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.