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.
This course is part of the Accelerated Computer Science Fundamentals Specialization
Offered By
Accelerated Computer Science Fundamentals SpecializationUniversity of Illinois at Urbana-ChampaignAbout this Course
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Course 2 of 3 in the
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Approx. 19 hours to complete
English
Subtitles: English
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 3 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 19 hours to complete
English
Subtitles: English
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
8 hours to complete
Orientation; Linear Structures
8 hours to complete
6 videos (Total 64 min), 6 readings, 4 quizzes
6 videos
1.1 Arrays11m
1.2 Linked Memory11m
1.3 Run Time Analysis13m
1.4 Array and List Operations10m
1.5 Queue (Data Structure)8m
1.6 Stack (Data Structure)8m
6 readings
Syllabus10m
Additional References for C++10m
Week 1 Overview10m
Downloading the Example C++ Source Code for Lecture with Git15m
Important Tips and Notes for All Challenge Problems10m
Guidelines for Asking for Help With Code10m
3 practice exercises
Orientation Quiz5m
Week 1 Quiz30m
Week 1 Challenge30m
2 hours to complete
Introduction to Tree Structures
2 hours to complete
5 videos (Total 54 min), 1 reading, 2 quizzes
5 videos
2.2 Binary Trees8m
2.3 Tree Traversals8m
2.4 Binary Search Trees19m
2.5 BST Analysis9m
1 reading
Week 2 Overview10m
2 practice exercises
Week 2 Quiz30m
Week 2 Challenge30m
7 hours to complete
Advanced Tree Structures
7 hours to complete
5 videos (Total 34 min), 1 reading, 3 quizzes
5 videos
3.1.2 AVL Analysis8m
3.2.1 B-Tree Introduction3m
3.2.2 B-Tree Insert7m
3.2.3 B-Tree Search4m
1 reading
Week 3 Overview10m
2 practice exercises
Week 3 Quiz30m
Week 3 Challenge30m
2 hours to complete
Heap Structures
2 hours to complete
5 videos (Total 30 min), 1 reading, 2 quizzes
5 videos
4.2 Heap Insert6m
4.3 Heap - RemoveMIN5m
4.4 Heap - buildHeap5m
4.5 Heap - Runtime Analysis3m
1 reading
Week 4 Overview10m
2 practice exercises
Week 4 Quiz30m
Week 4 Challenge30m
Reviews
TOP REVIEWS FROM ORDERED DATA STRUCTURES
by MCJul 26, 2020
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.
by JTJan 20, 2020
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.
by HNAug 24, 2019
My favorite Coursera specialization! Responsive staff, lectures are very clear, assignments are both challenging and educational (closely related to lecture materials). Thank you!
by RRJul 15, 2020
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.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.
More questions? Visit the Learner Help Center.
