LangChain Basics for Beginners: Build LLM-Powered Applications

Are you looking to build intelligent applications using large language models but do not know where to start? This written course guides you through LangChain, the industry-standard framework for orchestrating LLMs, prompts, and memory into cohesive applications. You will start with the foundational concepts of generative AI orchestration before moving on to practical implementations. By reading through clear, conceptual explanations and structured code snippets, you will learn how to connect models to external data sources, manage conversation history, and build structured workflows. What you'll learn: 1. Understand core LangChain concepts, including models, prompts, parsers, and chains. 2. Build custom workflows using the modern LangChain Expression Language. 3. Implement Retrieval-Augmented Generation to query your own documents and data. 4. Manage conversational state and memory for interactive AI applications. 5. Connect language models to external tools and APIs for dynamic problem-solving. 6. Apply best practices for prompt engineering and structured outputs. You will begin by learning key terminology and basic setup before progressing through step-by-step written tutorials that demonstrate how to construct modular AI components. This course is designed specifically for beginners and developers new to LLM orchestration, requiring only a basic understanding of Python. Start reading today to build your first AI-driven application.