Introduction to Algorithms and Data Structures 1: A solid foundation for the real world of machine learning and data analytics

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 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. 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 book, 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 book, 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 course. I really hope you’ll enjoy it. Are you ready? Let's dive in! 0. What You Will Learn & How to Get Help 8 0.1. Benefits of learning about algorithms and data structures 8 0.2. Course Structure 8 1. Introduction to Algorithms 10 1.1. Playing a Counting Game 11 1.1.1. What is an Algorithm? 11 1.1.2. Guess the Number Game 13 1.1.3. Algorithm Guidelines 17 1.1.4. Practice Exercise 1 22 1.1.5. Answers to Practice Exercise 1 22 1.1.6. Evaluating Linear Search 22 1.1.7. Evaluating Binary Search 27 1.1.8. Practice Exercise 2 30 1.1.9. Answers to Practice Exercise 2 30 1.2. Time Complexity 31 1.2.1. Efficiency of an Algorithm 31 1.2.2. The Big O 33 1.2.3. Constant and Logarithmic Time 34 1.2.4. Linear & Quadratic Time 39 1.2.5. Cubic Runtime 41 1.2.6. Quasilinear Runtime 42 1.2.7. Polynomial Runtimes 46 1.2.8. Exponential Runtimes 46 1.2.9. How to Determine the Complexity of an Algorithm 51 1.2.10. Practice Exercise 3 53 1.2.11. Answers to Practice Exercise 3 54 1.3. Algorithms in Code 55 1.3.1. Linear Search in Code 55 1.3.2. Binary Search in Code 61 1.3.3. Recursive Binary Search in Code 65 1.3.4. Practice Exercise 4 70 1.3.5. Answers to Practice Exercise 4 70 1.4. Recursion and Space Complexity 71 1.4.1. Recursive Functions 71 1.4.2. Space Complexity 72 1.4.3. A Recap of What You Learned 75 1.4.4. Practice Exercise 5 77 1.4.5. Answers to Practice Exercise 5 78 1.5. Download Training Resources & Get Further Help 79