How I Mastered Data Structures and Algorithms

[00:00] Today I'm going to explain to you how I

[00:01] mastered data structures and algorithms

[00:03] quickly without hating my life. Now I

[00:06] say that because a lot of people that

[00:07] get into this topic do it completely

[00:10] wrong. It takes up a massive amount of

[00:12] time and they just hate doing it. It's

[00:14] brutal. And let's not lie, no one enjoys

[00:16] data structures and algorithms. But

[00:17] there's a way to do it that's a lot less

[00:19] painful that I want to break down in

[00:21] this video. Okay, so let's get right

[00:23] into it. First things first, do yourself

[00:25] a favor and pick an easy language to do

[00:27] this in. Now, most people are going to

[00:29] be learning this either because they're

[00:31] in a computer science degree or because

[00:33] they're preparing for technical coding

[00:34] interviews. Now, I'm mostly speaking to

[00:36] that latter group there, people that are

[00:38] doing this because eventually they're

[00:39] going to be quizzed on this type of

[00:41] stuff and have to answer these le code

[00:42] style problems. So, I highly recommend

[00:45] use a language like Python when you're

[00:47] learning this and when you're going to

[00:49] be practicing these DSA style problems.

[00:51] The reason for that is it's a much more

[00:53] elegant language. It's way easier to

[00:55] write code in it and it's much easier to

[00:57] follow. So if you had to answer a

[00:59] question in Java, for example, it's

[01:00] going to take you just longer to write

[01:02] the code due to the syntax style of

[01:04] Java. Doesn't mean Java is a bad

[01:06] language, but for the purpose of passing

[01:08] coding interviews, you're just doing

[01:10] yourself a favor if you pick a language

[01:11] like Python. Okay? Even if you don't use

[01:13] it or it's not your primary language,

[01:15] it's very easy to learn enough of it to

[01:17] be able to answer coding questions in

[01:19] it. So I recommend that you pick

[01:21] something like Python, maybe even

[01:22] something like JavaScript. Anything that

[01:24] has relatively simple syntax and dynamic

[01:27] typing is going to help you a lot. Okay,

[01:29] moving on. Step number two. Now, I

[01:31] learned the theory quickly. A lot of

[01:34] people spend months learning the theory

[01:35] of data structures and algorithms.

[01:37] That's not necessary. There's three main

[01:39] things that you need to learn or kind of

[01:40] three main topics. I'll quickly go over

[01:42] them, but the point is don't spend too

[01:44] much time here. You need to understand

[01:45] the algorithms and data structures. Know

[01:47] the time complexity of the operations,

[01:49] but that's about it. You don't need to

[01:50] implement these from scratch. Sure, if

[01:52] you have extra time, it's a good idea,

[01:54] but it's not necessary. You're not going

[01:55] to be asked to write a heap, or at least

[01:57] very unlikely that they'd ask you to do

[01:59] that. It's more so understanding how to

[02:00] use the data structures and what the

[02:02] time complexity of the operations are.

[02:04] So, what I did is I started by learning

[02:06] bigo notation and time complexity

[02:08] analysis. This is the most fundamental

[02:10] thing. You need to understand this. Then

[02:12] I started looking at data structures. So

[02:14] I won't go through an entire exhaustive

[02:16] list because there's a lot of resources

[02:17] online that cover those better than this

[02:19] video can. But things like stack, Q

[02:21] linked list, trees, etc. I skipped the

[02:24] super complex stuff. So things like B

[02:26] trees, for example, red black trees, AVL

[02:28] trees, tries, if you're going for more

[02:31] senior positions, maybe you need to know

[02:32] those, but in my case, for internship or

[02:34] kind of entry level roles, you're just

[02:36] probably not going to be quizzed on

[02:38] those. Then I started looking at

[02:39] algorithms. So obviously famous

[02:41] algorithms, your sorting algorithms,

[02:43] your searching algorithms and I didn't

[02:45] implement all of these on my own. I just

[02:47] understood what they were enough that if

[02:49] I were asked a question about them, I

[02:50] would know the time complexity or I

[02:52] would know that they exist. I looked at

[02:54] things like graph algorithms and then I

[02:56] started looking at some more niche

[02:58] algorithms that come up in coding

[02:59] problems a lot. So things like dynamic

[03:02] programming, greedy algorithms, things

[03:04] like the two-pointer approach, the

[03:06] sliding window, and again not memorizing

[03:09] these, but just knowing that they exist

[03:11] and having some basic theory

[03:12] understanding so that when I start

[03:14] getting into solving problems, I know

[03:16] enough that I can at least reference

[03:18] back to that topic and then learn it

[03:20] more by applying it directly. Now, in

[03:22] terms of how I learned these, I pretty

[03:23] much just searched for a bunch of

[03:25] resources online. I found a solid road

[03:27] map that walked through a bunch of those

[03:28] topics and then I followed it and I

[03:30] looked up YouTube videos and used

[03:32] websites like Geeks for Geeks. Now,

[03:33] quick pause here because you'll probably

[03:35] find this relevant. If you are a

[03:36] software engineer right now or you are

[03:38] looking to become a software engineer

[03:40] and something like technical interview

[03:41] prep is holding you back, then consider

[03:43] applying for my program at Dev Launch.

