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Introduction to Data Structures

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Introduction

2:56 with Pasan Premaratne

In this course we're going to answer one fundamental question - why do we need more data structures than a programming language provides? We'll start by exploring one we already know of - arrays

Prerequisite Courses

If you'd like to learn how to program with Python before starting this course, check out the Beginning Python track

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    [MUSIC] 0:00
    Hi, my name is Pasan. 0:09
    I'm an instructor at Treehouse. 0:10
    And welcome to the Introduction to Data Structures course. 0:12
    In this course, we're going to answer one fundamental question, 0:15
    why do we need more data structures than a programming language provides? 0:18
    Before we answer that question, some house keeping, if you will. 0:23
    In this course, 0:27
    we're going to rely on concepts we learned in the introduction to algorithms course. 0:27
    Namely, big o notation, space and time complexity, and recursion. 0:32
    If you're unfamiliar with those concepts or 0:37
    just need a refresher, check out the prerequisite courses listed. 0:39
    In addition, this course does assume that you have some programming experience. 0:43
    We're going to use data structures that come built into nearly 0:48
    all programming languages as our point of reference. 0:51
    While we will explain the basics of how these structures work, 0:54
    we won't be going over how to use them in practice. 0:58
    If you are looking to learn how to program before digging into this content, 1:01
    check the notes section of this video for helpful links. 1:05
    If you are good to go, then awesome, let's start with an overview of this course. 1:08
    The first thing we are going to do is to explore a data structure we are somewhat 1:12
    already familiar with, arrays. 1:16
    If you've written a code before, there's a high chance you have used an array. 1:18
    In this course, we're going to spend some time understanding how arrays work, 1:22
    what are the common operations on an array and 1:27
    what are the runtimes associated with those operations? 1:29
    Once we've done that, 1:32
    we're going to build a data type of our own called a linked list. 1:34
    In doing so, we're going to learn that there's more than one way to store data. 1:37
    In fact, there's way more than just one way. 1:41
    We're also going to explore what motivates us to build specific kinds of structures 1:44
    and look at the pros and cons of these structures. 1:49
    We'll do that by exploring four common operations. 1:52
    Accessing a value, searching for a value, inserting a value, and deleting a value. 1:55
    After that, we're actually going to circle back to algorithms and 2:00
    implement a new one, a sorting algorithm. 2:03
    In the Introductions to Algorithms course, we implemented a binary search algorithm. 2:06
    A precondition to binary search was that the list needed to be sorted. 2:12
    We're going to try our hand at sorting a list and 2:16
    open the door to an entirely new category of algorithms. 2:19
    We're going to implement our sorting algorithm onto different data 2:22
    structures and explore how the implementation of one algorithm can defer 2:26
    based on the data structure being used. 2:30
    We'll also look at how the choice of data structure potentially influences 2:32
    the runtime of the algorithm. 2:36
    In learning about sorting, we're also going to encounter 2:39
    another general concept of algorithmic thinking called divide and conquer. 2:41
    Along with recursion, divide and 2:46
    conquer will be a fundamental tool that we will use to solve complex problems. 2:48
    All in due time, in the next video, let's talk about arrays. 2:52

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