Udemy - Sorting Algorithms in Python (Animation-Based)

Sorting Algorithms in Python (Animation-Based)



https://DevCourseWeb.com

Last updated 6/2023
Duration: 4h 34m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 1.28 GB
Genre: eLearning | Language: English

Implement and understand sorting algorithms through animations. Master sorting for your next coding interview!

What you'll learn
Six important comparison based sorting algorithms: Bubble Sort, Selection Sort, Insertion Sort, Quick Sort, Merge Sort and Heap Sort.
Relate each line in the code with its purpose in the algorithm.
How to implement the covered sorting algorithms in Python.
Compare the efficiency of sorting algorithms using the Big O Notation.
Requirements
Basic programming (Data types, variables, loops, functions, etc.)
Basic math for the time complexity analysis (Summations, functions, etc.)
To run the code and experiment by yourself, you will need to have Python 3 installed on your device.
Description
Sorting is a fundamental concept in computer science and is essential for many applications.
This course will teach you through detailed animations how the most important sorting algorithms work and how to implement them in Python. By the end of this course, you will have an excellent understanding of the six popular sorting algorithms: Bubble Sort, Selection Sort, Insertion Sort, Quick Sort, Merge Sort and Heap Sort.
We will start in the first section with an introduction to sorting, the Big O notation, and a rough overview over the master theorem.
For each sorting algorithm, there is a separate section, where we'll delve into at least two videos.
The
first video
serves always as an introduction to the underlying algorithm, covering its core concept, the corresponding Python code, and practical examples.
An
additional example
video is available
for Quick Sort
, as it can be a challenging algorithm for beginners to understand. By providing a very detailed example, the corresponding video aims to simplify the learning process and help learners gain a better understanding of the connection of Quick Sort and its implementation.
In the
second video
, we conduct a comprehensive analysis of the algorithm's properties. This includes mainly examining its stability, whether it performs in-place sorting, as well as its time complexity under various cases such as best, average, and worst-case scenarios.
This course is for anyone who wants to gain a better understanding of sorting algorithms and a bit of Python programming. Join this course today and take the first step in becoming an expert in sorting!
Who this course is for
Computer Science Students
College Graduates
Software engineers