Ask Me Anything IIIT Hyderabad AIML program
Hi, zoeken Good evening. Can you hear us as you're going? You're on mute. Okay, just trying to get, you know, a token to come online. Just give us a minute. I know that many of you are messaging thing that you can hear that.
Can you hear me now?
Now we can hear you.
Sorry about that. It was a bit of a I ended up on the Google meat link. And
that was taking me all over the place. So apologies for that.
mistake, I should have verified.
So what we're going to do today, ashokan is, you know, BB had this webinar, where we do this Ask me anything session, I know you've done it many times before. And just to try and help people make sense of taking a decision of doing a program in the IML or not. So I've not kept any presentation anything, which I usually do, because if you don't use the get you to do these sessions for us. So one request I would like to do is that I would like to request you to introduce yourself, and and then we can probably start taking questions from people directly. Since it's an Ask me anything session. I hope you're okay with that.
Sure, why not?
Great. So, you know, my name is Arturo, I'm a Senior Director for admissions here at talentsprint. Again, very focused on helping professionals like all of you try and make sense of any career moves that they want to make. I've been with the organization for about a year now, more than a little more than a year now. And before this, I was with the Indian School of Business, where I used to head the admissions for the flagship program, and I have over about a decade of experience. So that's me, I'm going to be primarily, you know, letting letting them manage the entire piece today. And any questions that you know, I can help, I'll be more than happy to do that. So also going over to you and to everybody else, you you have an option of raising our hands, we will unmute you, you can ask the questions that you have to ashokan and myself, either through audio or you can send it on the chat window, both of us are able to see that we will try and answer as many questions. So over to you.
Thank you. Good evening, everybody. Sorry for the delay. Time. Hopefully 10 minutes in and around computers for too long. Dinosaur started with COBOL mainframes went to see again, Unix pascall. Plus, a whole host of languages c++, and finally settled around in Python. And I said, when I learned c++, I told myself I learned my last language, six languages already to me. Then I came across Python, I fell in love with it. I built a large system on it. And that was way back in 1996 97. So my love affair with programming languages continues. I mostly teach how to think about programming in a language agnostic way.
I also talk about how to program how to convert our problems with vacation into a program say
you are seeing a 30 year old or choking on Spain. Sorry about that. It is it's a photograph I gave for all of the f1 students because they wrote the system to detect the age from a photograph. So I gave old photograph. Yes, you can see me Give me a minute. though. I'm not in the best of locations. I'm in my village and the power just tripped a few minutes back. So you are I am stuck with natural lady. You are able to see me
See you don't confuse the guy that the guy in the photograph is also weak but we are back. So don't worry about it. I Stein my change that for now. Okay, so that is my background. I have been into coding and software development and training. Alternatively, all these years. I my old fashioned hardcore programmer when it comes to doing application development, and I'm very interested in formalism, formal systems functional programming, which naturally these days lead to a lot of machine learning. So I'm interested in that also. I teach for some of the AML programs, the early modules, the Python programming modules, the math foundation modules. All the classical all those sort of things. What else? Yes, I've been an entrepreneur set up India's first.com harben.com company, the first travel website out of India that was just outside of India and so on. But my primary love remains program, I have written more than 200,000 lines of code in six different languages. given a choice, I like to write code. And Python remains my go to language, the languages I'm currently struggling to learn, or Haskell and this stone battle that was going on for the last five years, I expect to go on for some more time. That's about who I am and where they come from. Any anything I've left out? Yeah, I am a very early employee talentsprint, employee number six, to be precise. And I came into setup, how we trained people in programming skills, that's my primary one, I also do a lot of construction design. So that's where I come from. And that's what I do. So with your permission, I'll proceed to have a bit of coffee while you ask the question.
Absolutely. So. Okay, so Neil common asks, you know, I'm from a business analyst in a product management background, do I need to acquaint myself with Python to join the program?
