AIML Event Feb4

Home / AIML / AIML Event Feb4
live-webinar

Held on February 4, 2021 @ 6:00 PM

AIML will see massive hiring in 2021.
How to build expertise?

Aritro Bhattacharyya
Sr. Director
TalentSprint

2021 is here and if your looking forward to scaling up your tech career, the sun has finally decided to shine on you. As per TeamLease, IT hiring for new-age digital expertise like AI/ML will grow 10-12% in 2021 as global purse strings loosen. How can you become conversant with AI/ML technologies and tap this opportunity? This video puts your never-ending doubts to rest. Watch!

Watch Webinar Recording

About Advanced Certification Program in AI/ML

Advanced Certification in AI/ML is a 6-month in-depth, and comprehensive program. It enables working professionals from around the world to build AI/ML expertise from India’s top Machine Learning Lab at IIIT Hyderabad. The program is led by collaborative faculty from academia, industry, and global blue-chip institutions. The unique 5-step learning process of masterclass lectures, hands-on labs, mentorship, hackathons, and workshops ensure fast-track learning.

Event Transcript

AIML will see massive Hiring in 2021 - How to build Expertise

All right. Good afternoon. Good evening. Good evening. kerogen. Good to see you after a while. Yeah, same here.

So let's get started. You know, we will just probably about five minutes late, we'll try and make up for that time in in as we go along. So, hi, everybody, welcome, you know today to the session that we have here, develop, spend about and are talking about the opportunities that are there in AI and ml and you know, how you could look at benefiting from that as professionals and what other professionals have also done over the years, you know, in terms of upscaling themselves, in terms of the skills that are required for AI and ml. My name is Ernesto Bhattacharya, I am the Senior Director for recruitment at talentsprint. So when I say recruitment, I mean student recruitment. Most of the cases, you know, we deal with a lot of working professionals as well as college students, but, and I spend my entire life in the people development space, be it here at talentsprint, or in my previous roles as the admissions head for the PGP program at ISB. Or with Pearson Education, the largest education company in the world where, you know, I consulted for human capital in the human capital consulting space for about 3040 or fortune 500 companies. So that's me and Good. I'm glad to be joined by culture. And today he's an alumni of the first AI ml cohort of AAA at Hyderabad and talentsprint. So collegian would you just want to start off with a small introduction about yourself, and you know, then we can get started.

Sure.

My name is colleciton. I am currently working as a medical imaging specialist in Novartis Hyderabad. And coming to my background, I was an element a of talentsprint for the very first patch panel and way back in 2018,

right, yeah, yes.

Yeah, exactly. And, yeah, since then, I worked with two different companies on data science. So starting with Wally worleyparsons, where I worked as a data science manager. And right now we are it is my stint with medical imaging, using AI at Novartis.

Excellent. So yeah, thank you courage and we will get, you know, I'll bring culture and in, you know, as we get along, yeah, so I can see some of the questions have started coming in. So probably just to run a poll, you know, of the people who are attending the session, how many of you here are with without work experience, if you are freshers, and all, if you can just write that in the chat. That will give me an idea about that. And you can also start sending in, you know, couple of your questions on the chat window. So we are so I just have about five, seven more slides, you know, that that's there. And I'm going to tend to, you know, bring in culture and in between as we go along. So, so yeah, let's let's dive in. Let's talk a little bit about talentsprint. Because, you know, they've been exciting changes that have happened in our journey. And I think, and that that's something that's happened for the positive so we are now part of the National Stock Exchange, you know, recently, a couple of months back now we we've been bought out by NSE, which puts us in a very strong position NSC being the largest stock exchange in the country, almost like a pseudo regulator, so to speak. And and it opens up opportunities for us to work with even larger institutions both in India as well as outside. So now Yeah, so now we are we are a part of the National Stock Exchange group, we work with the top academic institutions which and in the areas of deep tech, you know, in terms of like, you know, triple IIT Hyderabad, we are among the first companies to have launched an AI ml program, an edtech company to have launched me I will program in the country college and like you mentioned, was a part of the same. You've gone on to launch very interesting programs B to AI and marketing with AI in Calcutta, or, you know, digital health and imaging again, which uses a lot of artists Intelligence machine learning in the healthcare space digital health enabling that the program that we launched with ISC, two, you know, regular programs like, you know, cybersecurity, etc, etc. So these are so usually we partner with these top top academic institutions to provide programs for working professionals to help upskill themselves. So that's, that's one aspect of what we do, we also work with a lot of these global blue chip companies in helping augment their talent pools. So we work with, you know, Google does a program called, you know, Women Engineers Techmakers that we run with Google, that's again, primarily for underprivileged girls to become top notch engineers. And, and, and, you know, then go ahead and bag got extremely premium job openings. In large companies, we've placed you know, you know, we've done almost about two, three of these batches, the two year long program that we do. So that's, that's, again, that's where primarily we work with the college space won't focus too much on that.

