Personalized Learning Pathway Planner for Banking Students

Two people studying banking rarely need the same course: a new teller, a compliance trainee, and a fintech founder each need different topics in a different order. Static curricula cannot adapt to that, but a generator that assembles a personalized pathway from stated goals can.

The intern builds the planner in python. Users select banking topics or describe their learning goals, and the system generates a structured pathway: an ordered sequence of topics, an explanation of each step, and quizzes to check understanding along the way. Langgraph manages the multi-stage flow from goal interpretation to pathway assembly to quiz creation, while an agentic-ai layer coordinates the stages and revisits weak sections, and generative AI through openai models writes the explanations and question sets. The output is a complete, structured learning plan with accompanying assessments, delivered as organized documents a learner or trainer can follow directly.

The project teaches curriculum decomposition, AI-driven content generation with consistent structure, and workflow automation. The intern comes away with a substantial artifact demonstrating that they can direct language models to produce organized educational programs rather than isolated answers.