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, ...

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.

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.

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 ...