And, okay, so let's, let's just talk a little bit about AI, you know, what's what's going on, in, in, you know, Ai, this is a, I believe, a report, which was brought out by Ernst and Young, so where they were talking about, you know, the growth of AI and the impact of that AI is having on the economies, if you really look at it, so, you know, developed Asia and, and the rest of the world I think India comes in the developed Asia part of it, where if you really look at it, and it's all around, I'm, if you've been reading news, etc, I don't really need to spend too much time around it, the advent of the pandemic has just helped us get you know, get to an adoption level, which is going to be much faster than what it is, but having said that, you know, our skill gap in India is still very high. So, most cases, you know, companies and this, this is, this is being brought out by multiple studies, etc. Indians do lack a lot of, you know, technical skill sets to be able to use AI, which is, which is great, because, one is the fact that there are a lot of openings, which are there, but, and people with skills, will be able to make the most of those openings, in the midst of the pandemic. You know, this is a personal anecdote that I can share with you, you know, where there was everybody was talking about job losses, etc. But people who had skills and especially if you know, Ai, skills, Ai, data science, you know, related skills, and all, nobody actually lost a job and there they will still openings companies were recruiting in big numbers, even for, you know, even in the midst of the pandemic. So those skills gaps are, are there and and programs like ours, and so many others that are available, help address these skill gaps. So and, you know, just couple of I think this was this was out a couple of weeks back EBI is planning to hire some 9000 ml professionals in 2021. About a month back does that come out? I was just doing before, you know, coming into this webinar today did a very cursory search on jobs that are available in the AI and ml space. So normally had 7000 plus openings. And this is like fresh data, I just did that search about two hours back. LinkedIn has 13,000 plus openings, indeed has 5000 plus openings. And these are these are the published openings. And then and then you know, they have these internal job. jobs that keep coming in new projects that keep coming in for which they kind of upscaled employees in organizations, then sales, or people who already had those skills in the organization, they get to be a part of those projects. average salaries again, this was you know, from Glassdoor, this is what you know, we were looking at. So glad to bring in college. Aaron over here. Culligan, you you were the first you know, you started off your journey at you know, almost two year two and a half years back when AI ml was a it was there, but it was not it had not taken the form that it has taken right now. So what is it that you what is it that led you to you know, come and look at AI ml as as something that you should build your expertise and

yeah, I mean, when I did that, it was very, I mean, 2017 where it was like just in the newspapers about data scientists being the most sexiest job of 21st century and all of that. I mean, those those things Definitely attracted me. So main reason was to change my career and then have a like, what is I was already 16 years experience. When I initially considered and my entire career was in oil and gas, I was doing data management, which was not related to programming or not related to programming skills, etc. So, but still, I thought, okay, let's give it a try, because it sounds something really interesting. And I started kind of trying to What do you say, experiment, try courses online, learn a bit, try running programs on my local machine and things like that. So that's that was my initial reason as to why I started out is because of what I read around about the hype and all that and I've got nothing to lose by learning something new. So

absolutely, absolutely. So you said the, you know, just like to pick up from, you know, the your answer to that question, but you said that you tried online resources, etc. So what was the experience with, you know, these online resources, but obviously, I mean, you decided to do a program, which was, which was kind of not an online program, what were the resources that you looked at online, if you remember?

Yeah, I mean, I did training for Microsoft. There is a special course on Microsoft about data science, basics, and fundamentals. And then I then I got into YouTube, where YouTube kind of led me everywhere. I mean, I just jumped from one playlist to other playlist. And it was crazy, because data science ocean, and it's just like, there's so many things to learn. I mean, do I learn Python, NLP, computer vision, open CV? Where do I get started? So it's just like, I mean, I spent a lot of time hopping from one series to other series, trying to hit the right one. Yeah.

Okay. And I'm sure you would have seen a lot of these. And yeah, one caveat that's there that I would like to give is that Ben cultural did his program, the program used to be completely a classroom based program, we've tried, and it used to be a three month long program, which now has become a six month long program, because we've kind of moved thanks to the pandemic, bureau last year, we've had to move sessions online. And and, and just to maintain the rigor of the program and the quality of the learning, we've actually doubled the time of the program from three months to a six month long program. So that's, that's something that's there. So while you may. And the interesting part is that even though we moved this online, the feedback from participants has gone up, because, you know, a college alum would have done the program on like, in a live classroom with the faculty talking to him, etc. Our programs, again, are not, you know, they are not recorded sessions, they are live sessions, even though they are now delivered online. So that's something that is very good. And so let's, let's understand, you know, let's talk a little bit about the sectors in which you know, ai ml is, is there and what's happening. So if you really look at and these are, if you if I mean, I've probably covered some five, six sectors, if that's, that's your, and these are the top sectors where you look at AI ml being used. So, except for the ones there on screen, I was going through this report, a couple of weeks back by, again, PwC, PwC fers, where they were talking about, you know, a, how is it that organizations use? Ai NML. So, amongst the top things that was there was in decision support systems, predictive analytics, again, is something where there's a lot of scope for people, and organizations are increasingly looking for people. And in terms of robotics, etc, etc. So, most of these industries, if you really look at it, so college or newer in healthcare, a healthcare company, so how is it that currently, you know, you are working on what kind of projects you're working on if you can just without you know, revealing anything specific about or you know, yeah,

