Data Structures Fundamentals

In this module, you will learn about the basic data structures used throughout the rest of this course. We start this module by looking in detail at the fundamental building blocks: arrays and linked lists. From there, we build up two important data structures: stacks and queues. Next, we look at trees: examples of how they're used in Computer Science, how they're implemented, and the various ways they can be traversed.

This module discusses Dynamic Arrays and their implementation when the number of elements is unknown beforehand. The focus is on amortized analysis methods for determining operation costs over sequences, particularly useful for analyzing Dynamic Arrays performance and later applications in Splay trees

This module covers priority queues for efficient job scheduling and file sorting in Big Data processing, implementing complete binary trees in arrays. It also introduces disjoint sets data structure used in dynamic graph connectivity and image processing, teaching implementation techniques that are both efficient and easy to code

This module introduces hashing techniques with applications in programming languages, file systems, and pattern search. Students learn to implement data structures for storing and modifying sets of objects and mappings, focusing on efficient memory usage and O(1) average performance

This module continues the exploration of hash tables, focusing on advanced implementation techniques and practical applications in distributed key-value storage. Students learn to optimize hash table performance and handle collision resolution while maintaining efficient memory usage

This module covers binary search trees for performing searches on dynamically changing ordered sets. Students learn about tree structure, insertion and deletion operations, and techniques for maintaining tree balance. The course covers specific implementations including AVL trees and Splay trees