About this Course

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Flexible deadlines
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Approx. 21 hours to complete
English
Subtitles: English
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 21 hours to complete
English
Subtitles: English

Offered by

University of Illinois at Urbana-Champaign logo

University of Illinois at Urbana-Champaign

Syllabus - What you will learn from this course

Week
1

Week 1

8 hours to complete

Orientation; Hashing

8 hours to complete
7 videos (Total 43 min), 5 readings, 4 quizzes
7 videos
Lesson 1.1.2 Hashing - Hash Function10m
Lesson 1.1.3 Hashing - Hash Function Examples4m
Lesson 1.1.4 Collision Handling I: Separate Chaining4m
Lesson 1.1.5 Collision Handling II: Probing and Double Hashing12m
Lesson 1.1.6 Hashing Analysis3m
Lesson 1.1.7 Hash Tables in C++2m
5 readings
Syllabus10m
Additional References for C++10m
Week 1 Overview10m
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 Challenge Problem30m
Week
2

Week 2

3 hours to complete

Disjoint Sets

3 hours to complete
6 videos (Total 32 min), 2 readings, 2 quizzes
6 videos
2.1.2 Disjoint Sets: Naive Implementation4m
2.1.3 Disjoint Sets: UpTrees - A Better Implementation6m
2.1.4 UpTrees: Simple Running Time3m
2.1.5A UpTrees: Smart Union & Path Compression I8m
2.1.5B UpTrees: Smart Union & Path Compression II4m
2 readings
Week 2 Overview10m
Terminology Note: "Disjoint Sets" and "Union-Find"1m
2 practice exercises
Week 2 Quiz1h
Week 2 Challenge Problem1h
Week
3

Week 3

7 hours to complete

Graph Data Structures

7 hours to complete
5 videos (Total 35 min), 1 reading, 3 quizzes
5 videos
3.1.2 Graphs: Vocabulary8m
3.1.3 Graphs: Edge List Implementation4m
3.1.4 Graphs: Adjacency Matrix Implementation6m
3.1.5 Graphs: Adjacency List Implementation8m
1 reading
Week 3 Overview10m
2 practice exercises
Week 3 Quiz30m
Week 3 Challenge Problem1h
Week
4

Week 4

3 hours to complete

Graph Algorithms

3 hours to complete
11 videos (Total 75 min), 1 reading, 2 quizzes
11 videos
4.1.2 Graphs: BFS Analysis9m
4.1.3 Graphs: DFS Traversal8m
4.2.1 Minimum Spanning Trees (MST) Introduction2m
4.2.2 MST: Kruskal's Algorithm I6m
4.2.3 MST: Kruskal's Algorithm II5m
4.2.4 MST: Prim's Algorithm9m
4.3.1 Graphs: Dijkstra's Algorithm6m
4.3.2 Graphs: Dijkstra's Edge Cases8m
4.3.3 Graphs: Dijkstra's Running Time2m
4.3.4 Graphs: Landmark Path Problem7m
1 reading
Week 4 Overview10m
2 practice exercises
Week 4 Quiz30m
Week 4 Challenge Problem1h

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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. 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 transcripted prerequisite CS coursework in the areas of data structures, algorithms, and object-oriented programming to strengthen their applications for admission. Learn more about the Online MCS Entrance Exam....
Accelerated Computer Science Fundamentals

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