Data structures offer different ways to store data items, while the algorithms provide techniques for managing this data. Application Data Computing applications use many different types of data.

The data structures and algorithms you use critically affect two factors in your applications: Memory usage (for data structures). CPU time (for algorithms that interact with those data structures).

An introduction to the analysis and implementation of algorithms and data structures including linear data structures, trees, graphs, hash tables, searching algorithms, sorting algorithms, ...

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.

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 ...

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 ...

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 ...

CSCA 5454: Advanced Data Structures, RSA and Quantum Algorithms Note that you do NOT need to complete all five courses within this specialization to earn admission to the Online MS-CS degree. However, ...