---
title: 'How I Mastered Data Structures and Algorithms'
source: 'https://youtube.com/watch?v=ryeycH0njP8'
video_id: 'ryeycH0njP8'
date: 2026-06-15
duration_sec: 639
---

# How I Mastered Data Structures and Algorithms

> Source: [How I Mastered Data Structures and Algorithms](https://youtube.com/watch?v=ryeycH0njP8)

## Summary

The speaker shares a method to master data structures and algorithms (DSA) efficiently without burnout, focusing on practical strategies for coding interviews. Key steps include choosing an easy language like Python, learning theory quickly, and practicing with quality over quantity.

### Key Points

- **Introduction to Efficient DSA Mastery** [00:00] — The speaker aims to explain how to master DSA quickly without hating the process, noting that many people approach it incorrectly.
- **Pick an Easy Language** [00:25] — Recommend using Python or JavaScript for DSA practice due to simple syntax and dynamic typing, which speeds up coding in interviews.
- **Learn Theory Quickly** [01:31] — Focus on Big O notation, time complexity, and common data structures (stack, queue, linked list, trees) and algorithms (sorting, searching, graph, dynamic programming). Avoid spending months on theory.
- **Quality Over Quantity in Practice** [04:27] — The speaker did only 60 LeetCode and 50 AlgoExpert questions, emphasizing understanding each problem deeply rather than solving hundreds.
- **Use Platforms with Video Explanations** [05:08] — Started with AlgoExpert for its in-depth video solutions, struggling with a problem, watching the explanation, then reattempting until understood.
- **Practice Like a Real Interview** [06:56] — Used a whiteboard, recorded himself, verbalized solutions, and timed himself to simulate interview conditions, which improved communication and confidence.
- **Conduct Mock Interviews** [08:06] — Did about 15 mock interviews with peers or platforms like Pramp to get comfortable with the interview format and receive feedback.
- **Confidence Through Preparation** [09:02] — Confidence came from knowing he had prepared as much as possible, which reduced anxiety and helped him perform well in actual interviews.

### Conclusion

Mastering DSA for interviews is achievable by focusing on quality practice, simulating real interview conditions, and building confidence through thorough preparation.

