Programming Generative AI: Build and Integrate AI Applications

Generative AI is transforming software development, but moving past simple prompts requires understanding how these systems work under the hood. To build truly intelligent applications, developers must learn how to programmatically interact with, chain, and customize generative models. This text-only course guides you from the fundamental concepts of neural networks to building your own AI-powered features. You will transition from a consumer of AI tools to a creator who can programmatically manipulate generative models, handle multimodal inputs, and manage context effectively. What you'll learn: Understand the fundamental architecture of neural networks, transformers, and multimodal models; Program generative models using modern Python, implementing asynchronous API calls and clean type hints; Configure Retrieval-Augmented Generation (RAG) patterns to connect models with external data sources; Implement vector databases to store and query high-dimensional embeddings; Apply basic prompt engineering principles programmatically to control model outputs reliably; Design secure AI workflows that handle text, image, and structured data processing. You will start with core definitions and the foundational mechanics of generative modeling. From there, you will read through step-by-step code explanations, exploring how to structure API requests, manage embeddings, and build practical applications. This course is designed for beginner developers who have a basic grasp of Python and want to dive into the engineering side of AI. No prior machine learning or advanced mathematics background is required. Start reading today to unlock the potential of programming generative AI in your own software projects.