Building Generative AI Applications with LangChain and LLMs

The rise of large language models has changed how software is built, making it essential for developers to understand how to integrate AI into functional applications. This course provides a structured path from understanding core AI concepts to building responsive, tool-aware systems that solve real-world problems. You will transition from a basic understanding of model interactions to creating complex, automated workflows that can reason and act. By focusing on the logic behind AI orchestration, you will gain the skills needed to develop modern, scalable AI solutions. What you'll learn: - Understand foundational concepts of Large Language Models and their underlying architecture. - Apply advanced prompt engineering techniques like chain-of-thought and in-context learning. - Create and manage reusable prompt templates to ensure consistent application behavior. - Build sophisticated workflows using LangChain components, including chains, tools, and agents. - Practice integrating external data sources using Retrieval-Augmented Generation (RAG) and vector databases. - Configure and compare different model parameters to optimize output quality and handle errors. The curriculum begins with essential terminology and model fundamentals before moving into practical prompt design and complex application orchestration. This course is designed for software developers and tech enthusiasts who are new to AI and want to build practical applications; no prior AI experience is required. Start your journey into AI development today and begin building your first intelligent system.