This program is intended to give a practitioners view of. So yes, the idea is, you are able to at least dip your toes into this. There are people who have been who came, for example, I'll tell you two of the extreme cases, I remember, while someone was the chief secretary in the government, he came in to join the program, because he wanted to, he was running an NGO, and he wanted to use machine learning algorithms to decide what type of work the NGO should do in order to be maximally effective. So obviously, you're not going to write code later. But even if you are going to manage people who are going to write code for you, it's a good idea to learn that. So he did. And by the way, he did predictably in the course, the other person is a pre sales person who I asked him, where are you wanting to do this program? And he told me very nicely, I want to have an intelligent conversation with my customers and my developers. And he ended up writing quite a bit of code. So two points, yes, you need to do more than acquaint yourself with Python. That's the first point. Second point, Python was designed to be a language in which it will be easy to learn program. So it's a very, very happy thing that Python has become the lingua franca of machine learning, because the language was first and foremost designed to be easy to teach programming. So the answer is yes. And the to the unasked question. Yes. It is very easy for someone with your similar background to learn programming by
listening to you know, you think you have been there since the inception of the program? What went into designing this program? And how is it a little different than EDF, so many programs available in the market? by the dozen, but how is this program a little different? Of You know, the programs that are there, if you could just talk a little bit about that, that would I'm sure help a lot of the people make your sense of whether you know, what is it that sets this program apart?
sometime in late 2018, triple it organized today a hands on workshop for people at the director level and about in organizations that itself person offshoot of persistent demand from these companies in Hyderabad for a session on what is this ml everybody's talking about? And how is it likely to affect us? And what should we know about it? So this program was run on a for two days. And there were 40 odd participants, I was lucky enough to be on up there. All the professors from AAA to explain different aspects. There was also a half a day of hands on session where we help people look at Python for even in today's session, half the day was the author to Python. So that gives you the hands on the approach has been from day one. The purpose is twofold. Triple it being by virtue of it very strong groups to the industry in Hyderabad is being a source of talent for certain high tech areas. Effectively these companies have been talking to prefer it and saying you're producing a few 10s of masters students, maybe around 100 masters students and students or PhD student, but again, most of them go abroad. So we need people in every area of work in what we understand because it's becoming a regular thing. It is not that programs or projects or tasks are coming, which are 100% a ml instead, regular everyday business is adding an A or ml or bs or whatever you want to call it, component. And so we need people at every level. So what can you do about it? So propriety his response was to organize a studio workshop so that both people could share a common terminology and further discussions. That two day workshop. After that replied, he talked to many of the attendees try to understand from their perspective, where they expect such techniques to be used or type of projects, what's the timeframe on so on. And as a result of this, the first version of this program was designed, which was launched in January 2009. So
yeah, but when we launched it at that point in time, I think the program has gone through certain changes, we find a lot of changes, because the
both the audience and the field have gone through certain amount of changes and forgiveness, not war hard, totally, it's probably 70 to 80% the same, the depth has been added in a few topics. And also remember, this is a field in which our research paper gets into production in less than a year. It the said the very first practical binary search algorithm took 20 years to come from the date of the original binary search paper. But today, it is quite possible to find a production system using a technique or a particular implementation of an algorithm from a paper which appeared one year back in the surgeon, so not always, not in every case, but much more often than any other field. So to that extent, as the latest developments in say, reinforcement learning, etc, have been added to the course as time went by, because we also got some feedback from the students who went back saying, Yeah, we found all of these useful, these are things we are now doing. So we reduce some of the classical techniques a little, and we added some of the later ones. And we change the amount of math the amount of programming in different pieces, because adjusting the dials rather than redesigning the car, if I would say.
Absolutely. So let's take a couple of questions that have come in. You know, this is a question from cyber hoarder who's currently working in data warehousing, or human databases with four plus years of experience, he wants to know how the program helped him in scaling up and growing up in his career, he already has hands on experience with Python.
