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 ...

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, ...

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 ...

How to recognize and use array and list data structures in your Java programs. Which algorithms work best with different types of array and list data structures.

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 ...

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.

22:544:643 Information Security 22:544:603 Business Data Management 22:544:641 Analytics for Business Intelligence (or 22:544:650 Data Mining) 22:544:613 Introduction to Data Structures and Algorithms ...

Tour of the most important data structures, fundamental algorithms, and algorithm design techniques: lists, stacks, queues, dynamic arrays, hash tables, heaps, priority queues, disjoint set unions, ...