This course introduces data structures and algorithms, focusing on practical implementation in Python.

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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

A graph is a set of ordered pairs of vertices called edges.

A path in a graph is a sequence of vertices such that all of its vertices are unique.

An edge in a graph is directed from the target to the source.

The number of vertices in a graph is denoted by $m$.

Which statement about graphs is true?

`add_edge(i, j)`, `remove_edge(i, j)`, and `has_edge(i, j)` operations take $O(n)$ time per operation.

What is a drawback of using the adjacency matrix representation for a graph?

What is a drawback of using the adjacency matrix representation for a graph?

It is best suited for graphs represented using an adjacency matrix representation.

The algorithm starts at a vertex and visits its neighbors in a depth-first manner.

The algorithm uses a stack data structure to store the vertices.

The algorithm ensures that no vertex is added to the queue more than once using an auxiliary boolean array.

What is *true*the  about the breadth-first-search algorithm?

What is truethe about the breadth-first-search algorithm?

Test yourself on what you've learned about graphs.

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

Quiz on Graphs