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Big O Notation For Algorithms In Plain English
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Angela Belfort, CEO of Firma Logistics strode into the meeting room quietly enraged. The way CEOs are enraged, composed and at the same time fuming. She is followed by her entourage. All the important people that make all the decisions. You’ve been at the company for just over a year and you’re not quite sure how you ended up in this room.
Her assistant had already set the room projector showing the live feed of the company’s fleet, over 4000 lorries scattered all over the country. Each vehicle was shown as a dot, colored red as stationary, green as moving. Almost all of them were red.
“What the hell is going on? I have lorry drivers complaining to unions because we aren’t able to give them a delivery schedule. I have furious suppliers on the lines asking for updates on their packages. We’ve got competitors circling over our clients like vultures. Can someone explain to me what is happening?”, Angela started.
Everyone was expecting an answer from the CTO, Brian Holms. Technically, on the huge org chart, he is your manager somewhere along the path from your position to the top, but it sure is a long way. He replies with “Er… em… We seem to be having some IT issues. I brought Alex here with me as she seems to have found a bug in the system”.
The focus is now completely on you. Hey, this might be the day you get fired after all… “It’s not really a bug. A section of the current scheduling algorithm has a quadratic runtime complexity with respect to the number of routes”.
The room looks at you as if you said the moon was made out of cheese. The big wigs turn their heads back to Brian for an explanation, but he seems as lost as they are. Instead he nervously nods, encouraging you to go on.
“Ok. Remember Paul Zimmer? Our ex-tech lead guy? Well it turns out that some of his old code does not scale well. It was fine while we had a few hundred lorries, but now that the company has grown so much the scheduling program is not able to keep up with the load. Especially on busy days like today. We have not really invested in keeping the code with the latest technologies and now nobody knows how it really works.” This is literally the most dumbed down version you can think of.
Angela jumps in “Where is this Paul?”
“He retired about a year ago. Rumor has it he opened an American diner in Hong Kong.”, replies Brian.
Angela’s composure is all gone now. “Can we fix the damn thing?”, she shouts.
“Well it’s very old code, nobody really understands how it works and we have been trying to reach Paul but if he’s in a different country… ”, puts in Brian but is interrupted by you.
“I already have a working linear solution. By linear I mean it will scale fine with our needs. I just need to run some further testing and then we can probably release it.”
Brian is visibly shocked. Everyone else is kind of confused, not completely sure what is going on. Angela is the only one with a grin.
Understanding the basics of Big O notation and being able to “read” how much an algorithm can scale is a must for all serious developers. This extra skill gives you the edge to take your career forward, to distinguish yourself from the rest of the crowd and get ahead. It helps you pass difficult coding interviews to get hired from some of the best tech companies.
The code in this course is in Python however if you have experience from any other major programming language (such as Java, C#, JavaScript, Ruby etc…) you’ll be ok with the code in the course as it’s designed to be easy to grasp.
All code in this course can be found on github, username/project: cutajarj/BigONotationInPlainEnglish
So don’t be a Brian, sign up to the course and learn something new today!
Who this course is for:
Self taught developers that want to up their game and learn about how to measure and improve their code.
College students that are struggling with the Big O Notation, Algorithms and Complexity theory topic.
Experienced developers that require a refresher, perhaps for an upcoming interview.
CTOs named Brian Holmes
Requirements
Some basic programming experience required. The code in the course is in Python however the code is simple enough that if you know how to program in any major language you’ll be ok.
This course is designed to be light on mathematics to facilitate understanding. If you can grasp the simple math in the (free) intro video you’ll be ok for the rest of the course!
