Hi everyone. My name is Patrick you in for
today's episode, we cover hackathons startups, as well as
data science. And for today's guest, I had,
krishnaiah Khan was a co-founder of a neuron AI, as well as a
YouTuber. I'll put all the links to
socials in description below. And with that being said, enjoy
the episode. I saw you guys, you guys with I
knew run, also organized like a big hackathon thing.
Yes, how'd that go. That's what that was quite
amazing. You know, he have a very big
office. The side over here, so we can
accommodate around 500 to 600 people at a time.
Nice. So everybody, like, we usually
keep it as a 24-hours hackathon. Yeah, so all the people out
here, itself will sleep ovae. Trink do.
That's also one and that actually gives an amazing
experience. For all the people out there
units is developing a product Within Yeah, would product one
in the end or is it still ongoing?
No, like, as soon as the 24-hour gets over, we take the poor, the
submission and we give the rewards then in there.
We make sure that we make the vital to make any eye
application. There are multiple problem
statements that we usually give. Yeah.
And I like many companies also do a tie-up with us, you know,
who specifically want to develop some products within 24 hours or
just start of a product? Yeah.
And through that way, you know, they they they finally see the
product and yeah they also quite happy, you know.
So by just seeing Look at the developer Community is quite
strong that and obviously because of covid and all we
could not do this before but now we are really having a lot of
fun. Yeah.
That makes sense. Meant 500-600 people in a huge
hackathon kind of because it was also a competition right there
was there were prizes involved in stuff like that.
Yeah. So like it's it's a good amount
of price you know. So it probably talk about
somewhere on five thousand dollars for the first rank for
the first winner, you know? Yeah.
Then we have a lot of It's distribution.
So, overall we distribute somewhere around ten thousand
dollars USD dollars. Yeah.
To all of that apart from that, we also give some companies like
last time we had the hackathon in collaboration with Jen
brains. The jetbrains gave them
developer license you know with respect to the tools that they
use and really cool. Yeah, I think it is so
important, right? I mean we have software
Engineers data engineers and data scientists in a lot of
companies, right, if your company is not there, Little
you're already behind in most Fields or most domains that are
out there that are consumer-based, right?
And having that time that freedom to experiment and just
play around with new technologies or be Innovative
and kind of a hackathon. I think is so important when it
comes to first of all, your engineering culture within your
company and just happiness within the team that they have
the freedom to stuff like that. Like you get a chance to
interact with all of them, right?
Yeah everybody has a separate kind of questions regarding the
carry regarding many. Things are such an, obviously he
that kind of postings that they will be doing in this digital
era right in Instagram LinkedIn and all right.
In short we are actually building a community developer
community and building a developer Community is so
important. You know, in this open source
world where many things are available for free, completely,
right. Giving you as an inheritance.
Open source all together to use all the products itself, which
is super important. Because of that, we are able to
learn so much and we are able to do so many things like data,
Sciences, all together. Like all the libraries that are
available, currently it is open source, just imagine anybody can
use it. Yeah, and develop some amazing
products, right? So, that is the reason why we
keep this kind of hackathons to promote open source activities
or not. Yeah, yeah, I completely stand
behind that. Right.
You wouldn't want to reinvent the wheel over and over and over
right once Have this kind of piece of information or piece of
software and it's available for everyone, then everyone gets
better because of that, I think that has allowed kind of the
tech space to evolve exponentially or don't know
what's even faster than exponentially, but that is what
it feels like, right? When someone has something
that's really cool, goes into the community.
I hear it from my colleagues, I hear it from my friends, I see
it on Twitter or somewhere else and people talk about it, people
experiment with it, people see. Okay.
What is the maturity level? Evil, what still is lacking?
What we want to add and have that dialogue with the people
creating it if you're so cool everything is transparent and
open in that way because you feel involved and not just
informed right? You want to be involved in Iowa.
So I had the best thing is that you get to meet a lot of people
Let It Be virtually or you know off in an offline way.
A person who's there and u.s. definitely knows about me
because I am teaching data sites.
I am today having a conversation.
With you so this way, right? So this is quite amazing.
We get to connect with lot of people get to share knowledge
with here each and with each other.
You know, definitely that actually leads to an amazing
initiative of community building all together.
Yeah, yeah, I absolutely agree. It makes the world feel so much
smaller because there's still a huge world.
I mean, we talked about traveling kind of in the
pre-show. I haven't been to all of the
countries nor do I think I will ever but I do Get to talk to a
lot of people from countries, I've never been to, which is
awesome, right? That world, that is huge out
there. All of a sudden, gets a lot
smaller, but just meeting people and humans are very much Social
animals. Right without social
interaction, we're going to get depressed.
We saw in covid, with isolations and lockdowns, and a lot of
depression happened there. So, now, it's kind of opening up
and it's allowing for us to be social again and have that
interaction. I really miss that.
So, no worries sign this thing. And this thing is that like, you
know, and trust me like we were planning this events to happen
from a longer time. Yeah.
This before covid. Also we had planned it but we
could not do it because we did not have a huge office at that
point of time. We thought of doing it somewhere
else, you know, like and this kind of hackathons at all.
But again it was costing us a too much of money, you know,
because in this kind of event You know, you really need to
spend things for food for accommodations for different
different things. Yes.
And now, when we don't know, like should I say this like
this, but definitely, this is giving us an opportunity to
really interact with so many people.
Yeah, because jetbrains, you know, they like they, they said
that okay, we are ready to do it for the entire year.
