Advanced Learning Path Recommendation Engine

Design a sophisticated recommendation system for personalized student learning paths using collaborative filtering and content-based algorithms. Develop a Python-based system that analyzes student performance data, course interactions, and skill progression to generate dynamic, adaptive learning recommendations. Implement matrix factorization techniques, create a scoring mechanism for recommendation confidence, and develop a modular system that can integrate with existing learning management platforms.