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.
Acerca de este Curso
Universidad de Illinois en 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.
- 5 stars83,65 %
- 4 stars12,61 %
- 3 stars2,44 %
- 2 stars0,77 %
- 1 star0,51 %
Principales reseñas sobre ORDERED DATA STRUCTURES
Excellent course, excellent teacher. Just the right approach to teaching data structures, Ive seen a few videos in the topic and this course is very good.
Nice course, challenging. A little bit dense and fast though. But I learned a lot of things for a person who has no computer science background.
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.
The course is not easy, but really worthy the effort. I learned what I used to think was impossible for me. Great course, the materials are incredible.
Acerca de Programa especializado: 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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