Foundations of Generative AI and Large Language Models

As artificial intelligence reshapes how we work and create, understanding the core technology behind conversational and creative tools is essential. This course provides a clear, text-based path to grasping the fundamentals of generative models and their impact on the modern digital world. You will move from a general curiosity about AI to a functional understanding of how these systems are built, trained, and utilized to solve complex problems. By focusing on the underlying logic of these technologies, you will gain the vocabulary and conceptual framework needed to engage with AI professionally. What you'll learn: - Define generative AI and distinguish it from traditional machine learning approaches - Understand the architecture of Large Language Models and how they process human language - Apply basic prompt engineering techniques to improve the quality and accuracy of model outputs - Identify practical use cases for generative tools across various industries and workflows - Explore ethical considerations, including data privacy, bias, and the challenge of hallucinations - Learn about modern integration patterns such as Retrieval-Augmented Generation (RAG) The course begins with essential terminology and foundational definitions before progressing into technical concepts and strategic applications. This structured reading experience ensures you build a solid theoretical base before exploring practical implementation. This course is designed for absolute beginners who want to understand the "why" and "how" behind the headlines. No prior programming or data science experience is required. Start building your knowledge of generative intelligence today.