[03:45] In this program, we take on a very small

[03:47] group of developers. Yes, it is

[03:49] expensive. It's a high ticket program,

[03:51] but it's designed to give people

[03:52] one-on-one guidance to help them land

[03:54] their next role. And we've already had a

[03:56] lot of success. For example, we had a

[03:58] senior software engineer come in really

[03:59] struggling with this topic specifically.

[04:02] We gave him the correct guidance, helped

[04:03] him with all the mock technical

[04:04] interviews, and he just landed 180K per

[04:07] year role and is interviewing with Meta

[04:09] right now where we expect him to receive

[04:10] an offer because he's in the final

[04:12] rounds. We have a lot of other examples

[04:14] like that. But if you're serious about

[04:15] this and you want someone to hold your

[04:17] hand through this whole process, then

[04:18] you can apply from Dev Launch down

[04:20] below. We don't just do technical

[04:22] interview prep, but obviously that's

[04:23] relevant to this video. Okay,

[04:24] continuing. Let's get into my prep when

[04:27] it came to the questions. So, I saw so

[04:29] many articles online of people saying

[04:31] they did like 400 lead code questions or

[04:33] 300 lead code questions or even 200.

[04:36] That is insane to do that many

[04:37] questions. First of all, that will take

[04:39] you like four, five, six months unless

[04:41] you're doing five a day or something

[04:42] along those lines. And I want to tell

[04:43] you for myself, I only did 60 lead code

[04:47] questions and I did about 50 algo expert

[04:50] questions. Okay? So my process when I

[04:52] was practicing these questions first of

[04:54] all was to always emphasize quality over

[04:57] quantity. Now yes you do need to put in

[04:59] sufficient volume. I think getting to

[05:01] about 75 to 100 questions for most

[05:03] people should be enough if they're

[05:05] practicing correctly and picking the

[05:06] right questions. But for me I started

[05:08] with a platform like Algo Expert. Now

[05:10] this is before I worked for Algo Expert

[05:12] in case you guys think this is like a

[05:13] sponsor. I don't actually make any money

[05:15] if you buy that uh platform so I don't

[05:17] care if you use it. But for me, I liked

[05:19] that platform because it had really

[05:21] in-depth video explanations of all of

[05:24] the questions. Now, I think Lead Code

[05:25] may have those now as well. It's been a

[05:27] while since I did this. But for me, when

[05:29] I was starting out, I really struggled

[05:31] with these questions. Like, I could

[05:32] hardly answer some of the easy

[05:33] questions. So what I would do is I would

[05:35] struggle at a question, but when I

[05:36] wasn't getting anywhere at all and I had

[05:38] put in the time and I had struggled, I

[05:40] would go and I would watch through the

[05:41] video explanation and really make sure

[05:43] that I understood it and then reattempt

[05:45] the question right after to see if I

[05:47] could actually do it on my own. So

[05:49] that's how I started getting good really

[05:50] fast was failing essentially watching

[05:53] the solution and then not just moving on

[05:55] to the next question, but doing it again

[05:57] after watching the solution. And then I

[05:59] might even revisit it another time,

[06:00] maybe the next day to make sure that I

[06:02] actually comprehended it. So even though

[06:04] I only did maybe 50 questions, I would

[06:06] do the same question multiple times

[06:08] until I actually got it correct. Okay,

[06:10] so that was where I started with Algo

[06:12] Expert, right? But they only have maybe

[06:14] 150, 200 questions on the platform and

[06:16] by the time you get through 50 or 60,

[06:18] you've done a lot of the easy medium

[06:20] ones, which is what I was targeting for

[06:22] kind of the internship level roles. So

[06:24] after that, I switched over to leak

[06:26] code. Now, leak code is a lot more

[06:28] challenging in my opinion because you

[06:29] don't have the same level of guidance or

[06:31] the same kind of quality of video

[06:32] explanations, but it's good when you

[06:34] want to put in more volume. So, then I

[06:36] switched over to leak code and again,

[06:38] same thing. I would do the questions. I

[06:40] would try to check the answers, but it

[06:42] wasn't always as good as Algo Expert.

[06:43] And that's when I put in more volume.

[06:45] Now, I was typically doing about two

[06:46] questions per day when I was preparing.