## Transcript

Today I'm going to explain to you how I
mastered data structures and algorithms
quickly without hating my life. Now I
say that because a lot of people that
get into this topic do it completely
wrong. It takes up a massive amount of
time and they just hate doing it. It's
brutal. And let's not lie, no one enjoys
data structures and algorithms. But
there's a way to do it that's a lot less
painful that I want to break down in
this video. Okay, so let's get right
into it. First things first, do yourself
a favor and pick an easy language to do
this in. Now, most people are going to
be learning this either because they're
in a computer science degree or because
they're preparing for technical coding
interviews. Now, I'm mostly speaking to
that latter group there, people that are
doing this because eventually they're
going to be quizzed on this type of
stuff and have to answer these le code
style problems. So, I highly recommend
use a language like Python when you're
learning this and when you're going to
be practicing these DSA style problems.
The reason for that is it's a much more
elegant language. It's way easier to
write code in it and it's much easier to
follow. So if you had to answer a
question in Java, for example, it's
going to take you just longer to write
the code due to the syntax style of
Java. Doesn't mean Java is a bad
language, but for the purpose of passing
coding interviews, you're just doing
yourself a favor if you pick a language
like Python. Okay? Even if you don't use
it or it's not your primary language,
it's very easy to learn enough of it to
be able to answer coding questions in
it. So I recommend that you pick
something like Python, maybe even
something like JavaScript. Anything that
has relatively simple syntax and dynamic
typing is going to help you a lot. Okay,
moving on. Step number two. Now, I
learned the theory quickly. A lot of
people spend months learning the theory
of data structures and algorithms.
That's not necessary. There's three main
things that you need to learn or kind of
three main topics. I'll quickly go over
them, but the point is don't spend too
much time here. You need to understand
the algorithms and data structures. Know
the time complexity of the operations,
but that's about it. You don't need to
implement these from scratch. Sure, if
you have extra time, it's a good idea,
but it's not necessary. You're not going
to be asked to write a heap, or at least
very unlikely that they'd ask you to do
that. It's more so understanding how to
use the data structures and what the
time complexity of the operations are.
So, what I did is I started by learning
bigo notation and time complexity
analysis. This is the most fundamental
thing. You need to understand this. Then
I started looking at data structures. So
I won't go through an entire exhaustive
list because there's a lot of resources
online that cover those better than this
video can. But things like stack, Q
linked list, trees, etc. I skipped the
super complex stuff. So things like B
trees, for example, red black trees, AVL
trees, tries, if you're going for more
senior positions, maybe you need to know
those, but in my case, for internship or
kind of entry level roles, you're just
probably not going to be quizzed on
those. Then I started looking at
algorithms. So obviously famous
algorithms, your sorting algorithms,
your searching algorithms and I didn't
implement all of these on my own. I just
understood what they were enough that if
I were asked a question about them, I
would know the time complexity or I
would know that they exist. I looked at
things like graph algorithms and then I
started looking at some more niche
algorithms that come up in coding
problems a lot. So things like dynamic
programming, greedy algorithms, things
like the two-pointer approach, the
sliding window, and again not memorizing
these, but just knowing that they exist
and having some basic theory
understanding so that when I start
getting into solving problems, I know
enough that I can at least reference
back to that topic and then learn it
more by applying it directly. Now, in
terms of how I learned these, I pretty
much just searched for a bunch of
resources online. I found a solid road
map that walked through a bunch of those
topics and then I followed it and I
looked up YouTube videos and used
websites like Geeks for Geeks. Now,
quick pause here because you'll probably
find this relevant. If you are a
software engineer right now or you are
looking to become a software engineer
and something like technical interview
prep is holding you back, then consider
applying for my program at Dev Launch.
In this program, we take on a very small
group of developers. Yes, it is
expensive. It's a high ticket program,
but it's designed to give people
one-on-one guidance to help them land
their next role. And we've already had a
lot of success. For example, we had a
senior software engineer come in really
struggling with this topic specifically.
We gave him the correct guidance, helped
him with all the mock technical
interviews, and he just landed 180K per
year role and is interviewing with Meta
right now where we expect him to receive
an offer because he's in the final
rounds. We have a lot of other examples
like that. But if you're serious about
this and you want someone to hold your
hand through this whole process, then
you can apply from Dev Launch down
below. We don't just do technical
interview prep, but obviously that's
relevant to this video. Okay,
continuing. Let's get into my prep when
it came to the questions. So, I saw so
many articles online of people saying
they did like 400 lead code questions or
300 lead code questions or even 200.
That is insane to do that many
questions. First of all, that will take
you like four, five, six months unless
you're doing five a day or something
along those lines. And I want to tell
you for myself, I only did 60 lead code
questions and I did about 50 algo expert
questions. Okay? So my process when I
was practicing these questions first of
all was to always emphasize quality over
quantity. Now yes you do need to put in
sufficient volume. I think getting to
about 75 to 100 questions for most
people should be enough if they're
practicing correctly and picking the
right questions. But for me I started
with a platform like Algo Expert. Now
this is before I worked for Algo Expert
in case you guys think this is like a
sponsor. I don't actually make any money
if you buy that uh platform so I don't
care if you use it. But for me, I liked
that platform because it had really
in-depth video explanations of all of