And we also going to even higher, okay, people who are
doing actually very good, you know.
Yeah, so last Kyle probably the next event that we are going to
have with jet prints there. They said that they going to
have. But even though what happened is
that in this hackathon also we had five people, we grow what to
see many people over there. They are right now in the
florets has. Yeah, yeah.
And in the next hackathon, which is going to come up on Saturday
which is again a 24 hours hackathon, we're going to hire
120 people. There's a company called as Mu
Sigma that is going to have 20 100 people and we are going to
hire 20 pee on the floor. That is crazy.
See all of a sudden. It's not just a competition, but
it might also be kind of an opportunity for your career.
I was just really cool. Yeah.
Because whenever you take one interview right, within two
hours will not be able to understand the person compared
exact. Let's go or three hours, right?
But here, if a person is developing, a product, isn't
he's playing with the entire team is working with the entire
team. And at the end of the day, you
get a permit that is what company requires, right?
Yeah. And I feel that this should be
the hiring process, you know. They should definitely make some
changes. In the hiring process not just
by one phone call and then one face-to-face meeting, nothing
like that. You come over here, build a
product. Let's simplify hours what you
do. Then you ask how he'll do you
want? Exactly first show.
Show what you got and 24 hours. So I'm wondering 600, 500
people. That's a lot of people, right?
If we look at the teams in the teams that were really
effective. Did you see kind of how do you
say that kind of a common field? How they approach things?
For example, did they figure out that Start drawing and be like,
okay, this is what we envisioned before they started building or
that they start building and creating different stuff and
trying things out before actually figuring out which way
to go. What work there and what didn't.
So see, whenever we see in a bigger company, right?
Whenever you have given a project or a product to develop,
right to go with various stages, right?
And there are design, team will be separately.
A requirement Gathering team will be separate where a
developer team will be separate. Yeah, we'll be having product
Agent. But here you are, just two to
three people. Exactly.
And I've seen people, you know, drawing diagrams then, and there
it's a of Designing something, you know, out of it, the doing
it pen and paper, you know, that was the most fascinating thing.
Then. Yeah, there is a store drawing
it with pen and paper. They're coming up with some kind
of conclusion that discussing within the team itself and
finally the able to create a product.
So altogether, like, if I really want to say that, yes, within
that 24 hours, okay, when we give the problem statements
that, we made sure that He added some more new tools.
Okay, let's say you want to whatever use Dockers you have to
use Cuba Nets. You know you have to make sure
that you use this new technology.
Some people were like sir. We don't know that then we told
them. Okay, do one thing learn and do
it because you have still have 24 hours.
Just let me do it quite fascinating, that more than 50
percentage of the people learnt there and did it.
And finally find it at the end of the event, they will sing the
quest. This was quite amazing, you
know. Yes.
We were sitting in home and probably participating in this
kind of hackathon in an online mode, we could have left it in
the halfway. But since we are sitting here
for 24 hours, you know, we got that kind of confidence by
seeing others because others also, learning and others were
also trying to do something. Yeah.
And they did it, you know, it's quite fascinating to see that.
So that was an amazing experience altogether.
There is awesome. I didn't know you gave such
guidelines like alright, we have a problem in.
This is what the solution needs to be.
I thought it was more free format.
It is very problem statement, is that problem statement is
clinically there? Oh, can you say them that?
Okay, you have to use this good practices like get GitHub
jackers, you know, Cuban. It's because this is what, the
companies are required. Exotic the any company who are
hiring? Yeah, we gave them this problem
statement. They said that we don't do this.
I think okay, you have 24-hour learn it, do it.
That is what developer do. Yeah, exit.
The that is exactly what I was going to say, right?
That is the skill that you need to have because Technologies are
going to be evolving, right? It's darker now.
Could be It is now in the future, it might be some whole
other thing. And then are you going to be
like, oh and I don't know that I'm going to go to my comfort
zone, or are you going to step out of that?
And be like, actually, I need to be able to learn this because
this is the new technology, right?
And we've done that in the past, we're going to keep doing that.
It is really cool because that means you get to learn a lot of
new things and stuff is continuously evolving.
Right? You need to challenge yourself
but it is completely different than I think traditionally Jobs,
right? If I'm a carpenter I'm gonna get
new tools but it's not going to be next year.
It's going to be in 10 years and then I'm going to be like all
this is very similar. This is like a slight upgrade.
I'm always going to have my carpentry skills.
So for engineering data science data engineering, nothing like
that. Pink, what we found out from the
entire audience, right? There were also people who are
from 10th standard in 12th standard oils and one of the
hackathon person from 12th standard, you know, he's still
in high school. Yeah, just imagine, he is 1/3
price, you know, a ribbon, then according by himself, then tar,
hackathon. He completed it.
Okay, and just to support him, his dad was also there along
with him. Yeah.
But the entire work I had seen him throughout night toward
equity for events. He was writing each and every
line of Put together. Yeah, and he built one of the
most amazing application, and the code quality was quite High,
okay. It was like, it was like an
experienced person, code loading, you know, something
like that. So it was quite good to see that
and he won third prize over there, that's a single crazy.
The think people like that, start really young and just
become like that. Let go.
Then we got to know that. It was this third hackathon?
Okay. He had already won.
The second hackathon. Also, and third a katana.
See And so yeah. Yes, he started quite early.
Yeah. He's been doing this for a
while. Yeah, makes that and his dad is
a scientist actually over here. We have something called as ADI
ADI. Oh yeah.
