This course is a practical guide to building intelligent, document-driven ChatGPT chatbots using LangChain and the OpenAI API. Designed for developers and AI enthusiasts, it focuses on integrating custom data sources like text files and Excel CSVs to create personalized conversational AI experiences.

Learners start by understanding LangChain and its role in connecting AI models to external datasets. The course then demonstrates step-by-step how to create Q&A systems that answer questions from user-provided documents. Students learn how to preprocess and load data efficiently, manage context, and optimize prompt designs for accurate and relevant responses.

Hands-on tutorials include building a ChatGPT system that reads from text documents and another that answers questions using Excel CSV files. Emphasis is placed on clean code, modular design, and scalability so that these chatbots can handle real-world data and grow with additional datasets.

By the end of the course, learners will be able to create fully functional, data-driven AI assistants using LangChain and OpenAI API. This course is ideal for developers, data scientists, and anyone looking to build advanced, custom AI chatbot solutions.