Course Notes Archive

This archive preserves course notes, assignments, exam reviews, and project records from my undergraduate and graduate studies. Unlike the curated Algorithms, AI Systems, CS Foundations, and Software Engineering maps, these pages follow the chronology and vocabulary of individual courses.

Study Stages

Stage	Focus	Entry
Undergraduate	AI foundations, deep learning, discrete mathematics, blockchain, recommender systems, and XR	Bachelor Courses
Graduate	Systems, theory, machine learning, graphics, animation, perception, and technology entrepreneurship	Graduate Courses

How to Use This Archive

• Use each course overview as the map for its lectures, assignments, projects, and exam material.
• Treat grades, schedules, and administrative details as historical records rather than current course policy.
• Follow links into the curated knowledge base when you want a topic-centered explanation rather than semester notes.
• Course pages may mix English and Chinese because they preserve how the material was originally studied.

Knowledge Maps

For polished, continuously maintained material, start with:

• Algorithms for problem-solving patterns and data structures;
• AI Systems for machine learning, foundation models, evaluation, and production AI;
• CS Foundations for operating systems, networks, and system design;
• Software Engineering for languages, data systems, delivery, testing, and operations.