Gain insights into array-based and linked list-based data structures, explore advanced structures like skiplists and hashing, and discover template-based collections for efficient data storage and retrieval.

java.tar.gz

Data structures and algorithms are essential in computer science since they play a crucial role in efficient information retrieval and processing, dealing with files, storing contacts on phones, social networks and web searches.

In this course, you’ll learn about the array-based implementation of various linear data structures, stack, and queues. You’ll also learn about linked list-based implementation. Next, you’ll explore advanced data structures like skiplists and hashing. You’ll learn how to implement a variety of trees and graphs, and data structures related to bits of an integer. Toward the end of the course, you’ll learn the implementation of structures based on external storage.

After completing this course, you’ll be able to create reusable programs with template-based collections that can efficiently analyze how to optimize the storage and retrieval of very large amounts of data. Overall, this course will enhance your productivity and performance as a software developer.

Data Structures with Generic Types in Python

# Graphs overview

In this module, we study two representations of graphs and basic algorithms that use these representations.

Mathematically, a (directed) graph is a pair $G = (V ,E)$ where $V$ is a set
of vertices and $E$ is a set of ordered pairs of vertices called edges. An edge
$(i,j)$ is directed from $i$ to $j$; $i$ is called the source of the edge and $j$ is called the target. A path in $G$ is a sequence of vertices $v_0,..., v_k$ such that, for every $i \in \{1,...,k\}$, the edge $(v_{i−1}, v_i)$ is in $E$. A path $v_0,..., v_k$ is a cycle if, additionally, the edge $(v_k , v_0)$ is in $E$. A path (or cycle) is simple if all of its vertices are unique. If there is a path from some vertex $v_i$ to some vertex $v_j$ then we say that $v_j$ is reachable from $v_i$. An example of a graph is shown below:


A graph with twelve vertices. Vertices are drawn as numbered circles and edges are drawn as pointed curves pointing from source to target.


Learn about graphs, their applications, and their operations.

Overview

Array-Based Lists

Linked Lists

Skiplists

Hash Tables

Binary Trees

Random Binary Search Trees

Scapegoat Trees

Red-Black Trees

Heaps

Sorting Algorithms

Graphs

Data Structures for Integers

External Memory Searching

Wrap Up

Introduction to Graphs

Graphs overview