The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social network analysis).
Offered By
Algorithms SpecializationStanford UniversityAbout this Course
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Learner Career Outcomes
41%
started a new career after completing these courses
48%
got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 12 hours to complete
English
Subtitles: English
Skills you will gain
GraphsData StructureAlgorithmsHash Table
Learner Career Outcomes
41%
started a new career after completing these courses
48%
got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 12 hours to complete
English
Subtitles: English
Offered by
Stanford University
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Syllabus - What you will learn from this course
4 hours to complete
Week 1
Breadth-first and depth-first search; computing strong components; applications.
4 hours to complete
9 videos (Total 162 min), 4 readings, 2 quizzes
9 videos
Breadth-First Search (BFS): The Basics14m
BFS and Shortest Paths7m
BFS and Undirected Connectivity13m
Depth-First Search (DFS): The Basics7m
Topological Sort21m
Computing Strong Components: The Algorithm29m
Computing Strong Components: The Analysis26m
Structure of the Web [Optional]18m
4 readings
Week 1 Overview10m
Overview, Resources, and Policies10m
Lecture slides10m
Optional Theory Problems (Week 1)10m
2 practice exercises
Problem Set #110m
Programming Assignment #12m
2 hours to complete
Week 2
Dijkstra's shortest-path algorithm.
2 hours to complete
4 videos (Total 79 min), 2 readings, 2 quizzes
4 videos
Dijkstra's Algorithm: Examples12m
Correctness of Dijkstra's Algorithm19m
Dijkstra's Algorithm: Implementation and Running Time26m
2 readings
Week 2 Overview10m
Optional Theory Problems (Week 2)10m
2 practice exercises
Problem Set #210m
Programming Assignment #22m
3 hours to complete
Week 3
Heaps; balanced binary search trees.
3 hours to complete
9 videos (Total 142 min), 1 reading, 2 quizzes
9 videos
Heaps: Operations and Applications18m
Heaps: Implementation Details [Advanced - Optional]20m
Balanced Search Trees: Operations and Applications10m
Binary Search Tree Basics, Part I13m
Binary Search Tree Basics, Part II30m
Red-Black Trees21m
Rotations [Advanced - Optional]7m
Insertion in a Red-Black Tree [Advanced]14m
1 reading
Week 3 Overview10m
2 practice exercises
Problem Set #310m
Programming Assignment #32m
4 hours to complete
Week 4
Hashing; bloom filters.
4 hours to complete
9 videos (Total 171 min), 3 readings, 3 quizzes
9 videos
Hash Tables: Implementation Details, Part I18m
Hash Tables: Implementation Details, Part II22m
Pathological Data Sets and Universal Hashing Motivation21m
Universal Hashing: Definition and Example [Advanced - Optional]25m
Universal Hashing: Analysis of Chaining [Advanced - Optional]18m
Hash Table Performance with Open Addressing [Advanced - Optional]15m
Bloom Filters: The Basics15m
Bloom Filters: Heuristic Analysis13m
3 readings
Week 4 Overview10m
Optional Theory Problems (Week 4)10m
Info and FAQ for final exam10m
3 practice exercises
Problem Set #410m
Programming Assignment #42m
Final Exam20m
Reviews
TOP REVIEWS FROM GRAPH SEARCH, SHORTEST PATHS, AND DATA STRUCTURES
by CSApr 12, 2018
Good course, but instructor does start to move fast and a few walk-throughs in certain spots would be beneficial . However the lack of it makes you do your own research, which is also beneficial.
by DSMar 29, 2020
Awesome course! Professor Roughgarden is fantastic. The material was appropriately challenging. Perfect amount of rigor. Only one minor squabble: the hash problem set is terribly misleading.
by TGNov 30, 2019
It was an awesome experience to learn from such a teacher. Now I have a much clear view of the graph algorithms. I have enjoyed this course. Thanks to Stanford for offering this course.
by GMMay 21, 2018
assignments didn't seem as interesting or complex as class 1, besides week 1 of class 2. Lecture material was high quality however, and the advanced optional material is appreciated
About the Algorithms Specialization
Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.
About the instructor: Tim Roughgarden has been a professor in the Computer Science Department at Stanford University since 2004. He has taught and published extensively on the subject of algorithms and their applications.
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