Generative AI Fundamentals for Developers

As artificial intelligence transforms how we build software, understanding the core concepts of generative AI is no longer optional for modern developers. This text-based course guides you from absolute beginner to confidently integrating AI tools into your daily programming workflow. You will transition from simply using AI chat interfaces to understanding how Large Language Models (LLMs) and Small Language Models (SLMs) operate under the hood. You will learn to write precise prompts, explore modern retrieval patterns, and understand how to manage AI models within a development lifecycle. What you'll learn: First, learn the fundamental terminology of generative AI, neural networks, and transformer models. Second, master prompt engineering techniques to generate clean, reliable code and documentation. Third, understand the differences between Large Language Models (LLMs) and Small Language Models (SLMs). Fourth, explore Retrieval-Augmented Generation (RAG) concepts and how vector databases connect models to external data. Fifth, apply basic MLOps concepts to deploy, monitor, and optimize local and cloud-based AI tools. Sixth, practice integrating AI-assisted workflows safely and securely into your software development lifecycle. The course begins with essential definitions and foundational AI concepts before moving step-by-step into practical prompt engineering, model selection, and modern integration patterns. You will solidify your learning through written explanations, conceptual analysis, and structured code exercises. This course is designed for beginner developers, software engineers, and tech enthusiasts who want a solid, practical understanding of generative AI. No prior experience with artificial intelligence or machine learning is required. Start reading today to unlock the potential of generative AI in your development projects.