Unordered Data Structures

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.This Specialization sequence is designed to help prospective applicants to the flexible and affordable Online Master of Computer Science (MCS) and MCS in Data Science prepare for the Online MCS Entrance Exam. The Online MCS Entrance Exam allows applicants who do not have graded and

( 11 Reviews )

Created by: Wade Fagen-Ulmschneider

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 98 / 100

Live Chat with CourseDuck's Co-Founder for Help

Need help deciding on a data structures and algorithms course? Or looking for more detail on Wade Fagen-Ulmschneider's Unordered Data Structures? Feel free to chat below.

Join CourseDuck's Online Learning Discord Community

Course Description

The Unordered Data Structures course covers the data structures and algorithms needed to implement hash tables, disjoint sets and graphs. These fundamental data structures are useful for unordered data. For example, a hash table provides immediate access to data indexed by an arbitrary key value, that could be a number (such as a memory address for cached memory), a URL (such as for a web cache) or a dictionary. Graphs are used to represent relationships between items, and this course covers several different data structures for representing graphs and several different algorithms for traversing graphs, including finding the shortest route from one node to another node. These graph algorithms will also depend on another concept called disjoint sets, so this course will also cover its data structure and associated algorithms.

Time: 16h

Instructor Details

Wade Fagen-Ulmschneider

4.9 Rating
11 Reviews

Wade Fagen-Ulmschneider is a Teaching Assistant Professor of Computer Science at The University of Illinois at Urbana-Champaign (UIUC). With a passion for data, he serves as the lead instructor of CS 225 (Data Structures) and works with students on numerous data visualizations that have accumulated over 10,000,000 interactions. In 2016, he was selected as one of the National Academy of Engineering's Frontiers of Engineering Education scholars; in 2017, he was awarded the Collins Award for Innovative Teaching; and he has been consistently ranked as an excellent instructor by his students for the past ten years.

Reviews

4.9

11 total reviews

5 star 4 star 3 star 2 star 1 star

Write a Review

By Nicholas L on 2-Jun-19

Thanks for offering this challenging course!

By ASHUTOSH T on 23-Oct-19

Good course with good exercises.

By Anil N on 5-Oct-19

The lecturer is super excellent and super clear. I wish he has more courses here.

By �� on 16-Sep-19

Very Challenging course. Learned a lot, very clear instruction. Assignments were interesting and challenging.

By Giri on 7-Oct-19

The third course in the specialization was quite dense, but the instructor did a great job providing a sufficiently clear overview + detail; the assignments are fun and interesting. Would be good to have more opportunities to code.

By Leonid M on 30-Aug-19

Excellent course! Looking forward to a more advanced course from the same course staff!

By Ravi A on 11-Oct-19

One of the best online classes I have ever had! That said, this is probably not a course for someone who don't know data structures already. I learned data structures and algorithms a couple years ago and had done many interview algorithm problems so this series of courses help me to review things I know in C++. Nevertheless, great course design, great material and incredible presentation by the instructor!

By M M Z on 28-Oct-19