Building Generative AI Applications with Python

The demand for software that can comprehend, summarize, and interact with human language is growing rapidly. If you want to transition from writing basic scripts to building intelligent, AI-powered applications, learning how to leverage large language models with Python is the essential next step. This written course guides you through the process of designing and implementing generative AI features. You will transition from understanding core artificial intelligence concepts to constructing functional applications, such as document-querying systems and conversational chat assistants, using modern Python libraries. What you'll learn: Understand the foundational concepts of large language models, APIs, and prompt engineering; Configure virtual environments and modern Python packaging tools for clean project setups; Build document-based question-answering systems using Retrieval-Augmented Generation (RAG) patterns; Integrate vector databases to store and retrieve semantic information efficiently; Implement asynchronous Python code to handle API requests concurrently and improve application performance; Create interactive conversational interfaces that maintain chat history and context. We begin with key terminology and foundational definitions before setting up a modern Python development environment. From there, the text-only lessons guide you step-by-step through practical implementation details, from simple API calls to advanced document retrieval architectures. This course is designed for beginner to intermediate Python programmers who want to enter the field of AI development, with no prior experience in machine learning required. Start reading today to begin building intelligent applications with Python.