Course Content
Algorithms and Data Structures Overview
Algorithms and Data Structures Overview
Why Do We Need Algorithms and Data Structures
It is strongly recommended to finish Ultimate NumPy course before starting this one.
Go here if needed.
Before we even start learning something in this course, it is very important to get familiar with the subject that we are learning and why we are learning it, so let's briefly discuss it further.
In most business cases, we are limited with the resources provided to us to achieve a goal of a project, and we need to manage and use these resources reasonably. This is where we need algorithms and data structures because they go hand in hand with each other, as algorithms and their productivity rely heavily on the right choice of a data structure.
Of course, many frameworks provide us with efficient implementations of all the most popular and used data structures and algorithms but to get a deep understanding of how each algorithm and data structure works and to be able to choose between them, we need to study them in detail.
Imagine you are developing an operating system's task scheduler. The goal is to efficiently prioritize and execute tasks with different priorities.
In this scenario, you can use a data structure known as a "priority queue" to optimize the task scheduling process. A priority queue ensures that higher-priority tasks are executed before lower-priority ones, leading to efficient task management.
Everything was clear?
