Data Structures

This module introduces the fundamental building blocks of data structures including arrays, linked lists, stacks, and queues. The module covers how trees are used in Computer Science, implementation techniques, and various tree traversal methods.

This module covers dynamic arrays and amortized analysis techniques. Topics include strategies for resizing arrays when the number of elements is unknown ahead of time, and methods for determining amortized cost of operations over a sequence of operations.

This module covers priority queues for efficient job scheduling and file sorting, and disjoint sets for dynamic graph connectivity and image processing. Topics include implementations in C++, Java, and Python, storing complete binary trees in arrays, and efficient algorithms for both data structures.

This module explores hashing techniques and their applications in programming languages, file systems, pattern search, and distributed key-value storage. Topics include implementing hash tables with O(1) amortized running time, data structures for storing and modifying sets and mappings, and practical applications like Dropbox file management.

This module studies binary search trees for performing searches on dynamically changing ordered sets. Topics include the basic structure of binary search trees, insertion and deletion operations while maintaining tree structure, and strategies for ensuring tree balance.

This module continues studying binary search trees with focus on non-trivial applications and Splay Trees. Topics include advanced binary search tree applications and Splay Trees which adapt to queries dynamically and are optimal in many ways.