• Anytime
    Application Deadline
  • 4 months
    Duration
Learn To Think Like A Computer Scientist. Master the fundamentals of the design and analysis of algorithms with this Algorithms Specialization offered by Coursera in partnership with Stanford.

Overview

The programme

Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This Algorithms Specialization offered by Coursera in partnership with Stanford 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.

Detailed Programme Facts

Programme Structure

Courses include:

  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms
  • Graph Search, Shortest Paths, and Data Structures
  • Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
  • Shortest Paths Revisited, NP-Complete Problems and What To Do About Them

English Language Requirements

This programme may require students to demonstrate proficiency in English.

General Requirements

Intermediate Level

Tuition Fee

7-day Free Trial on Specializations
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Funding

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.

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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