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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Divide and Conquer, Sorting and Searching, and Randomized Algorithms (Coursera) Coursera
Stanford University

Divide and Conquer, Sorting and Searching, and Randomized Algorithms (Coursera)

CS: Software Engineering CS: Theory

Dive into the core concepts of computer science with our specialized online course on Divide and Conquer, Sorting and Searching, and Randomized Algorithms. This course is designed for those who want to understand how to efficiently manage large datasets and solve complex computational problems using advanced techniques. Learn about asymptotic notation, sorting algorithms like Merge Sort and QuickSort, searching methods such as Binary Search, and the power of randomized approaches.

Jun 22nd 2026
4 Weeks
Programming Algorithms Matrix
Details
Graph Search, Shortest Paths, and Data Structures (Coursera) Coursera
Stanford University

Graph Search, Shortest Paths, and Data Structures (Coursera)

CS: Theory

Dive into the world of advanced data structures and graph algorithms with our Graph Search, Shortest Paths, and Data Structures course. This specialized program is designed for those looking to deepen their understanding of essential concepts like heaps, balanced search trees, hash tables, bloom filters, and more. Explore practical applications in connectivity and shortest path analysis, and discover how these principles can be applied to solve complex problems across various fields.

Jun 22nd 2026
4 Weeks
Algorithms Data Structures Computer Science
Details
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming (Coursera) Coursera
Stanford University

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming (Coursera)

CS: Software Engineering CS: Theory

Dive into the world of efficient problem-solving with our specialized online course on Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming. This course is designed for those who want to enhance their algorithmic skills and learn how to tackle intricate computational challenges effectively.

Jun 22nd 2026
4 Weeks
Programming Algorithms Clustering
Details
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them (Coursera) Coursera
Stanford University

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

CS: Software Engineering CS: Theory

Dive into advanced algorithmic concepts with 'Shortest Paths Revisited, NP-Complete Problems and What To Do About Them'. This course unravels the intricacies of shortest path algorithms, delves into the realm of NP-completeness, and equips you with strategies to tackle computationally hard problems effectively.

Jun 15th 2026
4 Weeks
Algorithms Data Structures Dynamic Programming
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