Foundations of AI Engineering

As artificial intelligence reshapes the technology landscape, software developers and tech enthusiasts need to know how to connect applications to intelligent models. Transitioning into AI engineering starts with mastering the foundational concepts, APIs, and integration patterns that power modern software. In this text-based course, you will learn how to bridge the gap between traditional software development and artificial intelligence. You will progress from understanding core AI terms to confidently implementing API calls, working with large language models, and applying advanced techniques like prompt engineering and retrieval-augmented generation. What you'll learn: - Understand the core concepts of artificial intelligence, machine learning, and neural networks. - Configure and authenticate connections to modern AI APIs for text and image generation. - Apply prompt engineering techniques, including few-shot learning and system role definition, to guide model outputs. - Integrate modern AI patterns like Retrieval-Augmented Generation (RAG) and vector database basics into your software. - Build programmatic workflows that handle API responses, error states, and rate limits. The course begins with essential terminology and the mechanics of large language models. You will then study practical text-based guides and code examples that demonstrate how to structure API requests, manipulate parameters, and execute multi-step AI tasks. This course is designed for beginner developers, software engineers, and tech professionals looking to enter the AI space. No prior background in machine learning or data science is required—only basic programming knowledge. Start reading today to begin building your first AI-powered applications.