Introduction to Algorithms and Data Structures

Introduction to Algorithms and Data Structures

A solid foundation for the real world of machine learning and data analyticsBy Bolakale Aremu
Michael Caine
Listen with Sir Michael Caine™ and 1,000+ voices
Length2h 21m

About this audiobook

Benefits of This Book. Learning algorithms and data structures from this book will help you become a better programmer. Algorithms and data structures 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. Course Structure. This book is the first volume of the series Introduction to Algorithms & Data Structures. 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. The third volume is packed with 5 hours of HD tutorial videos, practice exercises, sample codes, and popular interview questions asked by Google, Microsoft, Amazon and other big companies. So, in the third volume, you'll master linear data structures and algorithms which are essential to getting your dream job, so that you don't waste your time browsing disconnected tutorials or super long, boring courses. In this volume, 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, assessment tests are provided. You will also find links 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 series. I really hope you’ll enjoy it. Are you ready? Let's dive in!

Audiobook details

GenreTechnology, Science and Nature
Length2 hrs 21 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateApr 8, 2023
LanguageEnglish

Table of contents

10. What You Will Learn & How to Get Help
20.1. Benefits of learning about algorithms and data structures
30.2. Course Structure
41. Introduction to Algorithms
51.1. Playing a Counting Game
Show all chapters
61.1.1. What is an Algorithm?
71.1.2. Guess the Number Game
81.1.3. Algorithm Guidelines
91.1.4. Practice Exercise 1
101.1.5. Answers to Practice Exercise 1
111.1.6. Evaluating Linear Search
121.1.7. Evaluating Binary Search
131.1.8. Practice Exercise 2
141.1.9. Answers to Practice Exercise 2
151.2. Time Complexity
161.2.1. Efficiency of an Algorithm
171.2.2. The Big O
181.2.3. Constant and Logarithmic Time
191.2.4. Linear & Quadratic Time
201.2.5. Cubic Runtime
211.2.6. Quasilinear Runtime
221.2.7. Polynomial Runtimes
231.2.8. Exponential Runtimes
241.2.9. How to Determine the Complexity of an Algorithm
251.2.10. Practice Exercise 3
261.2.11. Answers to Practice Exercise 3
271.3. Algorithms in Code
281.3.1. Linear Search in Code
291.3.2. Binary Search in Code
301.3.3. Recursive Binary Search in Code
311.3.4. Practice Exercise 4
321.3.5. Answers to Practice Exercise 4
331.4. Recursion and Space Complexity
341.4.1. Recursive Functions
351.4.2. Space Complexity
361.4.3. A Recap of What You Learned
371.4.4. Practice Exercise 5
381.4.5. Answers to Practice Exercise 5
391.5. Download Training Resources & Get Further Help

Series

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