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Data Structures and Algorithms in Python

Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!

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4 Hours16 Videos49 Exercises4050 XP

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Course Description

Most computer programs are based on a few data structures and algorithms. Learn about what’s behind the hood of most of your computer interactions in this four-hour course! You’ll familiarize yourself with some of the most common data structures: linked lists, stacks, queues, and trees. You’ll also implement popular algorithms, such as Depth First Search, Breadth First Search, Bubble sort, Merge sort, and Quicksort.

Learn to Spot Data Structures and Algorithms in Everyday Life

You'll practice applying data structures and algorithms to decks of cards, music playlists, international dishes, and stacks of books. You’ll walk away with the ability to recognize common data structures and algorithms, and implement them in day-to-day applications!

Analyze the Efficiency of Algorithms

Along the way, you’ll stop to analyze popular algorithms in terms of their efficiency. You’ll come to grips with “Big O Notation”, the industry standard for describing the complexity of an algorithm.

Sharpen Your Python Programming Knowledge

Being well-versed with data structures and algorithms means being able to take everyday problems and solve them using efficient code. You’ll be practising this in Python, you’ll take these fundamental and transferable skills with you to any programming language.
  1. 1

    Work with Linked Lists and Stacks and Understand Big O notation

    Free

    You’ll begin by learning what algorithms and data structures are. You will discover two data structures: linked lists and stacks. You will then learn how to calculate the complexity of an algorithm by using Big O Notation.

    Play Chapter Now
    Welcome!
    50 xp
    Implementing a linked list
    100 xp
    Inserting a node at the beginning of a linked list
    100 xp
    Removing the first node from a linked list
    100 xp
    Understanding Big O Notation
    50 xp
    Big O Notation: true or false?
    100 xp
    Practicing with Big O Notation
    100 xp
    Working with stacks
    50 xp
    Implementing a Stack with the push method
    100 xp
    Implementing the pop method for a stack
    100 xp
    Using Python's LifoQueue
    100 xp

Collaborators

Maham Khan
Izzy Weber
George Boorman

Prerequisites

Writing Functions in Python
Miriam Antona Headshot

Miriam Antona

Software Engineer

Miriam is a freelance Software Engineer with 15+ years of experience. She is focused on analyzing, designing, and developing software applications. She also collaborates with the UOC University supervising Bachelor theses. Miriam loves programming and experimenting with different technologies. She is passionate about databases and enjoys playing with data. She holds a Master of Science Degree in Computer Engineering.
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