Learning Outcomes Explain fundamental concepts for algorithmic searching and sorting Describe heap data structures and analyze heap components, such as arrays and priority queues Design basic ...

Catalog : EECE.3220 Data Structures (Formerly 16.322) Id: 003179 Credits Min: 3 Credits Max: 3 Description Covers algorithms and their performance analysis, data structures, abstraction, and ...

Tour of the most important data structures, fundamental algorithms, and algorithm design techniques: lists, stacks, queues, dynamic arrays, hash tables, priority queues, disjoint set unions, binary ...

Description The design, implementation, and analysis of abstract data types, data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and ...

An introduction to the analysis and implementation of algorithms and data structures including linear data structures, trees, graphs, hash tables, searching algorithms, sorting algorithms, ...

Learn when and how to use different data structures and their algorithms in your own code. This is harder as a student, as the problem assignments you'll work through just won't impart this knowledge.

A Merkle tree is a data encryption structure used in data management applications where data is sent through a hashing algorithm in different ways to create a hash that represents all of the data ...

Brief Description of Course Content Studies data abstractions (e.g., stacks, queues, lists, trees) and their representation techniques (e.g., linking, arrays). Introduces concepts used in algorithm ...

Maybe. Hashing refers to the process of using an algorithm to transform data of any size into a unique fixed sized output (e.g., combination of numbers). To put it in layman’s term, some piece ...

A hash is a mathematical function that maps data of arbitrary size to a fixed-size value that is encrypted.