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 7 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 7 hours/week

English

Subtitles: English

How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

how it works

There are 4 Courses in this Specialization

Course1

Course 1

Divide and Conquer, Sorting and Searching, and Randomized Algorithms

4.8
stars
3,552 ratings
640 reviews
Course2

Course 2

Graph Search, Shortest Paths, and Data Structures

4.8
stars
1,501 ratings
166 reviews
Course3

Course 3

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

4.8
stars
953 ratings
104 reviews
Course4

Course 4

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

4.8
stars
589 ratings
74 reviews

Offered by

Stanford University logo

Stanford University

Frequently Asked Questions

  • 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.

  • 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.