Foundations of Generative AI: Principles and Applications

Generative artificial intelligence is transforming how we build software, analyze data, and solve complex problems. To stay competitive, you need to understand not just how to use these tools, but the underlying mechanisms that make them work.\n\nThis text-based course guides you from absolute beginner to a confident practitioner capable of designing and evaluating generative AI systems. You will transition from basic concepts to understanding modern architecture patterns, learning how to structure prompts, work with large language models, and integrate foundational AI technologies into real-world workflows.\n\nWhat you'll learn:\n- Understand the core evolution of generative models from basic neural networks to modern transformers\n- Apply effective prompt engineering techniques to guide model behavior and optimize outputs\n- Explore modern architecture patterns including Retrieval-Augmented Generation (RAG) and vector databases\n- Evaluate generative AI system performance, accuracy, and ethical considerations\n- Analyze security risks and bias mitigation strategies in AI deployment\n\nThe course begins with essential terminology and foundational definitions before guiding you through practical design patterns and evaluation frameworks. Through clear written explanations and structured exercises, you will develop a framework for thinking about and implementing AI responsibly.\n\nThis course is designed for beginners, developers, and tech enthusiasts who want a structured introduction to generative AI without needing prior machine learning experience.\n\nStart building your foundational knowledge of generative AI today.