Foundations of Agentic AI and Autonomous Systems

As artificial intelligence evolves from simple chat interfaces to autonomous systems, understanding how these agents operate is becoming a critical skill for modern professionals. Moving beyond basic prompts requires a grasp of how systems can reason, plan, and act independently to achieve complex goals. You will transition from a basic understanding of AI to a strategic fluency in agentic workflows. By reading through detailed explanations and logic-based exercises, you will learn to evaluate where autonomous systems can be most effective and how to guide their implementation within a business context. What you'll learn: - Define the core architecture of agentic systems and how they differ from standard language models. - Understand the principles of agentic reasoning, including multi-step planning and iterative self-correction. - Explore how agents interact with the physical and digital world through tool use and API integration. - Analyze Retrieval-Augmented Generation (RAG) patterns and their role in grounding agentic behavior with real-world data. - Evaluate high-value business use cases where autonomous agents drive significant operational efficiency. - Identify performance metrics, safety guardrails, and ethical considerations for agent-led initiatives. - Practice designing agentic workflows through written conceptual exercises and logic frameworks. This course begins with essential terminology and foundational definitions of agency before moving into the logic of planning, tool selection, and multi-agent collaboration patterns. You will gain the vocabulary and conceptual depth needed to lead AI initiatives and collaborate with technical teams. This course is designed for beginners, business leaders, and curious professionals who want to understand the next wave of automation. No prior programming or technical background is required. Start building your fluency in the next generation of artificial intelligence today.