yeah. So see again, now, it has a it has revolutionized every industry, I worked in two different domains. So initially, I worked with oil and gas. But right now, I've been working with healthcare and especially in the side of medical imaging, there is a lot of research that's happening, where in their algorithms are able to predict the disease progression, let's say a lung disease or tumor progression with the lungs, almost as good, maybe in some, some slight percentage is better than a human being. So that that whole process of including AI would actually speed up the process in which your new trucks are Discovered autos, something which used to take like three months timeline right now, it's it's been reduced to a month or two weeks by automating the patterns that are observed in the medical imaging. So similarly, even for discovering your, your medicines for molecules that are used for making those medicines is used to suggest what is the best molecule combination that can cure a certain disease. So, yeah, a lot is happening on healthcare. I mean, there's tremendous amount of data available, because every hospital keeps collecting it. And there's a lot of research happening.

Absolutely. So at this point in time, I mean, just going through some of the comments that are coming in, somebody wants to understand how it's used in financial services, again, financial services, as a lot of use of AI beat in terms of predicting customer behavior beat in terms of being able to predict the amount of business that you are going to get built in predicting customer churn, whether a customer is going to drop off at some point in time. Some of the other very currently use cases big use cases are, again, cyber, you know, being able to predict if, if the customers are going to? Well, I think there's so many use cases, I mean, if you look at the cyber security wise, in financial services, being able to predict what are going to be costs of premiums, in financial services, like in industry, what is going to be a premium, that person is going to be depay basis, all of the data that's available, because he I can actually help you look at data, there are so many use cases, you know, that are there. So that's, that's just one, I'll just also dive into some of the questions that are coming in at this moment. So So in terms of their couple of questions, in terms of prerequisites of, you know, doing the program, so that he can What do you want to just talk a little bit about, you know, prerequisites you have not you, you were an engineer, but you did not have a programming background. So, how did you manage that?

Um, yeah, I mean, initially, I mean, I, I joined the course when I was like, around 16 years of experience. And for the last seven years, at least, like, I was not programming, I mean, I was doing engineering data management, where I was like, creating some engineering drawings, etc. But before that, I had some experience in doing c++ programming, which was not related to Python at all. But when I started learning Python, it's a very, very user friendly, programming language. That's impressed me because I took like, two years, maybe at the initial phases of my career to learn c++, but Python, the moment I started, there's so much of help available. In today's times the programming mode has completely changed, you could just start from scratch and then create a mobile app in no time. So yeah, so Python, is the whole base for data science. So I think learning Python was a cakewalk. I mean, it didn't take time at all.

Absolutely. And, and in terms of, you know, the other prerequisites, if you were to look at it now that you know, you you are somebody who's working in there, what is it that you're according to us, if somebody were to come to you should be the things that a person should have? If they want to make a career in AI ml?

See, I mean, that's a I mean, it's it's depends on this scenario, but I believe AI ml is not similar to other programming languages or other technologies, right? I mean, if you want to learn Java, then I would suggest that you need something on whereby if you want to learn SAP, then I would suggest that you need some kind of an industrial experience. But AI ml is a kind of technology, I think, which for the first time it applies to every field, I mean, every nature of work, I mean, you could think of anywhere, I mean, any field if you can apply an AI NML so that's the best part of it. I mean, you could for me, if you if you come to learn HTML, then I would say the only skill you need to have is curiosity to be able to imagine where you could apply it I think that's what drives you to learn it and then apply it i don't think so, there is any other breed besides which are required to join a course like this,

right. But but then you do require the concept of you know, some basic, I mean, you can learn it obviously, but then you do require the concept, some mathematical concepts, etc. Statistics and, you know, algebra and linear algebra and all of that. Correct. I

thought that So yeah, I mean, that's anyway started in high school. I mean, if you're looking at derivatives If you're looking at the linear algebra, which is mostly all of us would have covered in our class to which Craig said anyways, so you just have to go back and refresh your pressure skills. I mean, I don't think so that's a new topic, which which you are encountering. But yeah, I mean, you have to revisit and then kind of have a relook at derivatives.

