Developing Generative AI Applications and Agents with Python

Generative AI is transforming how we build software, but moving beyond simple chat interfaces requires understanding how to programmatically orchestrate AI models. This text-based course guides you through the foundational concepts and practical architectures needed to build autonomous agents and smart applications from scratch. You will transition from writing basic prompts to developing sophisticated, stateful AI systems that can reason, use external tools, and access custom knowledge bases. By studying clear conceptual breakdowns and analyzing structured Python code, you will master the core design patterns behind modern AI engineering. What you'll learn: - Understand the foundational mechanics of Large Language Models, APIs, and structured prompt engineering. - Build autonomous AI agents capable of planning tasks, calling external APIs, and executing multi-step workflows. - Implement Retrieval-Augmented Generation (RAG) to connect your applications to custom data using vector databases. - Apply modern Python development patterns, including async/await for efficient API orchestration and robust error handling. - Manage conversational state and agent memory to maintain context over long interactions. The course begins with essential terminology and basic API integration before moving systematically into advanced agent orchestration and semantic search. Through clear written explanations and detailed code walkthroughs, you will build a strong mental model of how production-grade AI applications operate. This course is designed for developers, software engineers, and tech enthusiasts who want to transition into AI engineering. No prior experience with AI APIs is required, though a basic familiarity with Python is recommended. Start reading today to build your first generation of intelligent AI agents.