In India. So he was a chief scientist over
there. I think it's all about the
support, exactly support and inspiration there.
That makes a lot of sense. It's very different from how I
got into kind of software engineering because for me, it
was, I didn't know what I wanted to do coming out of University.
They know what I wanted to Go into the job market and then
through actually joining and starting job as a junior
somewhere. That's when I learned to get
this is what I want to do, right?
And then I had to kind of kick off that learning process.
I think it's very cool for people that are a lot younger
than I was back then that they already know.
Okay, this is this is what I'm going to try and do this is what
I'm going to experience because there's not necessarily an age
limit, right? You just need to be able to pick
up new stuff. Make stuff happen and it's very
visual. You can see if it works or it.
Doesn't what it looks like and you can learn from others,
right? Are we a lot of the information
is out there for you to pick up and teach yourself?
Yes, yes, it's all about the confidence and things that
you're actually want to do in the future right now.
If your goals goals are set, you want to achieve that?
I think age is just a number. We see exactly how I want to.
I want to learn a bit more about kind of the startup that you
build out that sigh, I know. On a IR.
Oh yeah. How did it come to be or when
did you decide or How to have that go.
So somewhere in 2015-16, right? We had always an idea like I was
a mentor at that point of time. I used to teach people, you
know, with respect to data science from then itself.
Yeah. And one thing that I used to see
that people were lacking things, what they are learning and what
they're implementing in the industry.
Okay, at that time. Yeah.
And the companies that were into this sector, ho teaching data,
science data, engineering, and all are, let's say with respect
to other So we should just teach some basic things.
You know, that was really not at all similar to the things that
we do in the company, like deployment scaling, a guy up,
and doing multiple things. Yeah, at that point of time, I
thought that okay. Now, I've gained so much of
experience, Why not start a start at that point, but still
thought process, we started at that point of time.
And one thing that I used to see is that okay cost Factor was
quite High, you know. Let it be in India specifically
real. People were charging Hefty
amount of money. Okay?
You know, other start teaching the step because if I know this
Tech, what one cost you this much?
Yeah, we definitely want to teach you in a such a way.
One important thing about education is that education
should be afforded and the quality should be high.
Exactly. So this was the brand Moto that
I had always in my mind before starting it up.
Okay. And after gaining so much of
years of experience at that point of time obviously Had he
not had any kind of funding, it was just personal saving.
Yeah, so I just delete that plan for another two years in 2018
19, which started out startup itself and we made sure that
quality is high affordability should be affordable.
So hardly in fifty, fifty dollars.
Let's see, if $50 you get to attend a six months, live
session, and respect to any Tech, any Tech you want, yeah.
Okay. Like Java data science
JavaScript, you know, AWS cloud. And so that kind of live
sessions. We have already started and
apart from that. We also created an Ott platform
where you get to 50 plus forces. Yeah.
And you also get a chance to demand any courses that you
actually want, okay. And this is for yearly
subscription and that is hardly somewhere around. 50, $60
itself. We re subscription.
Yeah. So we have reduced the cost
completely. We have made sure that the
quality is increasing and the quantity is also increasing.
Yeah, that sounds awesome. I mean, You want that, right?
Education is kind of weird in Holland.
It's very affordable to go to university.
I know in in the US and the Americas, it is insanely
expensive and I don't necessarily understand it the
whole system behind it. I've seen the newest that devops
Coast actually cost you somewhere around ten Cate
dollars, this ridiculous, right? I can teach you in $50.
That's ridiculous. I got it.
I can say go and upload that I'm videos in YouTube If I want.
Yeah, I probably take up the subject to work.
Exactly, right. Yeah, I don't get how those
business models work because you are you're competing against
either very affordable or completely free on YouTube.
So I I still don't get how that how that works and how that
operates? But the thing is that in our
company, what we have done is that we also have an R&D sector
R&D. Sector basically means anybody
who wants to incubate do internships in our company?
Yeah, they're free to do it. Okay.
And the projects that we actually We develop over here.
It is really, really relatable to the things that are happening
in the company's, okay. So a person who actually invest
three months and I knew Ron I complete this projects.
If he goes out is job-ready actually any companies will
definitely higher in hand from the last year.
We have done more than 2,500 plus transitions.
People from different different backgrounds domains.
You know they're made successful.
Career transition in these things.
Yeah very cool. I had a thought that I lost it,
I you were saying that there's a there's a difference in what you
can learn and what you can teach yourself and what companies
actually use. And I've heard that before but I
don't know how that goes wrong, right and University.
You get to kind of learn in a bubble, you get kind of
theoretical problems and you're going to build your Solutions
towards those problems. There's a piece of kind of
practicality that's missing there because when you draw an
organization, I mean hackathons you start from scratch, right?
Usually, when you join an organization, a lot of stuff is
already out there. So you have a lot of kind of
change when it comes to chains, when it comes to Technologies
and choices that have been made and you either need to build on
top of that. Or if you go against it you need
to have very good reasons because that's going to impact a
lot of stuff. But there's a gap there in what
you actually learn either in your educational Journey or even
the content that is out there and what organizations actually
put the practice. But I don't know why that Gap is
There doesn't make sense for it to be there right?
You want to be ready as soon as your educational Journey ends on
a more formal level. It's never actually going to end
because you're going to learn on the job but what do you think
that Gap is there? Thing is that like see I am in
India, you know, the colleges that we also say, we basically
say as a tire, one tire to Tire three colleges right now.