[06:49] And again, I was making sure that when I

[06:51] did these questions, I was emphasizing

[06:52] quality, which I'm going to move on to

[06:54] next. Okay. So, while I was doing these

[06:56] questions and especially in those last

[06:58] leak code questions, I made sure that I

[07:01] was practicing like I play, which I

[07:03] think is the number one mistake that

[07:04] people make when they do these types of

[07:06] problems. You can do as many problems as

[07:08] you want, but if you don't emulate a

[07:10] real coding interview, you're not going

[07:12] to succeed when you're just thrown into

[07:13] that environment. Now, I did a lot of

[07:15] research online. I knew people in the

[07:17] space, so I knew I'm probably going to

[07:18] have to write this out by hand. I'm

[07:20] going to have to verbalize my solution,

[07:22] and I'm going to have to walk through

[07:23] this very strict framework that I

[07:25] actually made a video about, which I'll

[07:26] put on screen right now. So, what I did

[07:28] is when I answered these questions, I

[07:30] literally bought a whiteboard, put it in

[07:32] my room, set up my camera, and recorded

[07:34] myself pretending I was in an interview

[07:36] environment. So, I would solve the

[07:38] question actually on the whiteboard. I

[07:40] would speak the entire time. I would

[07:42] time myself. And while I couldn't do as

[07:44] many questions when I did this, I really

[07:46] got comfortable in this environment

[07:48] where when I actually went into the real

[07:49] interview, it was the exact same thing

[07:51] that I've been practicing countless

[07:52] times. So, in my room alone like a crazy

[07:55] person, I would do that and I would

[07:56] highly recommend you do that because

[07:58] it's going to expose to you really

[07:59] quickly the other parts of the coding

[08:01] interview that most people end up

[08:03] failing, right? That are related to the

[08:04] communication. All right. Now, after I

[08:06] did a bunch of reps sitting in my room

[08:07] like a crazy person answering questions,

[08:09] I decided I should do some real mock

[08:11] interviews. So what I did is I reached

[08:13] out to people that I knew. For example,

[08:15] Clement, you guys might know him from

[08:16] Algo Expert. We did a mock interview on

[08:18] YouTube actually with him and I did a

[08:20] bunch of interviews using a platform

[08:22] called Prampt. Now I'm not sure if that

[08:24] platform is still around. This was a

[08:25] while ago, but essentially you could go

[08:27] on and you can volunteer and you ask

[08:29] someone a question and then they ask you

[08:30] a question and you're kind of both, you

[08:32] know, acting as the interviewer and the

[08:33] candidate. So I did a bunch of those. I

[08:35] probably did 15 mock interviews just to

[08:37] make sure again I was really really

[08:39] comfortable and I was not just worrying

[08:41] about memorizing all of these algorithms

[08:42] but actually how I presented them and

[08:44] how I spoke through the problem which is

[08:46] where I see most people failing. So just

[08:48] make sure you do as many interviews as

[08:50] you can. I even had some of my friends

[08:51] who are non-technical ask me a question

[08:53] that I had prepared for them to ask me

[08:55] that I didn't know the answer to and

[08:56] then I ran through it and I kind of got

[08:58] their opinion as a non-technical person

[09:00] on how well they thought I did. Okay, so

[09:02] those are the main things I did to

[09:03] prepare. The last point that I want to

[09:05] put on here, which is the reason I

[09:06] believe I succeeded in all of the

[09:08] interviews that I did, because I didn't

[09:09] fail any of them, is that I had

[09:11] confidence when I walked into the

[09:13] interview. Now, the reason I was

[09:15] confident was because I knew no matter

[09:17] what happened, I had done as much as I

[09:19] possibly could to prepare. I put in the

[09:21] time. I studied correctly. I did this

[09:24] properly, right? I was putting in

[09:25] quality. I wasn't just kind of wasting

[09:26] my practice. And I knew that even if I

[09:29] failed this interview, there's nothing

[09:30] more that I could have done. I prepared

[09:32] as best as I could. If you have that in

[09:35] the back of your mind and you know no

[09:36] matter what happens, it's honestly not

[09:38] your fault. You've done the preparation,

[09:40] you've done what you can and the result

[09:42] will be what it will be, then I think

[09:44] you just have some underlying confidence

[09:45] and kind of the way you present

[09:47] yourself, the calmness you have wears

[09:49] off in the interview. And at least for

[09:50] me, that's what I felt happened. And I

[09:52] knew doesn't matter if I fail, whatever.

[09:54] It's all good. I move on to the next one

[09:55] because I prepared as much as I can and

[09:57] there's just nothing more I can do. So,

[09:59] I challenge you, get to that point

[10:01] before you walk into some of your

[10:03] interviews and just know in the back of

[10:04] your mind, you've done everything you

[10:06] can. And if if you fail, you fail. Is

[10:08] what it is. You move on to the next one,

[10:09] right? There's nothing to be worried

[10:10] about. You did everything that was

[10:12] possible. Okay, that's all I have for

[10:14] this video. Again, if you guys want

[10:16] assistance with this, this is exactly

[10:17] what I do in Dev Launch. I literally

[10:19] teamed up with someone who's an ex

[10:20] Google, ex Amazon employee who's given

[10:22] hundreds of these technical interviews,

[10:24] who's really nailing the process for our

[10:26] students in this program. If you want

[10:27] help, apply from the link below and I

[10:29] will see you guys in another video.

[10:31] [Music]