Foundational Generative AI: Core Concepts and Applications

Are you curious about how generative AI actually works behind the buzzwords? This text-based course breaks down the core mechanisms of modern artificial intelligence, helping you transition from a passive observer to an informed decision-maker. Through clear, step-by-step written explanations, you will build a solid mental model of machine learning foundations, large language models, and transformer architectures. You will learn to evaluate AI tools critically and understand how they can be integrated into real-world workflows. What you'll learn: - Understand the fundamental differences between traditional machine learning and generative AI - Explore the inner workings of Large Language Models and transformer architecture - Master basic prompt engineering techniques to get reliable and predictable outputs - Learn the conceptual foundations of Retrieval-Augmented Generation for grounding AI responses - Analyze the ethical implications, bias, and responsible use guidelines of generative technologies - Identify practical use cases for implementing AI solutions in business and creative domains This course begins with essential terminology and foundational definitions before guiding you through the mechanics of neural networks and modern language models. You will progress from theoretical concepts to practical, real-world application strategies through comprehensive reading modules and analytical exercises. This course is designed for absolute beginners, business professionals, and curious learners who want a conceptual understanding of generative AI with zero programming prerequisites. Start reading today to build a confident, future-proof foundation in generative AI.