AlgorithmsDynamic ProgrammingGreedy AlgorithmDivide And Conquer AlgorithmsRandomized AlgorithmSorting AlgorithmGraphsData StructureHash TableSpanning TreeNp-Completeness
Algorithms Specialization
Learn To Think Like A Computer Scientist. Master the fundamentals of the design and analysis of algorithms.
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Offered By
Algorithms SpecializationStanford UniversitySkills you will gain
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.
Applied Learning Project
Learners will practice and master the fundamentals of algorithms through several types of assessments. Every week, there is a multiple choice quiz to test your understanding of the most important concepts. There are also weekly programming assignments, where you implement one of the algorithms covered in lecture in a programming language of your choosing. Each course concludes with a multiple-choice final exam.
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
Some related experience required.
Approximately 4 months to complete
Suggested pace of 4 hours/week
English
Subtitles: English, Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, Spanish
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
Some related experience required.
Approximately 4 months to complete
Suggested pace of 4 hours/week
English
Subtitles: English, Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, Spanish
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.
There are 4 Courses in this Specialization
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
4,656 ratings
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).
Graph Search, Shortest Paths, and Data Structures
1,828 ratings
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).
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
1,156 ratings
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).
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
740 ratings
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).
Offered by
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.
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