Build QA Systems with Langchain and Neo4j

In today's information-rich world, extracting precise answers from vast datasets is crucial for effective decision-making. This course equips you with the skills to design and implement intelligent question-answering systems that leverage large language models and structured knowledge bases. What you'll learn: - Understand the fundamentals of Large Language Models (LLMs) and prompt engineering. - Learn to use Langchain for chaining LLM calls and managing application flow. - Implement Retrieval Augmented Generation (RAG) to provide LLMs with external knowledge. - Integrate Neo4j to store and retrieve structured and unstructured data for RAG. - Practice building and evaluating a functional question-answering system. - Explore basic testing strategies and ethical considerations for LLM applications. This course begins with foundational concepts of LLMs and Langchain, then guides you through integrating Neo4j for data management, culminating in the construction of a complete RAG-based QA system. This course is designed for beginners interested in developing AI-powered applications, with no prior experience in LLMs or graph databases required. Begin your journey into building intelligent, data-driven question-answering systems today.