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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About this Course
Offered by

University of Illinois at 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.
Syllabus - What you will learn from this course
Orientation; Linear Structures
Introduction to Tree Structures
Advanced Tree Structures
Heap Structures
Reviews
TOP REVIEWS FROM 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!
submitting the program assignments for the first time took long and the process was tideous . except that the course content and the instructors explaination all were excellent.
About the Accelerated Computer Science Fundamentals Specialization
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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