Absolutely. So just trying to, you know, answer mahama dodging your question in terms of, you know, good foundation of AML. What are the expectations? Again, the expectations are that, you know, that's what, you know, collegian answered very, quite beautifully right now. So that's the answer to Mohammed. Audience Question. So the unconquered work experience of three in three, almost four years in quality assurance. Okay, that's not really a question. It's more of a statement. Okay. So this is an interesting question. And Prague a request culture, in particular, an automation engineer with 23 years of experience? Can he or she make subramania? So if he can he make his career in AI and ml?

See, if you actually right now go to LinkedIn right away, and then look at director, machine learning around roles like that, right. So you'll find a lot of job opportunities, because which didn't exist a few years back, but right now AML positions are being hired at director level. When you look at the job description of what they're asking for, right? I mean, so they would not want you to be somebody who could program but they would not, they would want you to be able to guide these 20 youngsters who would be developing AML applications. So so once you browse through those all job descriptions you don't like that's that's definitely something which is in demand. But the skill set that you need to build is a little different from the youngsters.

Absolutely. So again, a very basic question, which is there. What's the difference between data science AI, and then we get it in? I mean, most of all the webinars that we do, there's a question from Vishnu. As to me, okay. I probably interrogated you a little bit today.

Then I think, what's the difference between data science and AI? ml? Yeah, I think in terms of mathematics, I think AML is a subset of data science. Where in data science encompasses things like big data, and Hadoop and MapReduce and all of that, which also comes under data science, like analytics, you're taboo. So ml is a part of data science where the science is like, like, like a mother of all of it.

Absolutely. So again, yeah. So you kind of use that AI ml and and then you move into kind of deep learning. Which kind of brings me into the next question from Vidya and alluri. Are NLP and deep learning topics covered in depth in the curriculum, good enough to get the needed skills for jobs. So what's your take in terms of DD course coverage? That's there right now? Because has gone into a bit. I mean, some of it definitely has been updated since the time you did it. Because college and again, is this the first cohort participants. We are currently in the 16th cohort, which is being delivered right now. 17th is gonna start in March. So the curriculum has been changed a little bit over a period of time that since he has done it, but what was the what's your take on the coverage of the program and watch what we learned as, as a part of your curriculum? Correct. I

mean, in terms of the program, I think the main part was the algorithms, like we went, when we were like in the classrooms, we did like a three hour deep dive into every algorithm. So every class was on a separate algorithm, like we discussed SVM in one decision trees and one deal networks in one class, and then immediately followed by the labs on how to implement those, just to kind of understand from an example perspective. So yeah, it was a deep dive into algorithms. But yeah, I would have wished. If it had techniques related to deployment, then I think that would have been a very nice add for the course.

Yeah, I think we've we've kind of brought in some of those aspects. And the I think the current program, again, is, as we speak, undergoing another change whereby we are in the process of implementing additional projects over an additional period of three months, and it will be programmed the certificate again is going to become a more advanced certificate than the kind of working towards that so expect an announcement on that very soon. probably in the next couple of weeks. So we so we are going to bring in a bit of the deployment side of things as well, as we speak. And currently, and this is again, you know, in terms of a question from Vamshi. Krishna, on the sessions, is there any classroom based training? Currently, no, there aren't any classroom based trainings, you know, thanks to all of the COVID that's happening. But having said that, you know, all your sessions are live sessions, you know, they are interactive sessions, you get to see the whiteboard interact with the faculty, just like you would interact in a class, you interact with the other participants in a class both through audio as well as through chat, and video, if you want to share your video. And the platform that is used has the ability to you know, you have breakout rooms, we have, you know, mentor sessions that you can book, all of your, the, uh, you know, the practical exercises that used to happen, the labs that used to happen, they are all being moved online and all group exercises, the platform is a very robust platform that's used for this. So you do not actually miss any features. In a class, the only Yes, the difference is that you are not sitting in a class with physically sitting in a class with you know, 100 other people. The I know that this always brings in the question of how do I network? Well, you don't need to these days do you really need to meet people to network with them. I mean, we run so many of these programs with p&i kind of covered that none of the programs people have, you know, complained about the fact that they've not been able to interact with each other, you may not be able to interact physically, but you know, every program has their WhatsApp groups, their own telegram groups, etc, etc. You're also part of the alumni, townsman alumni network. So all the interaction part of it is kind of taken care of, you have to take some initiative in terms of doing the networking and the interaction part. But that's something that's a given culture. And, you know, are you still in touch with your peers? In from Cohort One?

Some of them Yes. But I recently, I mean, I chose to disconnect from all the social networks. So I wrote So right now, I don't put on a phone call. Yes, I could I have the numbers to be able to call up anytime.

