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More resources on Graph Algorithms
Algorithms, Part I
This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms. All the features of this course are available for free. People who are interested in digging deeper into the content may wish to obtain the textbook Algorithms, Fourth Edition (upon which the course is based) or visit the website algs4.cs.princeton.edu for a wealth of additional material. This course does not offer a certificate upon completion.
Algorithms, Part II
This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms. All the features of this course are available for free. People who are interested in digging deeper into the content may wish to obtain the textbook Algorithms, Fourth Edition (upon which the course is based) or visit the website algs4.cs.princeton.edu for a wealth of additional material. This course does not offer a certificate upon completion.
LeetCode
Online judge with thousands of algorithm and data-structure problems sorted by difficulty, topic and company, plus timed contests, discussion threads and study plans. Regular practice builds fluency with common interview problem patterns and writing correct, efficient code under time pressure.
CP-Algorithms - Minimum-cost flow (successive shortest path)
Article explaining the successive shortest path algorithm for minimum-cost flow, an extension of Edmonds-Karp that augments along cheapest paths, covering directed and undirected graphs, complexity analysis, an SPFA-based implementation, and practice problems. Readers can implement min-cost max-flow for contest problems.
Visualgo.net
Interactive visualization module from VisuAlgo, built at the National University of Singapore, showing how graphs are stored as adjacency matrices, adjacency lists and edge lists, so learners can compare these representations and trace graph operations step by step.
Algorithmic Thinking (Part 1)
Rice University course on analysing algorithmic efficiency and applying it to graph problems. Students implement several graph algorithms in Python and use them to analyse two large real-world data sets, learning how the structure of data affects algorithm behaviour.