So if I just talk about MIT in u.s., okay, so it is a tire one
quality. Similarly, in India, iat's
colleges are like, fire one qualities.
Yeah, but I want I to if I say and I T's I T's like this is all
colleges. Are they now if I probably try
to see Tire one and try to college with respect to tires,
three colleges, This Gap is more entire free.
Colleges Okay, the reason, you know, if I had sorry don't
worry. So again this change is that is
going to come up you know in the future I think this thing will
try to focus more on the Practical aspects.
But one thing, one quality thing that I've seen entire one entire
to colleges that they are reducing this Gap.
There You sure that people when they pass out of the college,
our industry. Ready?
Hello, and again, over there, it depends on the facilities.
That actually the colleges are actually providing yellow and
now the call is a becoming more competitive because everything
is available. Now in YouTube, examples of the
things I available in YouTube and definitely startups, like
us. You know, who already have that
specific experience? We're trying to teach students
then and there. So a student who is actually
less We are, you know, we start working on different kind of
things, that it be a research, let it be his own publication
that you want to really do, or you want to publish is on paper,
right? If I talk about the reason why
this are things are happening, like okay.
If again it can be a political reason all together, you know,
it can be reason because they're that is the reason why so many
high-tech startups are already there, you know, and now people
are getting more knowledgeable with respect to this.
I don't call it is in the future.
I think will definitely reduce this Gap until try to bring more
practical things, and it may also depend on what college can
provide to the students. It is not actually flexible that
the college can provide everything to the students at
once. Exactly, maybe a cost factor,
that will be involved. There may be people who may not
be, that was killed, you know, because in colleges, you know,
you'll find teachers you'll not find mentors.
There's a difference between teachers and mentors it Exactly
a mentor is a person who actually shares his experience,
a teacher, only teaches things, right?
So a mentor can actually do a work of both teacher.
Whereas, a personal guidance, we can actually provide how you can
actually Implement all these things.
Yeah, this is one of the thing and in most of the college that
I have actually found out teachers also lack a lot of
practical experience you know they lack a lot of practical
experience. They may have never worked in an
IT industry but they are teaching some Computer science
subjects. Yeah.
That is all that maybe 13. Yes, I've seen that.
I've seen that many teachers like that.
Even in my colleagues also I had teachers who just had a bookish
knowledge but no way practical knowledge was there.
Yeah. So this kind of situations
because of this, but in the future now, since colleges are
getting competitive College, also hiring mentors in such a
way that at least they should have some number of years of
experience in diet industry. Exactly getting yeah, I'm glad
you said that because I hadn't I realize that but I do think I've
seen that in that kind of the practical skills are lacking.
And I absolutely agree with you that teachers teach and mentors
also coach and on the job, right?
It's not a cookie cutter mold. So it's very personal it's a
very much tailored to the person that's supposed to you.
If you have a kind of a mentor-mentee relationship and
it is a lot of listening just just to add one point over here.
Is that what all the teachers are like that?
I get that. Yeah there are some Teachers who
are in this specific mode but other teachers also quite bright
over here, you know? Yeah.
They, they have an experience, they do a lot of research.
They publish their own paper, you know?
And that is the reason why I said I run it by 2, right?
Yeah, we find this kind of teachers, mostly entire three
colleges and all. So that particles that, what is
my observation? That that have a cheese told you
right now? Make sense.
Yeah. What I was thinking is so you
learning University, are you? I learned about data science a
lot and I went to college in like 20 17 2016.
So then it was kind of up and coming, we were talking about
this. This is probably going to be a
good career path going into the future because then it was
still, it wasn't necessarily trailblazing, it wasn't in the
Forefront, it had been established and we could form
education around it, which is why I actually got it.
I had a university, but it was also very new not a lot of
organizations have the data, we're ready for it.
Had any idea what it would mean in there.
Team structure in their organization structure.
So organizations are also lacking behind a lot of the
theory that universities teach. I think that also absolutely
will contribute to that Gap there because you're going to be
ready from University, you're going to have a lot of theory,
3, radical knowledge, but you can apply that because
organizations might not be ready for that in the few next few
years. That is going to basically take
some time. Yeah, we say that, right, right
thing is going to happen, but it is going to take exactly the man
organizational change. Takes a long time.
Right? That's pretty big organization.
Not startups. Exactly is really in the to make
sense. So you start your startup is a
2016 2018? No, no it's in 2019 October
after we started it up. Yeah, so the last few years,
what are kind of the biggest learnings you've had since then
because you started out with a goal right education, high
quality and very much affordable.
What was kind of the first step you took towards that?
Was it set up a website, set up your own, your own practical
guides in that way, how did it come to?
What you described earlier and where it is now?
So, we started very slowly, you know, it took time to develop
our own portal but parallelly, we started taking up classes,
okay? And, and probably around six to
seven months, it took us to make sure that our portal is actually
fine with respect to all the, all the functionalities that we
really wanted to put. Yeah, then what happened is that
since our price was really less trying one biggest challenges
that we got a lot of From the audience, you know, they wanted
to come and learn from us. So, with insect six months, we
were thinking that how to handle this big audience and that is
the major thing in edtech. You cannot just know if that
thousand two thousand people, you know, you have to make sure
that each and every person clarifies this doubt in a better
way, you have a kind of one-to-one interaction with
them, you know, that that point of time we faced a lot of
difficulties in building our team.
You know? Yeah.