Absolutely. And in terms of the interactions post, you know, be cohort getting over because this is some This is one aspect where, you know, ai ml is is there. But then a lot of people talk about the the networking side of things. So any, any, you know, now that the cohort was over? Are you aware of, you know, any of your compatriots from the program, doing something interesting, or collaborating with people, their peers after the program is was done?

Oh, yes. I

think one of one of my batch mate who did the course with me right now is handling automated vehicles for General Motors in Canada. And he's heading the team for it.

Oh, wow. Interesting. And the and in terms of, you know, if you have ever had any into, you know, as you restart, I'm sure, yeah. Have you ever reached out to any of your, you know, classmates or compatriots for any any support or any any clarification or networking in any kind?

Shall I think for a long time, I think for at least for a year after the course we were in touch. I know that. I mean, we there was a lot of discussion on what kind of openings are there in the market whose company is recruiting and then I was able to refer a few of those people into into the organizations that I I was hiring and yeah, so things like that. So it happened for quite some time. Yes.

Okay. So long she again, you know, if you come across other programs, some triple it on blockchain etc. Yes. Vamshi. We have, you know, upload program on blockchain again, one of the older programs of blockchain in India that it's almost two years old as well now more than two years old. So that's again from triple it and triple it the blockchain CO is Center of Excellence and triple it is amongst the best in the country. So yeah, if you're interested in blockchain as a program, we do have, you know, blockchain as an option available to you. And there's a question from Krishna does the course need programming background? kind of answered? Yes, you do need some programming background. This is something that we've kind of I would say discovered over a period of time that the program has been running on that, you know, if somebody's coming in without any programming background, the takeaways are and there are people who have done that over a course over the course of the cohorts that have been delivered, but what we've seen is that the takeaways from them are a little lesser than that you may be expectation is that you may not be required to do hardcore you know, programming etc as a part of the program. But then if you have no background, no concept at all, like somebody from an arts background, if he or she wants to do that, their takeaways are going to be significantly less because when somebody is you know, talking about say, a random forest, etc, etc, they are there are mathematical concepts that are involved in it, you may not be able to pick up as much as you know, somebody who has done that will be able to do and then there is there is you know, Python programming that's involved, it's easy to learn there are so many people who have done that, but having that will make it easier for you. So, if you are from an absolute non programming background, etc, we are going to ask you, you know, your selection process will probably take a little longer, and you will have to convince the selection committee as to why you want to do the program, etc. and your ability to match the classroom, the pace of the program, it's a rigorous program, and your ability to match up to that. So

feelings.

Okay, what's the minimum criteria for doing this course? Can any mechanical engineering without programming knowledge do this collegian bought? What was your engineering aid if you don't mind? mechanical or mechanical? So yeah, that that guru Raj Kulkarni, that answers your question. So, your culture and did it but 1516 years, right, of course, in during your work experience, you decided to do this.

I used to work for Shell, a proper oil and gas company as a mechanical.

Okay. Cool. So let me also talk a little bit about ask you about your decision to get enrolled for triple it. I'm sure there were some other programs I'm not not as many programs as they are currently in the market. But what made you choose the triple ID program and not some other program?

Ah, um,

I heard about people it in terms of the professor's so I think a lot of people were already kind of knowing that deployed, he was doing a lot of cutting edge work on AI, compared to even IITs. That's that's the buzzword that was going around in the hallway. So I also searched for some of the papers that replied, he writes, I mean, if you go to papers with code, and then look at most of the papers submitted in computer vision or NLP, they come from people it so i think that's that's what was one of the reasons and of course, I mean, it was nearby Have a nice day, like three kilometers away from the college. And it's a that was also one of the reasons for me to choose to provide.

Interesting, so Raghava has a question for you directly. He says that, you know, what, 16 years and no AI experience? Did you have to start start from scratch as a programmer? Or did you start at a managerial role overseeing a project? So and if we kind of, you know, juxtapose that, how does somebody with work experience, you know, compete against somebody who's probably freshly minted, professional or graduate? Yeah, correct. I think, for that I

started as a single guy, and I slowly built my team. I mean, I had 16 years of experience, but I was not doing ml. So I had to implement some of the ML components in my existing projects. That's when I built my team. So for the day, I spent a lot of time I mean, I spent a good number of hours trying to learn programming, try to run it one by one because I was not doing Python earlier. So the command line, the black window, everything was a little too new for me. But thankfully, I had a good good amount of time. So I spent ample number of hours trying to trying to master the skill. So once you master the skill, that's when you will be able to manage a lot of

people

coming because youngsters generally have a lot of questions. They just keep asking questions. So until unless you do it hands on, you will be able to not be able to guide them.

