Source: https://codefellows.github.io/code-401-python-guide/curriculum/class-01/notes/pain_suffering
That price is pain, the pain of growth.
The pain that you’ll experience during this course is no exception; most times it won’t feel good. You won’t feel good.
You’ll be pushed mentally, having to think your way through problems that you had only even heard about a few hours beforehand.
You’ll Constantly be thrust far outside of your comfort zone with the expectation that you’ll survive for the next push forward.
You’ll be pushed physically, and while sitting in a chair and staring at your screen isn’t the most strenuous exercise in the world, the consecutive hours of it will take its toll.
You’ll lose sleep, you’ll forget to work out, and you’ll feel exhausted all while being filled with information day after day.
Suffering is pain without purpose. Pain with no higher goal. Pain with no dreams, no ambition, no aspiration.
As you experience pain, seek the remedy! Ask questions that bridge the gap between what you know and what you need to be able to do. Research! Build your resources and your community! Don’t experience the pain in silence—that slides toward needless pain and the realm of suffering.
Source: https://rob-bell.net/2009/06/a-beginners-guide-to-big-o-notation/
Big O specifically describes the worst-case scenario, and can be used to describe the execution time required or the space used (e.g. in memory or on disk) by an algorithm.
O(1) describes an algorithm that will always execute in the same time (or space) regardless of the size of the input data set.
O(N) describes an algorithm whose performance will grow linearly and in direct proportion to the size of the input data set.
O(N2) represents an algorithm whose performance is directly proportional to the square of the size of the input data set.
This is common with algorithms that involve nested iterations over the data set. Deeper nested iterations will result in O(N3), O(N4) etc.
The growth curve of an O(2N) function is exponential - starting off very shallow, then rising meteorically.