See, without is going to happen to all the data you are blocked, and the purpose of that people want to data is being stored in order to be sliced, diced and some useful interesting decisions take the traditional mechanics mechanisms for decision making or extracting information from data is now leaning strongly to us ml techniques. So to that extent, you are coming from this end of the spectrum, you know how to store the data, you know how to ensure that data is easily retrievable. Now, adding the ML to your toolkit will help you decide or help you co design techniques for extracting useful and actionable information from this huge amount of data. That would be the way plus for you because this is a new field, right? So there is so everyone come from one area, they have an existing experience and they add other. So this would definitely be a very useful background to have, for a large class of tasks around the time of deployment, that would be very, very useful. So I would presume that your organization where whatever data that is being warehoused and stored in databases is there for a purpose and pushing that data through sophisticated ml algorithm is one of the things that is going to happen, and then how to do that and what would you do with whatever things that come out of what type of algorithms are better stupid how to use Explore potential avenues of work. All of that is, are things you will learn in this program?
Absolutely. I see a couple of people trying to raise their hands in case you want to ask a question through the audio mode. Just raise your hands once shokan answers the questions that he's been currently asked. You know, we will get to us well, and all we'll alternate between the questions coming on chat, and for people raising their hands. So this is a question from Archie who's an automation specialist in QA. How he wants to know how a program like this will help him in a QA kind of a job profile.
See all profiles. In fact, quite a few of these very senior level QA directors have come join, I asked them the same page. They said, Look, no one knows what is the way to test and validate applications which have a and ml at their heart. So we QA people need to understand what is happening inside them so that we can offer? Well, no one is going to tell us how to test the system they are building, we have to tell them how it is to be tested. That seems a very, very insightful and very powerful comment from this is a director of QA who answered me this question. So yes, this is still relatively new time for a ml center application. So the book is still being written on how to test them out to do whatever things QA people do to them. And you will be getting on the ground floor of such things. And you should be finding it exciting enough to. Absolutely.
You mentioned about the QA director, and I think it's good that if we can talk a little bit about the kind of people who tend to join us and like unlike the other programs, where you have a very young lot, you know, coming into learn and our you know, the students that are shokran teachers usually come in with a few more years of experience, we are an average have about eight plus years of experience in class, etc, which is a lovely thing to have. Because, you know, they they come in with a lot of perspectives in the industry, I don't know ashokan? What's your take on that? You're teaching
you Yeah, I happen to be one of those guys who's teaching HR people who are in the first year of college, or who have forgotten when their college books, jokes about the this program has a significant number of experience, the average, I think experience in the region of 10 years, and there is the average is probably quite misleading, because there are only a few people two or three people in every bath who have less than a year of experience. And about over 150, there'll be less than two three people well, unless seven years experience, and possibly in single digits, we have people around the year of experience. And then there is a big clump around the five year mark and another clump around the stained 12 plus room for everyone brings a different perspective to the table. And that has been one of the biggest strengths of this program for people to peer learning is really, really fabulous in this program. So yes, that has been the hallmark of this program, I should say. They should also we should also talk about one more thing, which in concert with triple it, we have done of this program from the very first cohort this anyone who has done this program this day, you know what you may or may not get an opportunity to apply immediately. So once you have completed the program, you are welcome to repeat any part of the course or the complete course we prefer that you do the complete course, anytime, any number of times, because if for example you're not upgraded for a few months, and now you start in your company, the jobs are coming in which leverage ml and you feel a little rusty, we welcome you with open arms to come earlier in the program, no additional fees, nothing but just give us an advance notice so that we can slot you in but you got to go through the whole thing. You can't say I won't do the practice and all that because that will be playing havoc with the other people's to do but the reason I'm talking about this is this is a program intended for the practicing people with a focus on practicality. We recognize some people may not have an opportunity to immediately apply. Some people may have an opportunity, but they may want to refresh once again, we are quite happy with them because this programs the sound the prayers like I said in the beginning, percolate is deep connect to the industry on a burning desire to ensure that the needs of the industry in providing a skilled populace in this territory is addressed. So That's right. You're not a customer. Once you're done the course, come again, complete load. Again, like I said, any time any number of times that tells him he thinks, okay, let me I don't see any race. And so I'm gonna take the questions one by one. This is Gary. Electricity in your mpg. How can this program helped me? Okay? I presume you could teach ml because every now every university now, MLA is so called the flavor of the week, whatever. So, there is going to be a need for people who can teach me so whether you can apply it or not. Being able to teach it itself will be useful. Oh, my video looks like a Muslim boy. Okay.
