Algorithms Specialization

Starts Sep 25

Algorithms Specialization

Learn To Think Like A Computer Scientist

Master the fundamentals of the design and analysis of algorithms.

About This 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.

Created by:

courses
4 courses

Follow the suggested order or choose your own.

projects
Projects

Designed to help you practice and apply the skills you learn.

certificates
Certificates

Highlight your new skills on your resume or LinkedIn.

Projects Overview

Courses
Intermediate Specialization.
Some related experience required.
  1. COURSE 1

    Divide and Conquer, Sorting and Searching, and Randomized Algorithms

    Upcoming session: Sep 25 — Oct 30.
    Commitment
    4 weeks of study, 4-8 hours/week
    Subtitles
    English

    About the Course

    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).
  2. COURSE 2

    Graph Search, Shortest Paths, and Data Structures

    Upcoming session: Sep 25 — Oct 30.
    Commitment
    4 weeks of study, 4-8 hours/week
    Subtitles
    English

    About the Course

    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).
  3. COURSE 3

    Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

    Upcoming session: Sep 25 — Oct 30.
    Commitment
    4 weeks of study, 4-8 hours/week
    Subtitles
    English

    About the Course

    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).
  4. COURSE 4

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

    Current session: Sep 18 — Oct 23.
    Commitment
    4 weeks of study, 4-8 hours/week
    Subtitles
    English

    About the Course

    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).

Creators

  • Stanford University

    Stanford University is one of the world's leading teaching and research universities. Since its opening in 1891, Stanford has been dedicated to finding solutions to big challenges and to preparing students for leadership in a complex world.

    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.

  • Tim Roughgarden

    Tim Roughgarden

    Professor

FAQs

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