Because we have to really build a team in Such a way that they
should be able to understand us. They need to understand how
Vision, okay? And this usually took time
around three to four months. We have to make sure that it
took us all a lot of moment of time.
And what we were also doing is that those whoever won getting
Lon whoever learning from us, right?
Once they completed the courses, we had them directly because
they knew the entire syllabus. They knew that.
How do we teach, you know? Yeah we hired them directly.
Right. Now in the floor, anybody you
see, has been taught by a soul. That's very smart.
Yeah, yeah. And because we really to build
the team who has the same kind of thought process, exactly,
because of that Weekly, efficiently, build up team
properly and we came up together and then we started also giving
live Skype support, okay? No Live sketch.
But basically means any 24-hour, 7:24, any time that you have any
queries, you just wanting in the sky.
Yeah, or you can turn through the chat but that is available
in our website, the query will be solved then and there.
So this really one thing I thought that none of the attack
are actually doing. They usually say drop us an
email will reply you back in 24 hours but we do not want to give
this experience. We want to give the experience
then and then only we need to solve your issue.
Yeah. And that was like super like by
all the people out there, you know, and then you know we came
up with most of us has like internships, we really wanted to
provide internships to all So that basically means this
internship is open to all from any part of the world.
You can apply internships and ironing you have the entire
problem statement. What project you need to be
solvent. Everything is available in the
portal and dashboard, just need to go and start solving and
there. Also we give experience letter
to the people who won some read the projects and are you know,
so internship is started. Then we came up with something
called as incubation Center. So when we started teaching more
and more people, you know, so people came up with some
amazingly Amazing ideals. Yeah.
And they really wanted to implement it as a start-up.
So we thought that why not we'll help you out.
You can use our office space. You can use.
We also make sure that we give food everybody.
Like for all the employees. We get through free food.
Yeah. In our office so they can they
can come and just focus on the work.
Okay, cool. So anyway, yeah, so this is the
thing. Now in that incubation Center,
once you develop a POC then we fund your product.
Okay? So that you can take it for the
larger scale So that functionality, that that feature
also be added in our things, right?
Yeah, the next feature that we came up with that when we are
launching a OTT, platform, many people said that Christians.
Some of the courses are not available in the Ott platform,
okay? Like if I take an example of
Netflix, you cannot title Netflix.
I want an action movie. This should be the hero that
should be the actress only, you cannot say that.
Yeah. But we have given them the
option, you can tell us, you know, TT platform, what courses
you and we have comments that that within 60 days.
We will try to upload the course.
Yeah. Okay so this feature also we
brought them and from there like we started with 100 courses.
Now there are more than 250 plus courses.
Yeah, that's crazy. So this all things and slowly we
are still add, yes. Trying to find our problems yet.
Still trying to add more things to the people.
Yeah, mock interviews, interview sessions.
Resume building everything on the go.
Yeah, right now, the team team was in the floor.
They are right now, taking mock interviews because this Saturday
Sunday we have Hiding that is going to happen in my liver.
Awesome. Listen, rather.
Yeah, really cool. That all things are going on.
It sounds it sounds very practical, right?
You see an opportunity and you go for it or you try things out
and you see if it works if yes, then scale it if it doesn't.
You move on to the next thing hiring people that are early on
and taking your courses to me, that sounds like a really smart
thing to do because those people understand a lot of
requirements. Yeah, I have a lot of
requirements side. Now also we are looking for
people who can IRT. Yeah.
Yeah, that makes sense. I mean, you want to, you want to
keep growing but those ideas, right consistency, is their high
quality is there. It's all about education and
smaller steps. Take you forward.
I think it's really cool to hear that.
Now, it hasn't even been that long.
Right? I 19.
So, like that. Really cool stuff.
I was wondering when I looked you up.
I saw something about, like, a GitHub star, kind of thing.
What is that? How did you get that?
This is basically. You have it opens?
Most efficient? Yeah, very cool.
This is a good house to get up star.
You can see over here. Yeah.
So what I did is that I used to as I said, right, I used to
upload a lot of YouTube videos, right?
Yeah. So through that way, I used to
teach a lot of things to a lot of Open Source contribution,
share knowledge with the people, you know.
Yeah. And one fine day.
I don't know. Someone nominated me for this
getup star awards. Very cool.
The next day. The next day I get an email from
GitHub saying that. Okay, you have been nominated as
the Of start. And I think in India, hardly you
have three to four people. Okay, entirely with this.
So you get some amazing goodies. You get to represent GitHub
nicely because last last to last hackathon, we conducted a
hackathon in collaboration with a bicycle.
Yeah, that's from Gustav. I really appreciate it when
companies do stuff like that for the community because it's
giving back, right? It shouldn't be like, ah, we're
just taking from the community and we're making money and stuff
like that. I think companies also need to
give back and I think this is a form of that, which I really
appreciate. It's exactly, like organizing
hackathons and bringing people together bringing communities
together because together, you learn, right?
It's all about collaboration and, and improving together in a
way as well. So in the upcoming two months,
we are packed with hackathons and good stuff.
You said 24 hours. That sounds tough, though.
Like it's 24 hours Hands-On. I mean, they probably take
breaks and stuff. But 24-hour, focus is, is a
tough one, but we give our all the necessary things like Red
Bull. Gives you wings fly.
Yeah, it makes it fly, right? So say this is the challenging
thing. Top.
That is how product is actually built.
Trust me like a company can actually notice about a
candidate. A lot of things from this
hackathon. Yeah, you know, if you are able
to develop a POC product in 24 hours, just imagine what the
company requires this because so many ideas will be going on.
