What Is an Algorithm?

[MUSIC] 0:00 Hi, my name is Pasan. 0:09 I'm an instructor here at Treehouse and welcome to introduction to algorithms. 0:10 Whether you're a high school or college student, a developer in the industry, or 0:14 someone who is learning to code, you have undoubtedly running to the term algorithm. 0:19 For many people, this word is kind of scary. 0:24 It represents this body of knowledge that seems just out of reach. 0:27 Only people with computer science degrees know about algorithms. 0:31 Now to others, this brings up feelings of impostor syndrome. 0:34 You might already know how to code but 0:38 you're not a real developer because you don't know anything about algorithms. 0:40 Personally, it made me frame certain jobs as above my skill level, 0:45 because the interview contained algorithm questions. 0:49 Well, whatever your reasons are, in this course, our goal is to dispel 0:53 all those feelings and get you comfortable with the basics of algorithms. 0:57 Like any other subject, 1:02 I like to start my courses with what the course is and is not. 1:04 In this course, we're going to cover the very basic set of knowledge that you need 1:08 as a foundation for learning about algorithms. 1:13 This course is less about specific algorithms and 1:15 more about the tools you will need to evaluate algorithms, 1:19 understand how they perform, compare them to each other, and 1:22 make a statement about the utility of an algorithm in a given context. 1:26 Now don't worry, none of this will be theoretical and 1:30 we will learn these concepts by using well-known algorithms. 1:33 In this course, we'll also be writing code. 1:37 So I do expect you to have some programming experience if 1:40 you intend to continue with this topic. 1:42 You can definitely stick around even if you don't know how to code but 1:45 you might want to learn the basics of programming in the meantime. 1:48 In this course, we will be using the Python programming language. 1:52 Python reads a lot like regular English and is the language you will most likely 1:56 encounter when learning about algorithms these days. 2:01 If you don't know how to code or if you know how to code in a different language, 2:04 check out the note section of this video for 2:09 links to other content that might be useful to you. 2:11 As long as you understand the fundamentals of programming, 2:15 you should be able to follow along pretty well. 2:18 If you're a JavaScript developer or a student who's learning JavaScript, 2:21 for example, 2:25 chances are good that you'll still be able to understand the code we write later. 2:26 I'll be sure to provide links along the way if you need anything to follow up on. 2:30 Let's start with something simple. 2:35 What is an algorithm? 2:37 An algorithm is a set of steps or instructions for completing a task. 2:39 This might sound like an oversimplification but 2:43 really that's precisely what an algorithm is. 2:47 A recipe is an algorithm, your morning routine when you wake up is an algorithm, 2:50 and the driving directions you follow to get to a destination is also an algorithm. 2:55 In computer science, the term algorithm more specifically means the set of 3:00 steps a program takes to finish a task. 3:05 If you've written code before, any code really, generally speaking, 3:08 you have written an algorithm. 3:12 Given that much of the code we write can be considered an algorithm, 3:14 what do people mean when they say, you should know about algorithms? 3:18 Now, consider this. 3:22 Let's say, I'm a teacher in a classroom and 3:24 I tell everyone I have an assignment for them. 3:26 On their desks, they have a picture of a maze and 3:28 their task is to come up with a way to find the quickest way out of the maze. 3:31 Everyone does their thing and comes up with a solution. 3:36 Every single one of these solutions is a viable solution and 3:39 is a valid example of an algorithm. 3:42 The steps one needs to take to get out of the maze. 3:45 But from being in classrooms or any group of any sort, 3:48 you know that some people will have better ideas than others. 3:51 We all have a diverse array of skillsets. 3:55 Over time, our class picks the best of these solutions. 3:58 And anytime we want to solve a maze, we go with one of these solutions. 4:01 This is what the field of algorithms is about. 4:05 There are many problems in computer science but 4:08 some of them are pretty common, regardless of what project you're working on. 4:11 Different people have come up with different solutions to these 4:16 common problems. 4:19 And over time, the field of computer science has identified 4:20 several that do the job well for a given task. 4:24 When we talk of algorithms, we're referring to two points. 4:27 We're primarily saying there's an established body of knowledge on how to 4:31 solve particular problems well. 4:36 And it's important to know what these solutions are. 4:38 Now why is it important? 4:41 If you're unaware that a solution exists, 4:43 you might try to come up with one yourself. 4:45 And there's a likelihood that your solution won't be as good or efficient, 4:48 whatever that means, compared to those that have been thoroughly reviewed. 4:52 But there is a second component to it as well. 4:57 Part of understanding algorithms is not just knowing that an algorithm exists but 5:00 understanding when to apply it. 5:05 Understanding when to apply an algorithm requires properly 5:07 understanding the problem at hand. 5:11 And this, arguably, is the most important part of learning about algorithms and 5:13 data structures. 5:18 As you progress through this content, you should be able to look at a problem and 5:19 break it down into distinct steps. 5:24 When you have a set of steps, you should then be able identify which algorithm or 5:26 data structure is best for the task at hand. 5:31 This concept is called algorithmic thinking and it's something we're 5:33 going to try and cultivate together as we work through our content. 5:37 Lastly, learning about algorithms gives you a deeper understanding about 5:40 complexity and efficiency in programming. 5:45 Having a better sense of how your code will perform in different situations is 5:48 something that you'll always want to develop and hone. 5:53 Algorithmic thinking is why algorithms also come up in big tech interviews. 5:56 Interviewers don't care as much that you're able to write a specific algorithm 6:01 in code but more about the fact that you can break 6:06 a seemingly insurmountable problem into distinct components and 6:09 identify the right tools to solve each distinct component. 6:13 And that is what we plan on doing. 6:17 In this course, though, we're going to focus on some of the tools and concepts 6:19 you will need to be aware of before we can dive into the topic of algorithms. 6:24 If you're ready, let's get started. 6:28

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