Generative AI Solutions with Red Hat AI

Enterprises are rapidly adopting generative AI to boost productivity, enhance customer experiences, and automate complex workflows. To succeed in this landscape, you need to understand how to build and deploy these intelligent applications securely and scale them effectively. This course guides you from the fundamental concepts of enterprise AI to the practical application of generative models within a modern infrastructure. By completing this text-only course, you will transition from understanding basic AI theory to confidently planning and structuring enterprise-grade generative AI workflows. You will gain a clear grasp of how to leverage open-source models, manage deployment environments, and align AI capabilities with business objectives. What you'll learn: - Understand the core architecture and components of Red Hat AI for enterprise applications - Identify and design high-impact generative AI use cases for customer support and workflow automation - Apply Retrieval-Augmented Generation (RAG) patterns to ground models in secure business data - Evaluate and select appropriate open-source foundation models for specific operational needs - Configure secure deployment environments using modern containerized infrastructure and Kubernetes principles - Implement basic monitoring and observability patterns to track model performance and reliability The course begins with foundational definitions, key terminology, and an introduction to enterprise AI architecture. Next, you will explore real-world use cases, step-by-step implementation patterns, and best practices for scaling and securing your AI workflows. This course is designed for IT professionals, system administrators, software developers, and technology decision-makers who are new to Red Hat AI and want to build a solid foundation in enterprise generative AI. No prior experience with machine learning is required. Start reading today to unlock the potential of enterprise generative AI with Red Hat AI.