About this Specialization
100% online courses

100% online courses

Start instantly and learn at your own schedule.
Flexible Schedule

Flexible Schedule

Set and maintain flexible deadlines.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 4 months to complete

Suggested 7 hours/week
Available languages

English

Subtitles: English...

Skills you will gain

AlgorithmsDynamic ProgrammingGreedy AlgorithmDivide And Conquer Algorithms
100% online courses

100% online courses

Start instantly and learn at your own schedule.
Flexible Schedule

Flexible Schedule

Set and maintain flexible deadlines.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 4 months to complete

Suggested 7 hours/week
Available languages

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

Divide and Conquer, Sorting and Searching, and Randomized Algorithms

4.8
2,152 ratings
416 reviews
The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts)....
Course2

Graph Search, Shortest Paths, and Data Structures

4.8
942 ratings
113 reviews
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)....
Course3

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

4.8
592 ratings
69 reviews
The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees)....
Course4

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

4.8
362 ratings
44 reviews
The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search)....

Instructor

Avatar

Tim Roughgarden

Professor
Computer Science

About 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....

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.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • 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.

  • 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.