Introduction to Big O Notation and Time Complexity (Data Structures & Algorithms #7)

Big O notation and time complexity, explained.

Special thanks to Brilliant for sponsoring this video.

[ahmadali-zzom]

After I finish my course I want to send this vid to my professor and tell him to explain it this way to make the student's life easier.

[guitarbansi]

Humble message to all the teachers I ever had:
This is how you teach.

[drewb]

I sat in class for the whole semester struggling to figure this out. Then I see your video and understand it in 30 mins. College is a joke.

[cludbear]

"I'm gonna use pseudocode"
**uses Python**
Python: "Am I a joke to you?"

[Thunderbuck]

I'm in my late 50s and starting a DS & A university course, and of course the first term I hit was "big-Oh" and when I saw the academic definitions it nearly triggered a panic attack. I am SO grateful for this engaging lecture and also immensely grateful that the Internet makes such valuable content available.

[smallcreativecorner]

4 years of University couldn't explain what you just did in 40 mins.
You truly have a gift!

[spicytuna]

I went to UC Irvine in Southern Cal. I had a professor (obviously PhD) who graduated from a big Ivy league who explained this. I could not understand. I couldn't F understand from the course book also. Now I understand. You are such a great teacher.

[jonharvey]

Thank you for the helpful video! Great examples for a beginner

0:21 Intro w/ example function find_sum
2:40 Testing actual runtime of example function in microseconds
12:37 Another Example: stupid_function O(1) compared with O(n)
17:03 Without Testing runtimes: BigO + TC for stupid_function and find_sum
25:05 Another Example : O(n^2)
34:04 Wrap up

[CSDojo]

Hey guys, sorry for the delay on this video.

I traveled for a week, and I sort of fell out of my routine after that. But I’m back!

Anyway, thanks a lot to everyone who messaged me or commented on my videos while I was away.

As usual, please let me know if you have any video requests in a comment below :)

[maialso]

0:20 sum function
1:30 how much time does it take to run this function ?
-> depends on the computer & programming language etc..
some tools to answer the question : Big O notation & Time Complexity
2:40 testing the function in python
4:54 Time Complexity
-> Linear time
-> constant time
-> quadratic time
5:42 Big O notation
-> Linear time, O(n)
-> constant time, O(1)
-> quadratic time, O(n^2)
7:30 how to find big O from an expression

-> find the fastest growing term
-> take out the coefficient
10:54 convenient features
-> gives you a rough idea about how your function scales as input increases
-> doesn't depend on your practical environment
12:38 practice_1
17:40 practice_2
-> O(1)+O(1)=O(1)
20:51 practice_3
25:06 practice_4
31:52 practice_5

edit : Free Palestine !!🍉🍉

[Titan_Ruler]

The flow of your explaining is excellent. After getting frustrated from reading this from text books, I came here and now it looks so simple to understand. Really excellent man..☺

[shrutisharma]

This is by far the best explanation of time complexity and how to calculate it for any function that I have seen on YouTube. Thank you.

[Sarah-uhwy]

I should be paying my tuition and fees to you lmao
Seriously, thanks!

[mikeallencopeland]

YK, just wanted to say how much I appreciate you for dedicating your valuable time and knowledge to the youtube community of developers. I am starting out fresh as a software developer and CS major this fall. Your videos are excellent learning tools are are helping me to grasp the discipline so thanks man!

[thundersmind]

Hey Dojo. Keep up with the amazing videos. You're destined for greatness!!

[sahilgarg]

Finally, in my current life. I understood this concept. Can't thank you enough dojo.

[Codebake]

I learnt this concept from a course and I swear no lecturer explained it better than you did. Good work man😎

[asadashoori]

you simplified the concept in a way that we don't memorize anything but understand them.
thank you so much for your clear explanation 🙏

[Jozin]

I've been struggling with this concept in my data structures & algorithms course, the way you explained it helped 👍

[Natena]

Unbelievable how simple the explanation is. Thank u