About this Specialization

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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.
Learner Career Outcomes
62%
Started a new career after completing this specialization.
26%
Got a pay increase or promotion.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Intermediate Level
Approx. 4 months to complete
Suggested 3 hours/week
English
Subtitles: English
Learner Career Outcomes
62%
Started a new career after completing this specialization.
26%
Got a pay increase or promotion.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Intermediate Level
Approx. 4 months to complete
Suggested 3 hours/week
English
Subtitles: English

There are 4 Courses in this Specialization

Course1

Course 1

Divide and Conquer, Sorting and Searching, and Randomized Algorithms

4.8
stars
3,986 ratings
734 reviews
Course2

Course 2

Graph Search, Shortest Paths, and Data Structures

4.8
stars
1,629 ratings
188 reviews
Course3

Course 3

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

4.8
stars
1,015 ratings
116 reviews
Course4

Course 4

Shortest Paths Revisited, NP-Complete Problems and What To Do About Them

4.8
stars
651 ratings
84 reviews

Offered by

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Stanford University

Frequently Asked Questions

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  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • 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.

  • 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. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • The Specialization has four four-week courses, for a total of sixteen weeks.

  • Learners should know how to program in at least one programming language (like C, Java, or Python); some familiarity with proofs, including proofs by induction and by contradiction; and some discrete probability, like how to compute the probability that a poker hand is a full house. At Stanford, a version of this course is taken by sophomore, junior, and senior-level computer science majors.

  • For best results, the courses should be taken in order.

  • No.

  • Having taken your programming and thinking skills to the next level, you will be well positioned to ace your technical interviews, pursue serious software engineering, and study advanced topics in algorithms.

More questions? Visit the Learner Help Center.