident Response: Handling AI System Failures
IntermediateLearn to respond effectively when AI systems fail. From detection to resolution—practical procedures for managing AI incidents and minimizing harm.
Monitoring AI Systems in Production
IntermediateProduction AI requires continuous monitoring. Track performance, detect drift, alert on failures, and maintain quality over time.
MLOps for LLMs
AdvancedApply MLOps practices to LLMs: versioning, CI/CD, monitoring, incident response, and lifecycle management for production AI.