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, ...

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.

This tutorial launches a short series introducing data structures and algorithms. In Part 1, you’ll learn what a data structure is and how data structures are classified.

Big-O, Big-Omega, Big-Theta notations, and their meanings. Basic data structures: Heaps, and Binary Search Trees. Algorithm Design Approaches: Divide and Conquer including analysis using recurrences ...

Programming languages offer a range of data structure options. When programmers choose data structures for their applications, they consider the nature of the data as well as what the application ...

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 ...