Let's say startup today, I want to implement so many things, I
have 10 different ideas on my mind.
I want to implement that specific thing.
Yeah who my baby, whom I will be dependent on this kind of people
who are able to build a product in 24 hours.
Exactly right? Yeah, the thing is.
So I think in some way those 24-hour hackathons are easier,
right? Because you have a very clear
scope, you have some guidelines with regards to Technologies and
your focus is building the solution.
What is harder in an organization is figuring out
what solution you need to build communicating with the
stakeholders. Make sure that all their needs
are met. People have hidden agendas.
Do some nasty things deadlines. Get moved up.
You get blamed for something you didn't do.
That is is in an organization or can be and that makes the end
product actually a lot harder to build, which is right.
If you remove all of that in a hackathon setting, it's actually
a lot easier than in an organizational setting.
There you'll be able to find out the real efficiency of the
entire team. Exactly.
You always need, you always need both skills, right?
The hard skills of actually getting it done being able to do
it, being able to teach yourself those Technologies as well as
the soft skills, right? Skating, which way is the right
way challenging requirements and stakeholders.
Making sure that actually meet the deadlines with the scope in
the time that you have more and more.
I see you need both sides. We really focus on the hard
skills though. Also when hiring I think your
voice is more common. Did we lose our DVDs?
Audio? Yeah.
You audio was last okay. Fine.
Yeah, that's fine. I think we're very good again.
Yeah, it's had lost my, I lost my train of thought.
So in the pre-show, I think the audio messed up there.
I wanted to ask you again. How did you get into data
science? Just so we have that in there as
well. Okay, so as I said that I
developed one, you see we got a reward from a company saying
that this is the best t.i. application.
Yeah. That really made me impressed
because I never had heard about a i at that point of time.
Yeah. There was some of my friends who
are doing Masters in US and Germany they told me that.
Okay. I something this is the story of
the ndia then I told you. I was quite fascinated by.
I want to learn this. Yeah, he said that.
Okay, we are doing it two years program over here for the same
thing. I'm okay.
Just do one thing. Just pass out.
All your materials. I will create my roadmap for my
side and probably alone. Everything's yeah.
And within three months I was in a state of mind that where I
could Implement so many things. I got a job in a iife.
Okay. That point of time it was it
somewhere on 2040. Yeah and again thanks to my
friends because they help to help me out with all the things
how to prepare and all Let It Be with respect to practical
impotent intimidation the maths behind all the algorithms, how
you can actually create an end-to-end application.
How to how you can actually deploy all those.
They actually help me out with respect to that.
Really cool. And then and then it was like,
wow. If if I can do it in 3 months
and I still say myself as an average student or average
person to learn something new technology, okay?
Now just imagine if I probably provide this entire thing to the
entire country or entire world, just imagine how amazing things
they can actually do because they have so many people were
smarter than me. Yeah, that is how I started.
Ted into data science and then later on converted into a
YouTube channel. 2018, it's a funny thought because I always,
I'm always, like, man, this is complex.
And then I'm like, okay, I figured it out, but there's a
lot of people smarter than me. They probably figured it out,
but it's starting, right? Starting small actually actually
doing some Hands-On stuff, and it might not be as difficult.
As you think it is to get something small up and running.
That was the one more thing like go has technology, right?
It is always good that you start early because when it is in the
early stage, if you join this right in the in the future, you
may get the maximum Advantage because till then your something
different. You have complete a different
person with a lot of experience, right?
Similarly, other Technologies like blockchain is also there.
Which I'm also exploring parallelly.
Yeah. You know which is quite it has a
lot of applications. I'm not talking about
cryptocurrencies and all but yeah, I'm talking about
blockchain applications. You know what all things you can
actually do. Recently Twitter x to the C.
Alright Jack Dorsey, it also announced about the F5, okay?
So again that is going to be get built on blockchain, Amazing
technology that are going to come up.
I think people should also focus on that what new things are
actually coming and try to put the hand over there, so that
they get the best Advantage out of exactly.
Because I was going to mention that when you jump thing, that
was 2014, that was kind of trailblazing period, right data,
science was very hot at that, at that time, I think And people
are figuring out. Okay?
What is this going to look like it's now 20 22, it's a lot more
mature. Do you think you can still make
that switch? If you're a software engineer
and either going to data science or data engineering with your
kind of software, engineering knowledge?
Or is it, is it too much? Now, normally, I can definitely
make it, you know, I've seen people from non-technical
background, right? Yeah.
Who do not have much programming experience.
Also, a mechanical engineer civil engineer is making a
switch to As data set. Yeah then why not we you know
her data is can go back to software, engineering or
software. Engineering can come to data
science any point of time? Yeah, I think that's, that's
really cool. Sometimes I wonder though is it
too much and everything that is out there because if I just look
at what I'm trying to do, I need to learn the programming
languages. Even not regarding the data
science aspect and need to figure out how to collaborate
with my team members right through.
Probably some version history management to need to figure out
my eye. Be and how I can be efficient on
my own thing. And I have the infrastructure on
which I deploy, right either, that stalker kubernetes where,
that runs Datacenter cloud, and all the technologies that come
with that. If I want to bring it into the
hands of the people, is it going to be web is going to be an app.
What is the infrastructure and networking?
There it is a lot to digest, right?
I love being in a team that is multifaceted because then I
don't need to know everything in that way.
