Agentic AI with Red Hat AI for Beginners

Artificial intelligence is shifting from simple chat interfaces to autonomous systems that can plan, use tools, and solve complex problems with minimal human intervention. To leverage this power in enterprise environments, you need a robust, secure, and scalable platform. This written course introduces you to the core principles of Agentic AI using Red Hat AI technologies, preparing you to build next-generation automation workflows. In this course, you will transition from understanding basic machine learning concepts to architecting autonomous agent workflows. You will explore how to leverage open-source foundation models, configure tool-use capabilities, and deploy secure agentic systems within an enterprise infrastructure. What you'll learn: - Understand the core architecture of Agentic AI and how it differs from traditional LLM applications - Navigate the Red Hat AI ecosystem, including Enterprise Linux AI and OpenShift AI platforms - Configure foundation models to autonomously plan tasks, call external APIs, and use tools - Implement retrieval-augmented generation (RAG) to ground your agents in secure enterprise data - Deploy, monitor, and scale agentic workflows using modern container-native infrastructure - Apply ethical AI guardrails and security best practices to manage agent autonomy safely Starting with foundational AI concepts and architecture definitions, this text-based guide takes you step-by-step through configuring models, designing multi-agent collaboration patterns, and deploying them to a secure enterprise cluster. This course is designed for software developers, system administrators, and IT professionals new to autonomous AI systems. No previous machine learning experience is required, though basic familiarity with Linux command-line concepts is helpful. Start reading today to build and deploy secure, autonomous AI agents for your organization.