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You see in our mind map here that we're now in the sorting section and this big of an log-in, something

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we haven't talked about, is showing up, we'll get to that in this section.

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But I want to add a quick note here, looking at all these sorting algorithms and there's a lot more.

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It's important to note that you don't need to write a sorting algorithm from scratch, most likely ever

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in your career.

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Frameworks usually do that for us.

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But you do, however, need to know how they work, because while one you're most likely going to get

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asked in an interview, and two, because it makes you a better engineer.

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But this section is also about being efficient.

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You see, you can spend a lot of time on each one of these sections implementing your own and talking

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about it deeply, because I don't think I've ever heard of anybody actually having to implement in code

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manually the sorting algorithms.

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Most of the time you can just talk about it or the interviewer tells you that the array assorted and

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you need to know what to do with it, but implementing it from scratch, that doesn't really happen.

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But I've included it in this section because it's good to know how they work.

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And I'm not going to lie coding, sorting algorithms is not my favorite either.

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Don't let that deter you.

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I encourage you to watch the next couple of videos and even practice coding your own sorting algorithms

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because it will help your learning.

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But the main thing that we're going to get from this section is not how to implement these.

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I mean, we will do that, but the key is the trade off.

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You see, we have the big picture here that we definitely know about.

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Right.

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We talked about data structures and how there's tradeoffs.

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Well, when it comes to sorting, there's tradeoffs as well.

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You see how there is some time, complexity, trade offs, space complexity, trade offs, and it's

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important to know when to use what algorithm.

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That's our goal of this section.

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And before we get into our first sorting algorithm, I want to show you this nifty little tool that

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I'm going to link to.

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We have a few sorting algorithms.

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We have insertion sought selection, sort, bubble, sort shall merge heap and then two different variations

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of quicksort.

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And we also have different data sets.

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This is a random data set, see how they perform when I click here.

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Based on different sorting algorithm.

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See that they're all working and.

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All of them finish at different times, one is a lot slower than the other.

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What about nearly sorted?

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Again, one such as insertion, it is really, really fast, while others are slower.

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Reversed if the items are reversed and we need to sort a completely reversed list, again, different

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algorithms.

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Perform differently.

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It's never one that wins out over the other, depending on the inputs.

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What we need to do their.

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Different abilities.

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Let's start to learn about these different types of sorting algorithms so that by the end of these videos,

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we can make the right decision when to use what I'll see in the next one.