Personalized Learning Path Recommendation Engine

Create an advanced machine learning recommendation system that generates personalized learning paths for students based on their academic profile, learning style, and performance history. Develop a collaborative filtering algorithm that can integrate multiple data sources, including assessment results, course completion rates, and skill acquisition metrics. Implement a sophisticated feature engineering pipeline that can handle both structured and unstructured data, with explicit techniques for handling cold-start problems and maintaining recommendation diversity.