Yeah, that's a very interesting insight in you know, because All of these professionals who come in for our program, they're actually very senior professionals. Just you know, if I were to give you an example, to make you understand this, on an average, the average years of experience or any of the triple it has about talentsprint AML program is more than eight years of work x, versus, you know, relatively very young people coming in and joining the other programs that are there in the market, one of the reasons why they choose to do a program from us is the fact that, you know, the programs that we be tml program is kind of very tailored to words, working professionals, and the needs that you have. So most of the cases and I see, so many questions that are coming in over here about, you know, whether what is the advantage I'll have, I have so many years of work experience, if you have the skills, you know, if you if you are able to imbibe the skills that are required, it's, it's not going to be you're not going to be competing against somebody who is just out of college per se. So, even if you are somebody who is working in the IT ita space or in a related field, you will have certain skills which are transferable and there are certain skills, which are non transferable skills in in any role, if you the transferable skills is something that will always put you at an advantage if you have worked for more than, you know, 810, five, whatever number of years, versus somebody who's an absolute fresher. So it kind of evens it out, but most cases people want to be the questions that we get when we talk to people are, you know, what is the next job that I will get etcetera. See, every sector right now is using AI ml data science in some form or the other, what people mostly should be concentrating on is the skills that they can build, if they have the skills, if you have the skills, a good job will follow. So my only suggestion is that and you know, I bet a part of this, we, you know, we talk to 1000s of people on every year, I would you know, at any point in time, we would be talking to a few 1000s of working professionals every year, and they pass out of our programs as well. So my only suggestion request to people is to focus on building the skills part. Most of the the the programs that are AI ml is something which is happening all the time. So I mean, in terms of you know, it's opportunities, if you are able to build the skills up the job welcome. And I've kind of tried to answer a lot of to where it says that, you know, I have so many years of experience, should I do? Should I not do? etc. So again, this is a question from you, for you from a BG of what are the things that you work on 80% of the time? What are the kinds of tools that you use in in, you know, in your work life?

So, again, I mean 80% of the time, it depends on the nature of the product, or product that you're building. I mean, if you're doing an NLP you use quite a lot. And then you work with Visual Studio code for the code editing and then if required, then for deployment, you use Docker. If your project has cloud space, then you work on AWS. So it depends really on on what project you are actually. But the answer the prime skills, again, if you're on Azure, there's a different way of doing machine learning on Azure. So pretty much me once you get started in this journey, I mean learning the other tools, learning even cloud enrollments, how they're doing will become very obvious. I mean, even the interface is completely new. I mean, you did you become a fast learner for with any new technology that's being used?

Absolutely. So this this question again, maybe Unitarian you would probably have some I'll take a crack at it. But how is he I'm an ml applied an offshore structure and in the shipping industry.

So again, I'm only even for drilling of the oil I'm trying to predict where the potential for drilling of oil, there is AML that is being used and in enter offshore structures, the maintenance of the equipment becomes very critical, when you need to be able to predict the downtime of equipment beforehand. And in cases like wind turbines and offshore structures which are used in the middle of the sea, the direction in which the turbine has to be shifted based on other parameters of the wind. So that is also available. Other projects like that are going on, mainly on scalla about all the instrumentation that is being used. There's a tremendous amount of IoT data that is being generated in oil and gas. So there is a lot of AI ml need to process that IoT data, etc.

Absolutely. In terms of, there's a question on capstone projects, what was the project that you had worked on culture and as a part of your AML program?

Um,

I think there was this project about automated vehicles, I think they had this small little tiny robots. And we had to develop a program training on recognizing the road signs and then turning left and right. And things like that. So then, after development, they faded the program into the chip of the device. And it was able to actually drive itself to the end of the, the simulated road.

