Building Large Language Model (LLM) Applications with Legal Tech

Large Language Models are transforming how we process text, analyze documents, and automate complex workflows across industries. Understanding how to harness these models effectively is becoming an essential skill for modern developers and domain professionals. This comprehensive, text-based course guides you from the foundational concepts of generative AI to building practical, specialized applications. You will learn how to structure precise prompts, integrate semantic search, and implement Retrieval-Augmented Generation (RAG) to solve complex problems, with a dedicated focus on legal technology use cases. What you'll learn: 1. Understand the core architecture, terminology, and capabilities of modern Large Language Models. 2. Master prompt engineering techniques to generate consistent, structured, and accurate outputs. 3. Configure vector databases to perform semantic search over custom document collections. 4. Implement Retrieval-Augmented Generation (RAG) patterns to ground model responses in real data. 5. Apply LLM workflows to legal tech scenarios, including contract review and automated summarization. 6. Evaluate model performance and manage basic operational considerations for AI applications. The course begins with essential definitions and foundational AI concepts before introducing practical code patterns and implementation strategies. Through clear written explanations and structured code snippets, you will build a solid understanding of how to orchestrate LLM systems from scratch. This course is designed for beginners, aspiring AI developers, and legal or business professionals looking to leverage language models in their workflows. No prior background in artificial intelligence is required. Start reading today to master the fundamentals of LLM application development.