The light is fading, but that's okay. I've seen you by now.
Yeah. Okay. I like that, like it would be proud of. Okay. Okay, I have beginners knowledge in Python. What prerequisite to join the future prospector? Depends on Khushboo. What is your current role, if you're an experienced person, the first time the biggest opportunity, you should deliver edges within your own organization, your experience and expertise when married to the AML knowledge would be valuable. That would be the first and primary thing for anyone with more than five years experience. This is a good thing I'm sorry, anyways, more than 10 years experience, this is possibly the first and the most important. You feel knowledge of Python. Additional prerequisite is you should be comfortable with abstract thinking some amount of mathematics, linear algebra calculus, that's about the scope of AML or cyber security, that is a very hot research topic even as we speak. So depending on which way you look at it, lots of scope because a lot of interesting research is going on, or more scope in industry, because as yet, it is still Omri researched in 15 years of experience in Microsoft. How will the company see oh gopis. There is a lot of people from Microsoft have done this program, by the way. So I would strongly encourage you to discuss with them. That said, I think Microsoft is one of those, along with many other big companies is fairly enlightened when it comes to upskilling, rescaling people, and they have to have a strong research program. In AML. Unlike a step in every area, you are going to require people so you may need to discuss with either your manager or your HR team to figure out what would be the migration path. But of course, as a senior person, their seniority has to be leveraged first. And if you're a senior person who understand the that is how you ought to position yourself and I'm sure there will be some opportunities, a lot of opportunities. That said, there are a few people with your type of experience, not just not Microsoft, someone came from Wipro, one more person came from another big company, who don't remember with 1518 years of experience. One of them, like I said, moved into the same company with ml projects under his belt after that, another person went out and became a consultant power to startups. So the seniority is useful. And it is for you to figure out how to apply it for the task. And the best place in my personal opinion is your current company because they know exactly what is the value of your seniority. And it will be easier to configure a upward path for you within the organization. Otherwise, of course you're to look out. But you're going to look out more as a senior person who can offer insights about organizational technological path forward with an understanding of you are not going to I mean, there's no point in you competing with the fresh out of college ms student in the MS or a PhD. That wouldn't be of any interest to either of you. And I'm sure that's not your intention here. You can definitely, however, leverage your experience by drawing this particular path.
Okay. We have somebody who has raised his hand so homearama
I don't see anybody raising them. I don't know why anyway.
So am I allowed you to unmute yourself, you can ask your question.
And I want to be Yes, yes, please go ahead. So I wanted to ask, Is there any scope like in data analytics? And how do I get started?
I don't understand. Are you asking? Is there a scope for data analytics? No says how do I get started with data analytics? If I'm a complete beginner? And I want to get started, I know basic Python and all those modules, but I don't know how to get started. We all know Okay. Do you have any work experience? No, sir, I do not have work experience. If you are going to do analysis, you need a wealth of experience to leverage. So the earliest stage is going to be probably starting as some machine learning engineer, see these titles very data engineer, machine learning engineer, whatever, and build that experience in a domain, then your ability to do analytics. To start with, I would suggest you complete a program in any of these, this particular program probably is not the best gear for sure. So I would definitely recommend again, though, quite a few freshers have done it, but they are very clear why they want. If you're going to ask me how can I use it there, then you have this program is not. But for a fresher, this is not the ideal program to go forward with a career in any ml analytics or a related.
So we have another question from Praveen these days design probing, you can unmute yourself and ask your question.
