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 new array is allocated and the data from the old array is copied into the new array.

Elements are shifted to make room for the newly added element.

The size of the backing array is increased.

What happens when the number of elements in an `ArrayStack` exceeds the size of the backing array?

What happens when the number of elements in an <code>ArrayStack</code> exceeds the size of the backing array?

`ArrayQueue` uses a circular array implementation to simulate an infinite array.

`ArrayQueue` uses a doubly-linked list implementation to simulate an infinite array.

`ArrayQueue` uses a singly-linked list implementation to simulate an infinite array.

`ArrayQueue` uses an infinite array implementation for optimal performance.

Which statement is *true* regarding the implementation of `ArrayQueue`?

Which statement is true regarding the implementation of <code>ArrayQueue</code>?

Which data structure allows efficient addition and removal at both ends?

Which data structure allows efficient addition and removal at both ends?

`DualArrayDeque` is better than `ArrayDeque` in terms of performance.

`DualArrayDeque` stores the number of elements it contains explicitly.

`DualArrayDeque` doesn't use the `balance()` method while performing the `add(i,x)` operation.

Which statement is *true* regarding the `DualArrayDeque`?

Which statement is true regarding the <code>DualArrayDeque</code>?

It stores $n$ elements using $O(n)$ arrays.

It always uses more than $O(\sqrt n)$ array locations.

It addresses the problem of wasted space.

It is similar to `ArrayStack` in terms of memory usage.

Which statement is *true* about the `RootishArrayStack` data structure?

Which statement is true about the <code>RootishArrayStack</code> data structure?

Which data structure store its data in one or two arrays and avoids resizing these arrays too often?

Which data structure store its data in one or two arrays and avoids resizing these arrays too often?

Test yourself on what you've learned about array-based lists.

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 Array-Based Lists