Predictive AI Use Cases with Red Hat AI

Organizations today sit on mountains of data, but the real value lies in anticipating what comes next. Predictive AI allows you to connect historical events with real-time data streams to project future trends with precision. This text-based course guides you through the foundational concepts of predictive modeling and demonstrates how to apply them using Red Hat AI solutions. You will learn how to identify high-value business cases, prepare your data for machine learning, and understand the workflow of deploying predictive models. We also explore modern MLOps principles and containerized model deployments to keep your predictive workflows reliable and scalable. What you'll learn: - Understand the core concepts of predictive AI and how it differs from generative AI - Identify and evaluate viable business use cases for predictive modeling in your organization - Explore the Red Hat AI ecosystem and its tools for data science workflows - Learn how to prepare, clean, and structure historical data for model training - Discover modern MLOps practices for deploying and monitoring predictive models - Analyze real-world scenarios including demand forecasting and anomaly detection The course begins with essential terminology and the mathematical foundations of predictive analysis, ensuring you have a solid grasp of the basics before moving into architecture and practical business scenarios. You will progress through step-by-step conceptual guides and structured text explanations that illustrate how to design and manage predictive pipelines. This course is designed for business analysts, aspiring data scientists, and IT professionals who are new to artificial intelligence and want to understand how to leverage predictive models. No prior machine learning experience is required. Start reading today to unlock the forecasting power of predictive AI for your organization.