Retrieval-Backed Course Material Generator for Banking Education

Added Nov 2025 3 design docs

Trainers and educators in financial services spend enormous effort producing course notes, quizzes, and explanations for every topic they teach, and the material dates quickly as products and regulations change. A generator that assembles fresh, accurate learning content from a maintained resource library changes the economics of banking education.

The intern builds this generator in python with a streamlit interface. Educational resources, including articles, definitions, and worked examples, are embedded and stored in a vector database. When a user enters a banking topic or uploads their own learning materials, a retrieval-augmented generation pipeline gathers the most relevant source content and generative AI composes tailored outputs: explanatory lessons, topic summaries, and quiz questions with answers. Because generation is grounded through RAG in the stored resources, the produced material reflects the curated corpus rather than the model's unverified memory, and users can regenerate or refine content interactively.

The project teaches content pipeline design, grounded generation for educational quality, and quiz construction logic, giving the intern a strong demonstration of AI applied to learning-content operations in a regulated domain.

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