Oh, interesting. So yeah, that's, that's, that's, that's one of the projects now we have, you know, chat bots, and all of that. So in terms of capstone projects, I, the question kind of went off, but then whoever asked it, yes, you do have capstone projects as a part of the curriculum. And they cover a wide, you know, number of topics, or think broad areas, like, you know, unlocking a camera, phone unlocking, etc. And just giving examples, I'm sure, there are a lot more speech based ideas, you know, driverless cars, computer vision, using computer vision, etc, etc. So and you have any, if you have some problem that, you know, you can bring in data for identify that from your own organization. And, and, you know, you want to get help in solving that. That's also something that's there, we do have mentors, you know, the faculty anyway, are top notch faculty. So that's, that's something that's always available to you. So that's okay. So let's see, let's try and answer as many questions as possible. Okay, is there any placement assistance and what is the career accelerator? Okay, so when we look at so this is one question that I would have kind of briefly touched upon that the career accelerator is his talent space way of looking at helping people get access to certain tools, which will help them in their career. So what are those opportunities that are what are these tools that are there primarily, you are a part of a very large alumni network in the sense that, you know, you are not only alumni of the triple it hydrobath talent, a talentsprint AML program. As a part of the alumni community, you get to interact with see our program, the alumni from our FinTech program, FinTech and financial blockchain program, that's an I am Calcutta program or AI in marketing program, which is again right in Calcutta program or a cybersecurity program, which is an IIT Kanpur program of ours, this is a new thing that has started, we just started this late last year, you also get access to some specific job opportunities that are there, which are posted regularly on the platform, you have, you know, we help you with building your profile up in LinkedIn, kaggle, etc, etc. as well as you know, you get to interact. And if you have any specific startup ideas, etc, etc, you get to, you know, be you get to interact with experts on that. The idea is that, again, we have placements was never a part of this program. And, you know, colleciton will attest to that there were no placements for his batch, and talentsprint as an organization, we've always believed that the skills is what led lead you to the job. So that ways we've and for most cases, like I said before, right, on an average, it's eight plus 10 plus years of experience professionals who come in and work. So from an from an experience perspective from the fact that your knowledge in the industry itself is a concern, you have a lot more bureau connections in the industry than a placement officer in say, in my company or in any other a tech company will be able to give you a job with so the request is that and we believe that you know if you build up the skills and we provide you all the tools to build up your skills, etc. The job will come your way, needed career accelerator helps do that. But then, placement is something that we overt placement is not something that is provided. So let's look at This. Okay, so Muhammad azeem? uh you know, AWS versus ashore versus GCP etc Tableau versus Power BI, etc. How do you choose? Do you go by demand? Or what the target industry needs? college are? And would you want to take a shot at it my guesses would be what the target industry needs? Yeah, I

think if you go by the statistics of the usage, then AWS stops it then goes Azure then goes GCP and Tableau versus Power BI, nobody uses Power BI, it's all tableau.

So, are the lie device classes? Again, it's a question from funny or the live classes available as a recording sessions to review later. Yes, funny the live classes are available as recorded and the they are again AI pod recordings in the sense that you know, for example, this webinar, we are talking about so many things, you can actually there is an artificial AI engine that goes through the video and creates a table of contents and the platform the learning management system that you will have access to even if you open up that entire lecture, you will know that you know one hour 20 minutes say a random forest was being busy being discussed etc. So, you can actually go through those sessions in case you missed later. Any any of these sessions are for your reference. No Apoorva Manuel the course is not free. The the the program cost is 200 to 2.25 lakhs plus GST there are scholarships that are available. We have we know the need question Vishnu who manage the admissions for the program, you know, and their numbers, they are putting it in the chat, you can reach out to them to know more about the program. So I will speed up quickly. We just have about 910 more minutes left. So Santos is a researcher working on AI ml core subject is electrical engineering. What's the opportunity in data science? data and what do you I would request you to take a crack at it.

If you know that skybell Electric recently took over a lot of companies in Hyderabad. So standard electric is going really big on

AI.

So I think Yeah, so I think that's that's a good place to apply if you're focused on electrical engineering based AI.

Okay, question from Vikram, who has 18 years of experience from QA and production support in IDR apps in it with a chemical engineering background? He asked will the program help him?

See, if you look at the there is a new technology called as AI Ops, which is related to using artificial intelligence in operation management. So I think senior people like you can actually start building a career in AI Ops, because if you have done something of product development and QA using DevOps, then the next step is to migrate to a ops that way, I mean, learning Yeah, and then integrating it into AI ops is going to be a great choice for you.

Excellent. So the let's get this question. Vinod Kumar, what's the eligibility of this course for a person in the healthcare background who has no knowledge of programming, you could do it but then there is a programming there's a program that we run on digital health and imaging with ISC which which will probably be a better fit for you, it it's not as hardcore as the AML program, but then it covers most of these concepts specifically from a healthcare sector you can look up that program it's it's a talentsprint program we run it with the Indian Institute of Science in Bangalore but yeah, with no knowledge in programming Well, I will take that you know over there if you can, you know, if you can learn it up just like college or indeed you know, it's not going to stop you but then you will still need to figure that out. So probably a better fit for you would be the digital health and imaging program. So there is this question from srini he has eight years of experience as a lecturer in mathematics 12 years experience in SAP abp. So how much time will it take to master or to get a grip on AI ml in solving problems? culture and take would you take a crack at this Master

Master ml live I don't know I mean, I even I am not master at AI ml. Maybe it's been like four years since I started. But yeah, I think you need to choose your path. I mean, whether you're gonna go the NLP way, or the computer way or the Big Data way, then that is going to help you master short time. But yeah, in data science is a huge ocean and nobody could know everything out of it.

