Foundations of Artificial Intelligence: From Classic Models to Generative AI

Artificial intelligence is transforming every industry, yet navigating the vast ecosystem of models, tools, and terminology can feel overwhelming. This course demystifies the core concepts of AI, giving you a clear, structured path from historical foundations to modern generative technologies. You will gain a comprehensive understanding of how AI models work, how they are applied in fields like computer vision and natural language processing, and how to evaluate the economic and ethical implications of AI implementation in business. What you'll learn: Understand the fundamental terminology, history, and classification of AI models and intelligent agents; Explore practical applications of natural language processing (NLP) and computer vision in modern software; Master the basics of generative AI, including prompt engineering principles and retrieval-augmented generation (RAG) patterns; Analyze the economics of AI adoption, including cost structures, resource requirements, and business value; Evaluate ethical considerations, bias, and responsible AI practices in development and deployment. The course begins with foundational definitions and historical context before guiding you through core neural network concepts, specialized domains like NLP and computer vision, and finally, modern generative tools and their real-world economic impact. Designed entirely for beginners, this text-based course requires no prior programming experience or advanced mathematics background. Start reading today and build a future-proof understanding of the AI landscape.