Core Concepts of Artificial Intelligence Systems

Many modern careers require a basic understanding of how Artificial Intelligence operates, but diving into the technical details can be overwhelming. This course provides a clear, conceptual foundation for understanding AI systems, focusing on the core components, processing methods, and practical applications. By the end, you will be able to confidently discuss AI capabilities, differentiate between various system types, and identify opportunities for integrating intelligent solutions into your work. What you'll learn: * Understand the core concepts and historical context of Artificial Intelligence and Machine Learning. * Differentiate between various AI system types, including expert systems, knowledge-based systems, and modern generative models. * Analyze the typical architecture and workflow of an AI system, from data ingestion to decision output. * Apply basic principles of prompt engineering to effectively interact with and steer large language models (LLMs). * Evaluate the foundational ethical considerations and potential biases inherent in deploying AI systems in professional settings. This course begins by defining key terminology and exploring the evolution of AI. It then transitions into detailed explanations of system components, covering data processing, model types, and common deployment patterns. The final sections focus on practical application and responsible AI use. This course is designed for absolute beginners, managers, and professionals who need a conceptual understanding of AI systems without requiring prior programming or advanced technical knowledge. No prerequisites are required. Start building your foundational knowledge of the technology shaping the future of business and industry today.