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, ...

Learning outcomes 1 Design, select and implement key data structures in C++. 2 Implement algorithms using these data structures to solve practical problem scenarios. 3 Analyze, compare and classify ...

Quantum Algorithms Prerequisites Undergraduate algorithms (CSCI 3104), data structures (CSCI 2270), discrete mathematics (CSCI 2824) and two semesters of calculus, or equivalents. We will assume that ...

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 ...

Definition of a Data Structure & Algorithms. Data structures and algorithms are vital elements in many computing applications. When programmers design and build applications, they need to model ...

Introduction to the fundamental principles of data structures and algorithms and their efficient implementation. Developing algorithmic thinking. Basic toolkit for the design and analysis 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 ...

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 ...