Building Generative AI Applications with Python

Generative artificial intelligence is transforming how we interact with technology, opening up incredible opportunities for software developers. If you want to move beyond using AI tools and start building your own intelligent applications, mastering the integration of large language models is the essential next step. This text-based course guides you through the foundational concepts and practical steps of developing AI-powered software. You will learn how to connect Python applications to advanced language models, structure prompts effectively, and create functional user interfaces for your AI tools. What you'll learn: - Understand the core concepts of large language models and generative AI architecture - Apply prompt engineering techniques to guide model behavior and improve output quality - Build interactive conversational interfaces using Gradio and Flask - Configure application workflows with LangChain to chain multiple LLM tasks together - Implement Retrieval-Augmented Generation (RAG) patterns to connect models to custom data sources - Manage API integrations securely and handle model responses in Python The course begins with key terminology and foundational AI concepts before guiding you through written code implementations and practical application architecture. You will progress from simple text generation to building structured chatbots, summarizers, and translation tools through detailed explanations and code analysis. This course is designed for beginner to intermediate Python developers who want to enter the world of AI development. No prior machine learning or AI experience is required. Start reading today to begin building your own generative AI applications.