But it seems like a Fungus task. If you want to figure out
everything on your own way also a person who do not have some
basic knowledge on this. The transition phase will
obviously be somewhere around 6 to 7 months.
It won't be just within one month or two months since I was
a software engineer. And you know, about web
application. I knew about mobile apps.
I was working in dotnet programming and JavaScript at
that point of time. Yeah, so I knew that basic
things, right? So for me just to learn data
science and try to convert that same project in Data science
project. It hardly took me three months,
you know. But for a person who is coming
from some other background, yes, some amount of time will be
required, but you really need to devote some n amount of hours
every day. Exactly that is, that is
something n, because you can avoid one hour to hour, you can
devote five hours, it depends on interest, the more number of
hours every day. So consistency, should be there
every day Colonel. You'll be able to make this
transition quickly otherwise it is just going to go with the
flow. Yeah.
I really like that you said every day right?
And sure don't be too harsh on yourself.
Sometimes it's not going to work, but if you have that
mindset, that every day, I'm going to do, I'm going to move
that rock a little bit. Then all of a sudden you're
going to have a distance that you wouldn't even imagine you
would have pushed it. I think consistency is so
important and then you will see progress right now in a week
from now you're going to be like ah last week.
I didn't actually know all these things or look at what I've
created. I didn't know I could do this,
and it's very tangible, the results you will get.
Or the knowledge you'll game because you can put it to
practice or you can take it with you because a lot of knowledge
also anchors and you'll see it in the future.
You'll be like, I've read about this, let me touch upon this and
polish the skill that you already have.
And if you are able to learn multiple Technologies, just
imagine that today. You're interested in data site
tomorrow interesting data in here.
Once you learn something, right, then you'll get a feeling that
okay? Moving to other Technologies.
Also a piece of cake. Yeah.
Because all the base our say, you know, the most of the
activities that we do in the company's almost.
Yeah. Yeah you can.
I mean the biggest skill there is just the will to be able to
teach yourself or figuring out what the best way is for you,
right there. All the documentation out there.
I'm more visually oriented. So, go to YouTube.
I look at what people draw kind of live, or in a video that is
kind of tailor made in that way the digest information faster.
I know a lot of people that love reading the order book and be
like, go through all the details in, they'll learn that way, but
everyone has kind of their own way on how they consume content
and how they learn problem is figuring out what works for you
and then we're the best content is to get that because there's
just too much content nowadays. Also So yeah, to the so many
YouTubers. So, openly building content,
logs blogs are there, so many things are there.
That's quite amazing. Good.
What I was wondering is because we touched upon the kind of
difference between data science and data engineering, but the
audio might have messed up there.
Could you could you go through that again, with regards to the
difference between data science and data engineering?
So if I talk about data engineering, their main task is
how they can aggregate the entire data.
Let's say the data can be generated from some kind of of
iot products. It can be generated from some
kind of devices. Let's say.
So any any anything or suppose if you are interacting with the
mobile app, in a mobile app, the clicks, the kind of interaction
the information that you're feeling, all that can be
captured in the form of data. Now this data, since millions
and millions of users are using this.
So if I talk an With respect to LinkedIn Twitter.
Like so much data is getting generated over there now as a
data engineer might ask should be that.
I should effectively try to find out a way to collect that data
and store it in a way so that I can give this data access to
anyone who basically require this to make some kind of
decisions, right? So as a data engineer, my focus
will be that I should really create a data warehouse or
probably try to use tools through, which I can efficiently
capture this data, do some kind of cleaning store it efficiently
and make sure Sure that I can provide it to the other users.
If I talk about data science we come to the next step.
Now data science and data Engineers are brothers just
consider that because tomorrow they really want to bet the
block something. You know they will be saying
please give me the data okay. So as a data scientist you
really need to take that particular data clean it.
You know after that create a model for some kind of business
use case. And this model will be able to
help you to do predictions for castings.
You know? In short, it will be able to
make the stakeholders to make better decision in theory on
which in turn actually increases the revenue of a company.
Very cool. Yeah, they go hand-in-hand.
I've I mean I've always had those Concepts in the back of my
head but that makes it really tangible and where once
responsibility kind of ends and where the other one picks it up
and makes use of in a different way then.
Do you think it will kind of assimilate in the future?
Because right now, they're very different.
Those roles I've heard in the beginning, this was like 2019
data. Science is very much up and
coming right now, 2020. Maybe even the last year.
I've heard eight engineering has become a bit more prevalent.
I do. See those kind of Shifting, but
do you think they'll ever assimilate?
That one will do all of that? Basically what you just
described? Yeah, so there is a role which
is called as full stack data scientist.
Okay. Full stack data scientist is a
person who knows Big Data also who knows, who knows, data
engineering Workforce so who knows data science work also,
okay? So if you combine this both the
skills probably you become a full stack data scientist.
I never heard that help. Yeah.
Yeah as a other industrial experience, I'm just taking out
this and saying it in front of you because my previous company
like Panasonic, I was working and Panasonic in my previous
company we had some amazing full stack data.
Scientist over there. Yeah you know who used to work
in but big data and data sites also.
So I was anyhow the part of the data science team but just by
seeing the skills that really motivate me, motivated, me to
learn data engineering. Yeah, you get the challenge with
having a separate is that you do need to understand what the
other person is doing, right? To certain degree, not in depth,
but you do need to be able to communicate what the
requirements are, what the challenges are, what the, what
the impediments or so the communication.
