This advanced course explores fundamental and advanced data structures used in computer science, focusing on binary search trees (BSTs), symbol tables, and self-balancing tree structures.

The course begins with ordered operations in binary search trees, explaining how to efficiently find minimum, maximum, floor, and ceiling values. These operations are essential for working with sorted data and optimizing search performance.

It then covers deletion in BSTs, demonstrating how key-value pairs are removed while maintaining tree structure and performance. This is a critical concept in maintaining efficient data structures in dynamic systems.

The course also introduces symbol tables and advanced tree structures such as 2-3 trees and red-black trees. These structures are used to maintain balanced search performance even as data is inserted and deleted frequently.

A key focus is red-black trees, including their design, balancing rules, and left-leaning variants, which improve efficiency in implementing symbol tables and ordered data storage systems.

Finally, the course highlights practical applications of red-black trees in real-world computing systems, showing how these data structures are used in databases, compilers, and large-scale software systems.

By the end of this course, learners will have a strong understanding of advanced tree-based data structures and their applications in efficient computing.