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 ...

Foundations of Data Structures and Algorithms Specialization Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and ...

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.

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 ...

Want to learn more? Click the button below to watch the Data Science Foundations: Data Structures & Algorithms pathway instructor give an overview of the topics covered in this pathway. Watch the ...

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

Like arrays, which were introduced in Part 3 of this tutorial series, linked lists are a fundamental data structure category upon which more complex data structures can be based.

Data structures and algorithms are vital elements in many computing applications. When programmers design and build applications, they need to model the application data.