All of the data structures we’ll look at in this series are aggregates. Containers. Anything from which data items are stored and retrieved could be considered a data structure.

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

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

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.

It’s a very common programming task to search a singly linked list for specific data items. While the Linear Search algorithm (introduced in Part 2) is most frequently used for this type of task ...

Specialization: Data Science Foundations: Data Structures and Algorithms Instructor: Sriram Sankaranarayanan, Assistant Professor Prior knowledge needed: Mathematical Background: We expect that the ...

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 search ...

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

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 ...