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, ...

Data structures and algorithms constitute the foundational pillars of computer science. They provide the systematic methods for organising, storing and manipulating data, and offer step-by-step ...

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

I see it time and again in Google interviews or new-grad hires: The way data structures and algorithms — among the most important subjects in a proper computer science curriculum — are learnt is often ...

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 ...

In this module the student will learn the very basics of algorithms through three examples: insertion sort (sort an array in ascending/descending order); binary search: search whether an element is ...

What if the huge design space for data-driven software could be efficiently mapped and explored in order to have tailor-made, optimized solutions? Researchers from Harvard combine analytical models, ...

What makes some good software developers good at building large scale software but weak at data structures and algorithms? originally appeared on Quora: the place to gain and share knowledge, ...