Building Real-Time AI and ML Solutions with InterSystems IRIS

Modern industrial and enterprise systems generate massive amounts of data that must be analyzed in real time to prevent failures and optimize operations. The InterSystems IRIS platform provides the perfect foundation for embedding artificial intelligence and machine learning directly into your transactional workflows. This course guides you through the foundational concepts of building, deploying, and managing real-time AI and machine learning applications. You will transition from understanding basic database architectures to designing predictive workflows that monitor equipment health, detect anomalies, and automate decision-making. What you will learn: Understand the foundational architecture of the InterSystems IRIS data platform and its multi-model capabilities; Integrate diverse data sources including SCADA, IoT devices, and enterprise ERP systems; Deploy predictive machine learning models using Python and modern data science runtimes within the database; Configure hybrid transaction-analytical processing to handle high-throughput real-time data streams; Design adaptive business processes that support continuous model learning and automated feedback loops; Expose analytical insights to external systems through secure API management and integration workflows. The journey begins with the absolute basics of the platform's architecture and data ingestion strategies. You will then progress through step-by-step written explanations on embedding analytical models, orchestrating real-time decisions, and distributing results to operational systems. This course is designed for software developers, data analysts, and system integrators who are new to InterSystems IRIS. No prior experience with the platform is required, though a basic understanding of programming concepts is helpful. Start reading today to unlock the power of real-time predictive analytics in your enterprise applications.