Understand the principles of efficient algorithms for dealing with large scale data sets and be able to select appropriate algorithms for specific problems. Understand and be able to apply the main ...

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, ...

A language that's data-intensive naturally should have a way to dig into the data effectively. Here's a look at some of the R functions for searching and sorting through it all. Searching and sorting ...

GPU-based sorting algorithms have emerged as a crucial area of research due to their ability to harness the immense parallel processing power inherent in modern graphics processing units. By ...

Have you ever thrown around the word algorithm without knowing what it means? When people complain about the Facebook algorithm, the Netflix algorithm, or the Google search algorithm, they don’t ...

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 ...

Think of Google Photos as Gmail for pictures, said Google vice president Bradley Horowitz. Before Gmail existed, Horowitz recalled, he’d obsessively file away every email. But as the emails started to ...

Application of object-oriented techniques for systematic problem analysis and specification, design, coding, testing, and documentation. Semester-long project approach emphasizing larger programs.

We’re suckers for the kind of “life hacks” that tell you that you’ve been doing some relatively mundane task all wrong, and that there’s a super-easy alternative which can massively speed up your ...