Generative AI and Large Language Models for Beginners

Generative AI is transforming how we interact with technology, yet the underlying principles often seem opaque. This course demystifies Large Language Models (LLMs) by providing a clear, text-based path from core concepts to practical implementation. You will gain a solid understanding of how these models are built, how they process information, and how to effectively guide them to produce high-quality results for various use cases. What you'll learn: - Understand the fundamental architecture of Large Language Models and the Transformer mechanism - Master prompt engineering techniques to improve the accuracy and relevance of AI outputs - Learn the basics of Retrieval-Augmented Generation (RAG) to connect models with external data - Explore the role of vector databases in managing information for AI applications - Understand ethical considerations, bias, and the limitations of current generative systems - Practice designing workflows that integrate AI into everyday problem-solving The curriculum begins with essential terminology and the history of natural language processing before moving into the technical logic of modern generative tools. You will then progress through structured written explanations and code snippets that cover application design and performance tuning. This course is designed for beginners who want a conceptual and practical introduction to AI without needing a background in data science. Start your journey into the world of generative AI today.