In this course, you will learn new data structures for efficiently storing and retrieving data that is structured in an ordered sequence. Such data includes an alphabetical list of names, a family tree, a calendar of events or an inventory organized by part numbers. The specific data structures covered by this course include arrays, linked lists, queues, stacks, trees, binary trees, AVL trees, B-trees and heaps. This course also shows, through algorithm complexity analysis, how these structures enable the fastest algorithms to search and sort data.
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Université de l'Illinois à Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
Programme du cours : ce que vous apprendrez dans ce cours
Orientation; Linear Structures
Introduction to Tree Structures
Advanced Tree Structures
Heap Structures
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Meilleurs avis pour ORDERED DATA STRUCTURES
It covers a lot of material in a short span of time, so retention is key. Make sure to take a lot of notes and give yourself some time to really process all the material from each week.
Really good course so far. Using VSC + git bash on a Windows 10 machine for the programming assignments, and the web-based compiler for the challenges. Really good experiences so far.
My favorite Coursera specialization! Responsive staff, lectures are very clear, assignments are both challenging and educational (closely related to lecture materials). Thank you!
Was a bit fast for me to catch at first, but I eventually got the hang of the pace. Loved the resources the instructor provided. Illinois is lucky to have such a great educator.
À propos du Spécialisation Accelerated Computer Science Fundamentals
Topics covered by this Specialization include basic object-oriented programming, the analysis of asymptotic algorithmic run times, and the implementation of basic data structures including arrays, hash tables, linked lists, trees, heaps and graphs, as well as algorithms for traversals, rebalancing and shortest paths.

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