Introduction to Algorithms and Data Structures: A solid foundation for the real world of machine learning and data analytics

Introduction to

Algorithms &

Data Structures 1

A solid foundation for the real world of machine learning and data analytics

Bolakale Aremu

Ojula Technology Innovations

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This is an electronic version of the print textbook. Due to electronic rights restrictions, some third-party content may be suppressed. Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. The publisher reserves the right to remove content from this title at any time if subsequent rights restrictions require it. For valuable information on pricing, previous editions, changes to current editions, and alternate formats, please contact [email protected] and inquire ISBN number, author, or title for materials in your areas of interest.

Introduction to Algorithms & Data Structures

First Edition

© 2023 Ojula Technology Innovations®

ISBN: 9791222093178

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented.

Ojula Technology Innovations is a leading provider of customized learning solutions with employees residing in nearly 45 different countries and sales in more than 130 countries around the world. For more information, please contact [email protected].

Printed in the United States of America

Print Number: 01

Print Year: April 2023

I am indebted to my mother for her love, understanding and support throughout the time of writing this textbook.

Bolakale Aremu

Table of Contents

0. What You Will Learn & How to Get Help

0.1. Benefits of learning about algorithms and data structures

0.2. Course Structure

1. Introduction to Algorithms

1.1. Playing a Counting Game

1.1.1. What is an Algorithm?

1.1.2. Guess the Number Game

1.1.3. Algorithm Guidelines

1.1.4. Practice Exercise 1

1.1.5. Answers to Practice Exercise 1

1.1.6. Evaluating Linear Search

1.1.7. Evaluating Binary Search

1.1.8. Practice Exercise 2

1.1.9. Answers to Practice Exercise 2

1.2. Time Complexity

1.2.1. Efficiency of an Algorithm

1.2.2. The Big O

1.2.3. Constant and Logarithmic Time

1.2.4. Linear & Quadratic Time

1.2.5. Cubic Runtime

1.2.6. Quasilinear Runtime

1.2.7. Polynomial Runtimes

1.2.8. Exponential Runtimes

1.2.9. How to Determine the Complexity of an Algorithm

1.2.10. Practice Exercise 3

1.2.11. Answers to Practice Exercise 3

1.3. Algorithms in Code

1.3.1. Linear Search in Code

1.3.2. Binary Search in Code

1.3.3. Recursive Binary Search in Code

1.3.4. Practice Exercise 4

1.3.5. Answers to Practice Exercise 4

1.4. Recursion and Space Complexity

1.4.1. Recursive Functions

1.4.2. Space Complexity

1.4.3. A Recap of What You Learned

1.4.4. Practice Exercise 5

1.4.5. Answers to Practice Exercise 5

1.5. Download Training Resources & Get Further Help

About The Author

My name is Bolakale Aremu. My educational background is in software development. I have a few colleagues who are software developers and system engineers. I spent over 17 years as a software developer, and I’ve done a bunch of other things too. I've been involved in SDLC/process, data science, operating system security and architecture, and many more. My most recent project is serverless computing where I simplify the building and running of distributed systems. I always use a practical approach in my projects and courses.

Bolakale Aremu

CEO, Ojula Technology Innovations

Web developer and Software Engineer

Ojulaweb.com

0. What You Will Learn & How to Get Help

The design of an efficient algorithm for the solution of the problem calls for the inclusion of appropriate data structures. In the field of computer science, data structures are used to store and organize data in a way that is easy to understand and use. They are used to organize and represent data in a way that will make it easier for computers to retrieve and analyze it. These are the fundamental building blocks that any programmer must know how to use correctly in order to build their own programs.

0.1. Benefits of learning about algorithms and data structures

First, they will help you become a better programmer. Another benefit is that they will make you think more logically. Furthermore, they can help you design better systems for storing and processing data. They also serve as a tool for optimization and problem-solving.

As a result, the concepts of algorithms and data structures are very valuable in any field. For example, you can use them when building a web app or writing software for other devices. You can apply them to machine learning and data analytics, which are two hot areas right now. If you are a hacker, algorithms and data structures in Python are also important for you everywhere.

Now, whatever your preferred learning style, I've got you covered. If you're a visual learner, you'll love my clear diagrams and illustrations throughout this book. If you're a practical learner, you'll love my hands-on lessons so that you can get practical with algorithms and data structures and learn in a hands-on way.

0.2. Course Structure

There are three volumes in this course. This is volume one. In this volume, you'll take a deep dive into the world of algorithms. With increasing frequency, algorithms are starting to shape our lives in many ways - from the products recommended to us, to the friends we interact with on social media, to even important social issues like policing, privacy and healthcare. So, the first part of this course covers what algorithms are, how they work, and where they can be found (real life applications).

In the second volume, you'll work through an introduction to data structures. You're going to learn about two introductory data structures - arrays and linked lists. You'll look at common operations and how the runtimes of these operations affect our everyday code.

In the third volume, you're going to bring your knowledge of algorithms and data structures together to solve the problem of sorting data using the Merge Sort algorithm. We will look at algorithms in two categories: sorting and searching. You'll implement well-known sorting algorithms like Selection Sort, Quicksort, and Merge Sort. You'll also learn basic search algorithms like Sequential Search and Binary Search.

At the end of many sections of this course, short practice exercises are provided to test your understanding of the topic discussed. Answers are also provided so you can check how well you have performed in each section. At the end of the course, you will find a link to download more helpful resources, such as codes and screenshots used in this book, and more practice exercises. You can use them for quick references and revision as well. My support link is also provided so you to contact me any time if you have questions or need further help.

By the end of this course, you will understand what algorithms and data structures are, how they are measured and evaluated, and how they are used to solve real-life problems. So, everything you need is right here in this book. I really hope you’ll enjoy it. Are