the questions. Now, I think Lead Code
may have those now as well. It's been a
while since I did this. But for me, when
I was starting out, I really struggled
with these questions. Like, I could
hardly answer some of the easy
questions. So what I would do is I would
struggle at a question, but when I
wasn't getting anywhere at all and I had
put in the time and I had struggled, I
would go and I would watch through the
video explanation and really make sure
that I understood it and then reattempt
the question right after to see if I
could actually do it on my own. So
that's how I started getting good really
fast was failing essentially watching
the solution and then not just moving on
to the next question, but doing it again
after watching the solution. And then I
might even revisit it another time,
maybe the next day to make sure that I
actually comprehended it. So even though
I only did maybe 50 questions, I would
do the same question multiple times
until I actually got it correct. Okay,
so that was where I started with Algo
Expert, right? But they only have maybe
150, 200 questions on the platform and
by the time you get through 50 or 60,
you've done a lot of the easy medium
ones, which is what I was targeting for
kind of the internship level roles. So
after that, I switched over to leak
code. Now, leak code is a lot more
challenging in my opinion because you
don't have the same level of guidance or
the same kind of quality of video
explanations, but it's good when you
want to put in more volume. So, then I
switched over to leak code and again,
same thing. I would do the questions. I
would try to check the answers, but it
wasn't always as good as Algo Expert.
And that's when I put in more volume.
Now, I was typically doing about two
questions per day when I was preparing.
And again, I was making sure that when I
did these questions, I was emphasizing
quality, which I'm going to move on to
next. Okay. So, while I was doing these
questions and especially in those last
leak code questions, I made sure that I
was practicing like I play, which I
think is the number one mistake that
people make when they do these types of
problems. You can do as many problems as
you want, but if you don't emulate a
real coding interview, you're not going
to succeed when you're just thrown into
that environment. Now, I did a lot of
research online. I knew people in the
space, so I knew I'm probably going to
have to write this out by hand. I'm
going to have to verbalize my solution,
and I'm going to have to walk through
this very strict framework that I
actually made a video about, which I'll
put on screen right now. So, what I did
is when I answered these questions, I
literally bought a whiteboard, put it in
my room, set up my camera, and recorded
myself pretending I was in an interview
environment. So, I would solve the
question actually on the whiteboard. I
would speak the entire time. I would
time myself. And while I couldn't do as
many questions when I did this, I really
got comfortable in this environment
where when I actually went into the real
interview, it was the exact same thing
that I've been practicing countless
times. So, in my room alone like a crazy
person, I would do that and I would
highly recommend you do that because
it's going to expose to you really
quickly the other parts of the coding
interview that most people end up
failing, right? That are related to the
communication. All right. Now, after I
did a bunch of reps sitting in my room
like a crazy person answering questions,
I decided I should do some real mock
interviews. So what I did is I reached
out to people that I knew. For example,
Clement, you guys might know him from
Algo Expert. We did a mock interview on
YouTube actually with him and I did a
bunch of interviews using a platform
called Prampt. Now I'm not sure if that
platform is still around. This was a
while ago, but essentially you could go
on and you can volunteer and you ask
someone a question and then they ask you
a question and you're kind of both, you
know, acting as the interviewer and the
candidate. So I did a bunch of those. I
probably did 15 mock interviews just to
make sure again I was really really
comfortable and I was not just worrying
about memorizing all of these algorithms
but actually how I presented them and
how I spoke through the problem which is
where I see most people failing. So just
make sure you do as many interviews as
you can. I even had some of my friends
who are non-technical ask me a question
that I had prepared for them to ask me
that I didn't know the answer to and
then I ran through it and I kind of got
their opinion as a non-technical person
on how well they thought I did. Okay, so
those are the main things I did to
prepare. The last point that I want to
put on here, which is the reason I
believe I succeeded in all of the
interviews that I did, because I didn't
fail any of them, is that I had
confidence when I walked into the
interview. Now, the reason I was
confident was because I knew no matter
what happened, I had done as much as I
possibly could to prepare. I put in the
time. I studied correctly. I did this
properly, right? I was putting in
quality. I wasn't just kind of wasting
my practice. And I knew that even if I
failed this interview, there's nothing
more that I could have done. I prepared
as best as I could. If you have that in
the back of your mind and you know no
matter what happens, it's honestly not
your fault. You've done the preparation,
you've done what you can and the result
will be what it will be, then I think
you just have some underlying confidence
and kind of the way you present
yourself, the calmness you have wears
off in the interview. And at least for
me, that's what I felt happened. And I
knew doesn't matter if I fail, whatever.
It's all good. I move on to the next one
because I prepared as much as I can and
there's just nothing more I can do. So,
I challenge you, get to that point
before you walk into some of your
interviews and just know in the back of
your mind, you've done everything you
can. And if if you fail, you fail. Is
what it is. You move on to the next one,
right? There's nothing to be worried
about. You did everything that was
possible. Okay, that's all I have for
this video. Again, if you guys want
assistance with this, this is exactly
what I do in Dev Launch. I literally
teamed up with someone who's an ex
Google, ex Amazon employee who's given
hundreds of these technical interviews,
who's really nailing the process for our
students in this program. If you want
help, apply from the link below and I
will see you guys in another video.
[Music]