In there is very crucial and if you're that one person, or if
everyone understands the change that's happening and that
communication is either internal or just needs to be shared
within the team to get that shared understanding and this is
very high-paying Job. Full stack data scientist when
yeah, I can imagine. Yeah, you are very unique and
rare like, yeah, that makes sense.
So, what I've always wondered is, that's how I start a
start-up where I start an organization, where I want to
get a proof of concept as soon as soon as As possible as fast
as possible to the hands of the user live so we can learn from
that. When will I start collecting
data? Is that from the start?
Because I, you need a lot of data before you can make
data-driven decisions, right? When is it a good time to start
aggregating data? Because I see a lot of
organizations. So we want to do something with
data science. We want a recommendation system
yet, they don't have any history, they don't have any
data, which means if they want that, it's going to be months on
end before they can start. So in the initial stage,
whenever you are developing a POC because the at that point of
time you definitely don't have any kind of data.
So definitely data-driven use cases.
It's not possible at that point of time.
Yeah. So for the products that I have
specifically developed, you know once it is live once user
actually using it. We wait for at least three
months, two to three months at depends on the quantity of data
that is getting produced, right? Yeah, let's say in one one month
of data like you have at least let's say, Island Records.
You know, I'm probably of clean the data.
I've got 1 million records light.
It also depends on what is the quality of that specific data?
See there are multiple ways, how you can decide whether this much
data data will be sufficient or not, depends on the variety of
data that you have depends on the quality of data.
You have, you know? And again, this decision alone,
a data scientist cannot make no, okay?
There will be other people. Like, as I said, domain
expertise, right? Will be involved over there.
No. Yes, we can see that, okay?
With this much data, can we create a model or can we make
sure that data-driven use case can be created?
Yeah, that we can definitely say.
But we also need to have other people in this communication
like one is the product manager domain expertise Pearson and
all. And if you're planning to create
it, you know, we basically keep that data driven use case in the
testing phase for some months. You know, let's say for two to
three months where we just White this feature only to some
selected people whom we know is going to make that kind of
decision. Yeah, just to test for the
testing purpose. Let's say we have some cluster
of information of people you know whom we are definitely sure
that whenever we launch a product they're going to buy
first. Let's say iPhone products.
Yeah you know I have so many people.
The hardcore fan of iPhone or Mac Book.
Let's say okay as soon as a new model comes they'll go and buy.
So this kind of information we can definitely take out from the
data itself and we can Test this model on those specific users.
Yeah. And slowly, you know, when this
is in testing phase, we try to open up this feature too, slowly
to everyone, and this is how it happens in Industry.
So I think whether you've seen this or not, I've seen this in
many companies like LinkedIn. Also, they wanted to provide
some features with respect to job initially, they are
indirectly, do not open for every month.
They opened for a small audience and even if I talk about GitHub,
right, they come up with some amazing tools like GitHub code
space. GitHub copilot.
You don't give this access to everyone initially only for
those people who are interested into it.
So slowly slowly when we try to give this and then we try to see
the performance metrics, how this particular feature is
performing how much accuracy it is giving slowly.
We try to open it up to the environment.
Yeah, they open it up. Kind of in a maintainable way or
in a way they can contain it, right?
Because if they open it out to everyone and it's not doing what
you expect or then the impact is quite quite Hefty.
I just said that quality data is required initially in the
quality data is there. Then only you will be able to
make your product scalable. Exactly.
Because if you have garbage in, then your output is also going
to be garbage, right? What defines high quality data?
To data like suppose. If you had told a person to fill
a survey for, okay, yeah, there's some people who just
feel it for time pass. That's me, recited.
But a true quality data. Basically means how seriously is
filling up this form. How seriously is writing down
that survey, you know, because that actually shows a true
information of a specific person or what ideology he actually
has, right? Yeah.
So that is the reason why I said that, Okay?
When you're launching a product, only give it to some customers
whom you believe, right? These are the customers who are
really using your products. Yeah, makes sense that can be
actually found out from the data itself, not a problem with that.
Yeah. So their intent needs to be
sincere, they shouldn't Miss use, whatever you provide and
give you that garbage data in a way, they're do.
You think organizations can never save or retrieve too, much
data, or even store? I guess, because I would, I've
seen is kind of black and white, right?
Either organizations are at zero level of data retrieval.
Or they're like how we're going to achieve everything.
We're going to save everything. All the data that we have all
the data that we can get, we will save because we might use
in the future. Do you think it will give me too
much also. Yeah, it kind of too much Google
already has so much of data. Even it has your bank
information, banking transactions, everything.
But how wisely utilize this in a typical way that?
That is super important and for any new Top, I think you can get
data. I've seen people actually from
somewhere. They buy that specific data,
which suppose, if you're selling something, yeah, leads data is
something different in it. But if I talk about most of the
data, that is being captured by bigger companies through the
application where they have millions and millions of users,
you know, so yes, again one point that I really want to put
in an ethical way, how wisely use the data, that is super
important. Yeah.
Not matter whether you have a huge data or small data but
definitely matters for this specific product.
Yeah, crash. I really enjoyed this
conversation. We went over kind of hackathons
your journey with. I knew Renee I and then we ended
with a little bit of the data side of the tech space.
Is there anything missing that you still wanted to share?
No, I think we have covered almost everything.
Awesome. Awesome.
Whenever you're in Holland, whenever you're in Europe, hit
me up and we'll, we'll do this again.
Definitely, not a problem. Krishna everyone.
I'm going to put the links to socials in the description below
and thanks for listening. We'll see you on the next one.