It has open thank you so much for this session and sharing your experience. My name is Praveen. I'm working in IT industry over 10 years as a programmer, and now as a consultant in mainframes, and he is 400 now I'm planning to make a move in Python, AI and ml. And I'm learning over let's say six, seven months, Python and AI and ml. So, I just wanted to know how effective this ai ai and ml is being used in Indian market and what about the opportunities for experienced person like me, who are you know, going to be in new technology like AI and machine learning
every single program in a IML data science which is being sold in the market is only for experienced people okay. So, and obviously, all these experienced people are not going abroad. So, Indian market is using it it is not ca ml, data science, whatever you want to call it has become what I call substrate technology. It is no longer no one says here is a project. Okay, every project now has a ml component. And that's how it will be. So a ml is an enabling technology. There will be some components of your system which need to leverage these technologies heavily in order to be I'm fond of talking about Amazon is successful, not just because it has a wonderful yay ml recommendation system, because it has a extraordinarily powerful purchasing system, they are able to get the price best they are able to induct vendors, they have a wonderful logistics system. So, the recommendation system leverage is a but it is only one of the many pieces in a large number of pieces. And that is how typically all successful systems enterprises are using a and m as an one or two components, but very important critical components that are going to give the edge to do so that said yes, anywhere everywhere it is going to be used. So in a market, everyone is every service company all the people TCS for example is now asking their freshers. You know we do train for people who have been selected by companies like TCS in the college so they are asking people like me large companies like Wipro, Infosys TCS are expecting people to know some amount of ml when they get into the system, like programming was one of the core things people expected for their purchase. Now, some ml knowledge is becoming you are not going to see ml specialization as much as the ability to build systems which contain one or more ml Yeah, thank you. Thank
you so much.
Hello, people are asking use cases project manager with no development experience, then it is gonna be a little tricky. Because this is this is more like a engineering managers role where you can offer your project managers We haven't had I can't recall any person to build the program. Like I said there are people who are absolutely nothing to do it industry who they like the chief secretary or somebody else. But your project manager, I don't recall. I'll come back to you I can't think of something directly or see, some people are asking for use case this is if you look at medicine today, you have some that are working if you want to do automated the study of the X rays to provide preliminary diagnosis or preliminary classification into these x rays need a deeper route, these x rays mean the person doesn't have a problem. So, this sort of room is just I'm only scratching the tip, there is one that does one time or there are people who are building systems which segregates cashew coming on a conveyor belt into different categories, high quality, low quality and all that. So, all of this are using ml algorithms. And we have companies which are trying to figure out which customer buys Amazon famous the people who bought this also what is the one of the earliest examples of this, so, every single field where there is a large amount of existing data, from which I can glean new intelligence to direct my thinking, that is how the whole field is. So, to asking for a use cases like can you give me a use case for computers or wherever computers can be used with an additional requirement wherever there is a large amount of data, a lease either already being used or will be used very short. Every single field can you transition into a in any field, whatever domain you're brought experience in? One of our most successful persons from the first batch is, was a maintenance engineer in a geophysical prospecting company? So yes, he was saying, You know what, I was getting bored because everything was settled and was doing well. So I decided I will attend this program. He attended the program, he got some ideas for doing some low hanging fruit, simple ml projects in their organization. He hired a bunch of interns did a few projects. Suddenly he became the go to Man for All ml projects, Steve became pretty lost. And after a year, he moved away to another company as a CIO Yes, we actually have unlimited that person we often call to talk to the other batches also, from mechanical domain, yes.
