Foundations of Artificial Intelligence and Generative AI

Artificial intelligence is transforming every industry, yet grasping how these technologies actually work can feel overwhelming. This course breaks down complex algorithms and modern models into clear, jargon-free written explanations. You will transition from a curious observer to a knowledgeable professional who understands the mechanics behind machine learning, deep learning, and generative AI. By studying foundational definitions and practical conceptual frameworks, you will gain the literacy needed to discuss, implement, and leverage AI technologies in your career. What you'll learn: - Understand foundational AI terminology, including the differences between narrow AI, general AI, and machine learning. - Explore core machine learning paradigms, from supervised and unsupervised learning to neural networks. - Learn the mechanics of modern generative AI, including large language models (LLMs) and transformer architectures. - Practice basic prompt engineering techniques to optimize outputs from generative models. - Discover modern data patterns such as vector databases and retrieval-augmented generation (RAG). - Evaluate ethical considerations, bias, and responsible AI practices in real-world applications. The course begins with essential definitions and historical context before guiding you step-by-step through machine learning concepts, deep learning structures, and cutting-edge generative AI workflows. This course is designed for absolute beginners, business professionals, and aspiring tech enthusiasts who want a solid conceptual grounding in AI without needing a background in advanced mathematics or programming. Start reading today to build a future-proof understanding of artificial intelligence.