Last Updated 6/2022
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TutsNode.com.txt
63 B
[TutsNode.net] - Big O Notation for Algorithms in plain English/1. Introduction/1. Introduction Big O Notation Part 1.mp4
188.2 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/1. Introduction/1. Introduction Big O Notation Part 1.srt
11.3 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/1. Introduction/2. Cracking an A to Z padlock.html
197 B
[TutsNode.net] - Big O Notation for Algorithms in plain English/1. Introduction/3. Introduction Big O Notation Part 2.mp4
94.8 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/1. Introduction/3. Introduction Big O Notation Part 2.srt
5.5 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/1. Introduction/4. Understanding Scalability.mp4
36.4 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/1. Introduction/4. Understanding Scalability.srt
14.2 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/1. Introduction/5. Useful pointers for this course.html
528 B
[TutsNode.net] - Big O Notation for Algorithms in plain English/2. Linear Complexity Functional Class/1. What does it look like to scale linearly.mp4
54.4 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/2. Linear Complexity Functional Class/1. What does it look like to scale linearly.srt
3.6 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/2. Linear Complexity Functional Class/2. Finding Minimum Algorithm.mp4
14.4 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/2. Linear Complexity Functional Class/2. Finding Minimum Algorithm.srt
8.1 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/2. Linear Complexity Functional Class/3. String Equals Algorithm.mp4
28.2 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/2. Linear Complexity Functional Class/3. String Equals Algorithm.srt
12.7 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/3. Quadratic Complexity Functional Class/1. Understanding the Quadratic Runtime.mp4
51.6 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/3. Quadratic Complexity Functional Class/1. Understanding the Quadratic Runtime.srt
7.9 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/3. Quadratic Complexity Functional Class/2. Closest Points Brute Force Algorithm.mp4
32.7 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/3. Quadratic Complexity Functional Class/2. Closest Points Brute Force Algorithm.srt
15.6 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/3. Quadratic Complexity Functional Class/3. Closest Points Brute Force Analysis.mp4
75.4 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/3. Quadratic Complexity Functional Class/3. Closest Points Brute Force Analysis.srt
11.6 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/3. Quadratic Complexity Functional Class/4. Optimizing Closest Points Brute Force.mp4
35.9 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/3. Quadratic Complexity Functional Class/4. Optimizing Closest Points Brute Force.srt
14.8 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/4. Constant Complexity Functional Class/1. Introduction to Constant Runtime Algorithms.mp4
35.3 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/4. Constant Complexity Functional Class/1. Introduction to Constant Runtime Algorithms.srt
3 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/4. Constant Complexity Functional Class/2. Number of Edges in a Graph Algorithm.mp4
25.8 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/4. Constant Complexity Functional Class/2. Number of Edges in a Graph Algorithm.srt
11.7 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/4. Constant Complexity Functional Class/3. Improving Algorithm and Analysis.mp4
29 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/4. Constant Complexity Functional Class/3. Improving Algorithm and Analysis.srt
11.8 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/5. Exponential Complexity Functional Class/1. How fast is Exponential Growth.mp4
34.7 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/5. Exponential Complexity Functional Class/1. How fast is Exponential Growth.srt
9.2 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/5. Exponential Complexity Functional Class/2. Subset Sum Problem Explained.mp4
26.1 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/5. Exponential Complexity Functional Class/2. Subset Sum Problem Explained.srt
15.3 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/5. Exponential Complexity Functional Class/3. Subset Sum Implementation and Analysis.mp4
20.3 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/5. Exponential Complexity Functional Class/3. Subset Sum Implementation and Analysis.srt
7.2 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/6. Logarithmic Complexity Functional Class/1. Introduction to Logarithms.mp4
59.6 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/6. Logarithmic Complexity Functional Class/1. Introduction to Logarithms.srt
7.6 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/6. Logarithmic Complexity Functional Class/2. Binary Search Algorithm.mp4
38.1 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/6. Logarithmic Complexity Functional Class/2. Binary Search Algorithm.srt
17 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/6. Logarithmic Complexity Functional Class/3. Why is Binary Search Logarithmic.mp4
36.2 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/6. Logarithmic Complexity Functional Class/3. Why is Binary Search Logarithmic.srt
15.4 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/7. Log Linear Complexity Functional Class/1. Understanding Log Linear Complexity Functional Class.mp4
17.3 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/7. Log Linear Complexity Functional Class/1. Understanding Log Linear Complexity Functional Class.srt
9 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/7. Log Linear Complexity Functional Class/2. Building the Merge Sort.mp4
19.3 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/7. Log Linear Complexity Functional Class/2. Building the Merge Sort.srt
7.6 KB
[TutsNode.net] - Big O Notation for Algorithms in plain English/7. Log Linear Complexity Functional Class/3. How scalable is a Log Linear algorithm.mp4
58.8 MB
[TutsNode.net] - Big O Notation for Algorithms in plain English/7. Log Linear Complexity Functional Class/3. How scalable is a Log Linear algorithm.srt