Absolutely. Just running a poll would request people to vote on it. Okay, can you? Okay, let's look at. Okay, so I think we'll repeat question, any career graph? Because COVID would any career gap. Okay. So there's this question that Japan has, which is like a career gap would hinder the chances of getting into the fields of Katyn, see a career gap is something that most organizations, I mean, most people have some sort of career gap at some gap at some point in time. If you if you feel that that's something that's insurmountable, perhaps that's not the right outlook to look at? Yes. Again, I don't know we need to know a lot more about the the exact nature of the question and the length of your career gap, etc, etc, and what led to it. But if there are cogent reasons, and organizations will consider that, you know, if and if you have the requisite skills, again, it brings me back to my oft repeated thing that people who concentrate on building up the skills they get, you know, the opportunities do come their way. So concentrate on building the skills, if you have a career gap, you can't change that, right? If you already have it, what can you do about it, you might as well look at things to or skills to build up so that you get on with your life, instead of worrying about what career gap will do. And whether you should then do some do a program or learn something new or not, would probably not be the best decision, or the best made thought frame of thought mental frame of thought is how I would put it. Okay, so there's a question from Gk, ai ml can be used in the area of project management or not.

Project Management, I think, yeah, ai ops is is a way that you could possibly, I mean, that's much more for the DevOps and product management, but I don't know, I mean,

I probably you have project management has certain areas where data is there. So which which kind of map, you know, which involves a lot of data is there, which could be Yeah, there is I mean, like, he's, no culture is mentioning that it's there. And there are certain use cases, we can actually, if you can connect up with me, after the session, I can actually give you information on that. I remember something just not coming in the top of my mind. Can you tell about opportunities of AI ml with respect to ca D and ca technologies, CAD, etc kulturen any, any field that CAD and all? Are you aware of AI ml being used for CAD CEO, I

was actually working on cat, because cat involves drawing. And we were working on a computer vision application, which could recognize paper drawings and automatically generate AutoCAD drawings out of it. So there's a lot of

need of

computer vision on it. And there's a lot of startups who are experimenting on this technology because we got 30 year old worth drawings which need to be digitalized. Well,

that's that's an interesting thing. So we are almost I think we would have covered most of the questions that are there. You know, okay, there is a question on AI ml can help in automotive industry. There's so much that's there, you know, smart cars, and all of that all that uses computer vision. So that's this huge scope, in that, you know, in that field itself. Okay, last question. vishwanathan would you recommend this question by vishwanathan? He's asking you would you recommend this course for a senior IT manager with over 22 years experience no coding or statistical knowledge? Yeah, I

would recommend this if you're willing to learn and

yeah, I mean, see vishwanathan It's, it's, you've got to learn this. And you've been you've got to be willing to you know, open up your mind and to this program is really I'm we're undergoing a similar program. from one of our things and I I have had no experience I am ob Gong grad at the moment, but then if you ask me, yes, I it's, it's, it's it's difficult to do because you know, I'm been working around 12 years now. But if you are willing to put in the Spend the hours, spend additional hours basically, because you are going to be competing against people who already have those skills and who are going to be there. So you've got to make up for that with additional hours, and additional preparation for it. So if you are willing to spend that time and puro do it, you can, nothing stops you from actually mastering, or at least learning and picking up the skills required for this. So with this, I think we are at 7pm. I would want to stick to time on this. I thank everybody who was who has come in today, especially early children. It's been lovely meeting you, again, for one of these webinars that we do we conduct these webinars very regularly across with many of our alums from, you know, different sectors, industries, etc. If you have any questions around it, you know, you have, we know the knee, push and Vishnu is numbers, they put it on the chat window, you please reach out to them, they will be able to guide you in terms of how this program is doing. What is it that it has been able to do for more than 2500 odd alumni who have passed out of the program? culture and, you know, thank you so much for joining us today. It's been lovely having you. We look forward to hosting you on more successions, but at some times, physically if you know the Coronavirus situation, you know, subsides and you know, we are able to get to here in the office. For sure now, always happy to be here because

I totally understand people I had a similar set of questions before I was about to join. So that always kind of gives me a nostalgic feeling when I come into this sessions. And I used to look up to people in my classroom who used to come when I joined as a student, so always feel very happy to come here and help whatever I can.

Absolutely Thank you so much. Really appreciate you taking your time out. And thank you to everybody you know who participated in the session. Thank you for asking all of your questions in case we've not been able to answer anything you need more information about the AML program or any of our other programs in detail. please reach out to us on the numbers given you know in the chat and the email id. Our team will be happy to help you. Thank you everyone. Stay safe. I know most of you would have voted if anybody wants to vote. We will keep the voting on for the next couple of minutes. Thanks again. All the best

Watch the entire interview here https://www.youtube.com/watch?v=xHbRsbFvYI8

Note: This video transcript is generated by AI. Therefore, it may not be 100% accurate.