Algorithms and Data Structures Overview

Algorithms and Data Structures Overview

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1. Introduction to ADS

When we start learning something new, it is very important to get familiar with the subject of our study first. So let's dive deeper into what we will learn about in this course.

Why Do We Need Algorithms and Data Structures

Why Do We Need Data Structures?

Algorithm Analysis

Challenge: How to Determine Algorithm Complexity

2. List and Array

Arrays and lists serve as foundational data structures in programming, with Python employing them extensively. This section provides an overview of these structures, delving into their concepts and highlighting their implementation nuances within the Python programming language.

Array Data Structure

Basic Array Operations Time Complexity

Challenge: Inserting Elements into the Array

Linked List Data Structure

Basic List Operations Time Complexity

Challenge: Inversing the Order of Elements in the List

Doubly Linked List

3. Advanced Data Structures

There are many applied tasks in which it is necessary to operate with large amounts of structured data and simple data structures such as an array or a linked list may no longer be enough for these purposes. In this section, we'll look at the concept of an abstract data type and how different ADTs allow us to efficiently manage large amounts of data.

Challenge: Using Stack to Find Palindrome

Challenge: Creating Hash Table with String Keys

4. Graphs

In the real world, one often has to deal with tasks in which it is necessary to model complex dependencies between various nodes of a system or domain. Graphs can help us with this. In this section, we will learn what a graph is and how to represent it in computer memory efficiently.

Graph Implementation

Challenge: Graph Traversal Algorithms

Challenge: Balanced Trees

Course Content

Algorithms and Data Structures Overview

Challenge: Inserting Elements into the Array

Task

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Now we will perform the insertion operation and calculate the time needed to do it in seconds. We will conduct this process for different N values and construct a plot illustrating the dependency between the time required for the insertion operation and N. Your task is:

Insert randomly generated integers into a NumPy array for different N values: 1000, 2000, 3000, 4000, and 5000.
Calculate the program running time for this operation.

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Section 2. Chapter 3

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Challenge: Inserting Elements into the Array

Task

Swipe to show code editor

Now we will perform the insertion operation and calculate the time needed to do it in seconds. We will conduct this process for different N values and construct a plot illustrating the dependency between the time required for the insertion operation and N. Your task is:

Insert randomly generated integers into a NumPy array for different N values: 1000, 2000, 3000, 4000, and 5000.
Calculate the program running time for this operation.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 3

toggle bottom row

Challenge: Inserting Elements into the Array

Task

Swipe to show code editor

Now we will perform the insertion operation and calculate the time needed to do it in seconds. We will conduct this process for different N values and construct a plot illustrating the dependency between the time required for the insertion operation and N. Your task is:

Insert randomly generated integers into a NumPy array for different N values: 1000, 2000, 3000, 4000, and 5000.
Calculate the program running time for this operation.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Task

Swipe to show code editor

Now we will perform the insertion operation and calculate the time needed to do it in seconds. We will conduct this process for different N values and construct a plot illustrating the dependency between the time required for the insertion operation and N. Your task is:

Insert randomly generated integers into a NumPy array for different N values: 1000, 2000, 3000, 4000, and 5000.
Calculate the program running time for this operation.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 2. Chapter 3

Switch to desktop for real-world practiceContinue from where you are using one of the options below

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