This course is part of the Algorithms Specialization

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stars
1,924 ratings

Tim Roughgarden

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Offered By

Algorithms SpecializationStanford University

About this Course

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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).

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 2 of 4 in the

Algorithms Specialization

Intermediate Level

Approx. 15 hours to complete

English

Skills you will gain

Graphs
Data Structure
Algorithms
Hash Table

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 2 of 4 in the

Algorithms Specialization

Intermediate Level

Approx. 15 hours to complete

English

Instructor

Instructor rating

4.84/5 (118 Ratings)

Tim Roughgarden

Offered by

Stanford University

Syllabus - What you will learn from this course

Content Rating93%(3,064 ratings)

Week1

Week 1

4 hours to complete

Week 1

4 hours to complete

9 videos (Total 162 min), 4 readings, 2 quizzes

9 videos

Graph Search - Overview23mBreadth-First Search (BFS): The Basics14mBFS and Shortest Paths7mBFS and Undirected Connectivity13mDepth-First Search (DFS): The Basics7mTopological Sort21mComputing Strong Components: The Algorithm29mComputing Strong Components: The Analysis26mStructure of the Web [Optional]18m

4 readings

Week 1 Overview10mOverview, Resources, and Policies10mLecture slides10mOptional Theory Problems (Week 1)10m

2 practice exercises

Problem Set #130mProgramming Assignment #130m

Week2

Week 2

3 hours to complete

Week 2

3 hours to complete

4 videos (Total 79 min), 2 readings, 2 quizzes

Week3

Week 3

4 hours to complete

Week 3

4 hours to complete

9 videos (Total 142 min), 1 reading, 2 quizzes

9 videos

Data Structures: Overview4mHeaps: Operations and Applications18mHeaps: Implementation Details [Advanced - Optional]20mBalanced Search Trees: Operations and Applications10mBinary Search Tree Basics, Part I13mBinary Search Tree Basics, Part II30mRed-Black Trees21mRotations [Advanced - Optional]7mInsertion in a Red-Black Tree [Advanced]14m

1 reading

Week 3 Overview10m

2 practice exercises

Problem Set #330mProgramming Assignment #330m

Week4

Week 4

5 hours to complete

Week 4

5 hours to complete

9 videos (Total 171 min), 3 readings, 3 quizzes

9 videos

Hash Tables: Operations and Applications19mHash Tables: Implementation Details, Part I18mHash Tables: Implementation Details, Part II22mPathological Data Sets and Universal Hashing Motivation21mUniversal Hashing: Definition and Example [Advanced - Optional]25mUniversal Hashing: Analysis of Chaining [Advanced - Optional]18mHash Table Performance with Open Addressing [Advanced - Optional]15mBloom Filters: The Basics15mBloom Filters: Heuristic Analysis13m

3 readings

Week 4 Overview10mOptional Theory Problems (Week 4)10mInfo and FAQ for final exam10m

3 practice exercises

Problem Set #430mProgramming Assignment #430mFinal Exam30m

Reviews

4.8

230 reviews

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TOP REVIEWS FROM GRAPH SEARCH, SHORTEST PATHS, AND DATA STRUCTURES

by KSJul 11, 2018

This is an excellent course. Though the assignments are quite challenging, it is rewarding to complete them. Professor Roughgarden's explanations are wonderful.

by HCNov 11, 2017

Focused on principles and motivations behind algorithms. You might forget an algorithm you learned, but you will definitely be able to come up with one quickly after this course.

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 HLMar 1, 2021

There is very little hand-holding in this course and no code provided. This really challenges you to implement the ideas taught in the most efficient and appropriate manner possible.

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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.

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. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

Graph Search, Shortest Paths, and Data Structures

About this Course

Skills you will gain