Time & Space Complexity - Big O Notation - DSA Course in Python Lecture 1

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[@GregHogg]

Master Data Structures & Algorithms For FREE at AlgoMap.io!

[@hello_there79]

Great video Greg!
Maybe this playlist will turn into one of the best Python DSA course on youtube ;)

[@Jafar801]

Please continue adding more videos on data structures and algorithms (DSA) in Python; they are really helpful.

[@blazenetic]

Wow. Huge thank you, best explanation yet. Your teaching abilities seem magical.

[@GregHogg]

Awe thank you so much, that's so kind of you to say

[@ahnaftanjid5531]

your explanation is so soothing. Already watched DSA 1-6. Please bring more.

[@GregHogg]

Glad to hear it!

[@shiyun2811]

Really loved how well scaffolded and structure this video is! Knew about big O but your video was definitely one of the best explanations I've come across 🎉 with simple to understand functions before delving into the concepts mathematically. Thanks for the great work done

[@GregHogg]

Very glad to hear it, thank you ☺️

[@PostMeridianLyf]

Lets gooooo!

[@firdousbhat123]

Awesome

[@hello_there79]

​ ​ @GregHogg this video is under "Linked List Questions" Featured playlist, which can be seen in video description.
starts with
1.7K views 4 days ago _Linked List Questions_

[@turmoilstabilizer9054]

I was aware of your channel for quite some time, read and churned through numerous dsa and python da books. This content is golden and the best that I have seen on youtube to date. Keep up the great work Greg!

[@GregHogg]

Haha really glad to hear it 🥰

[@aaronlobo3106]

Thanks alot bro!
Your videos are amazing.. Please keep teaching DSA!

[@GregHogg]

Thanks so much!

[@chakradharkalla2857]

here we go!!!!
Babe new video dropped from Greg Hogg new DSA series..

[@GregHogg]

HAHAHA

[@muniswamivikram]

Yes I also waiting for machine learning

[@jamestacular]

I’m confused. Isn’t the second example O(n*logn) since you’re not traversing through the entire array for each number? Just the remaining possibilities of unique numbers? With n^2 you’d get 25 possibilities but here you get 15

[@epicman9181]

It's actually about 1/2 n^2 which simplifies to O(n^2).
Imagine generating every pair of inputs including 'duplicates' like (1,5) and (5,1). You would get the full 25 options.
Adding the rule "once the (1,5) pair is made (5,1) is redundant" can at most divide the number of outputs by 2.
It doesn't perfectly divide the input by 2 due to pairs like (2,2) and (5,5), making the formula 1/2 * (n^2 +n), but that simplifies to O(n^2).

[@wilsonchen5224]

W mans I love your content

[@GregHogg]

Thank you!

[@Andrew_N_G]

Hey bro have you covered strings i am not able to find the lecture

[@GregHogg]

Yes check my theory playlist

[@alanmathew7247]

Do a video on tree and O(log n)