Balance sprint projects, not really, we don't have them on tabular data. How effective in Indian market like I said, we have about Britain, this is the 17th, cohort or retro
Yes, we are recruiting for the 17 cohort 1615 just got over 16% classes
also. And we have more than 2500 students have gone to them and nearly 99% of them are working in the Indian industry. So and they all have come because there is an opportunity in the Indian market their organizations are expecting them to liberate it That is why for a fresher How do you become an ml engineer die in an organization where people pressures or be inducted into the and we'll see but a few organizations are doing that
robotic Process Automation Yeah, quite a few people from RPA backgrounds they all came because there is a there is some common ground but obviously there are two different ends of the spectrum. So, robotic Process Automation is significantly different from ml even though the ML models can be used for building such tools. So there is a relationship but robotic Process Automation is more to do with the process automation side while machine learning works more with Danny figure out the star from historical data can a figure out some patterns which allow me to take it actionable, allows me to glean or extract actionable intelligence so that they extend they are different. But yes, you have quite a few students from RPA background working RPF To have come to the program that will mean that you get any particular advantage. don't really think so unless, of course, if you use Python as part of the robotic process automation, bison, selenium or similar scripting languages, yes, that's a plus. then beyond that, I think much
answered most of the questions, I'm getting a question the last person to me directly or choking, you know, you will be able to take it. What Why should I choose? What should I do to choose between a person who's confused between doing data science and AI and ml, and he was,
look, hey, I'm a data science all relate to proximately very similar. And organizations don't help by giving confusing designations to keep. The fundamental difference is a is trying to build a system with attempt to mimic human cognitive behavior. That's it. Well, machine learning algorithms are one particularly important technique to do the same. In that sense, machine learning is a subset of data science is largely using ml algorithms. But unlike ml algorithms, which often result in direct atom, data science is more associated with a human seeing the final result. In that sense. data scientists final product is thought of as a report which a human sees and decides the next course of action. While an ml algorithm often is taking a decision based on earlier data. That's about the distinction, but 75% of the subject matter is arising. If you're in your college, this is not the program. I don't know what do you mean by this? There are not multiple brands of a ml is useful for you. But this program probably is not. Given a few more questions.
Think electrical domain, you know, Shogun kind of answered that.
As a fresh graduate, it doesn't matter which team you are from. I don't mean why I don't understand what you were just saying this program. Let me repeat, this is not a program for a fresh graduate. This is more ideally suited for someone with a significant amount of experience. Depending on the range and nature of your experience you can do, you can either go back the ability to implement the existing algorithms or direct a bunch of programmers implement these algorithms in your job and so on. But in every domain, is meeting a bar that is orthogonal to a few other tools, the embedding ml tools added features in a buttoned up way, I don't know what it means. But under the hood, you see a Python programmer playing with hyper parameters the future. I see Python programmers, modifying or improving existing ml systems, I will generalize it to not just playing with hyper parameters, working with existing ml systems and building them maintaining them improving them, like any other traditional programming system is the same. So yes, there is definitely going to be a large number of existing systems which are going to require fine tuning improving, and there is definitely going to be a requirement for not just Python programmers, Python is a very small part of the whole. For example, in the the entire program, probably you will rate less than 200 lines of code.
If you're taking a break, and you're returning, okay, this again something we have heard a few people articulate the same reason. I would think in general, the industry is only now waking up to helping people who are returning particularly women, so, you can strengthen the hands of the organization which is trying to help you return by saying I have four years experience and I am not if I do, I have upskill myself, I also understand AML I think that would be a very, very big plus in your plus column. So this you know, HR people existing people are always reluctant about people coming after a break now Anything which reduces that reluctance that concern is a big plus. And I think, any good program, depending on your area of interest, it could be blotching. If we if you have taken a deep dive program in that, and you're saying, You know what, I took a break. Now that I am returning, I am returning to the bank, I have done a deep dive program and I'm coming, that I think would be something which reduces the amount of anxiety any hiring manager might face in the uncertainty of hiring someone was taking a break. This is something I've heard both HR people articulate as well as one or two people who tried after the break, articulate. Does it make sense, Bonnie,
if you can, just to add a second, we were actually talking to a very large company just about a couple of days back where they are looking at sponsoring some of these women who want to come back from taking up after taking a break. So you know, there are some very progressive companies who are actually looking at it, maybe something will happen very soon in the future, which could, you know, which could be a part of, you know, these programs, I don't want to give up too much at the moment. There's certain discussions that are kind of going on, as we speak specifically for women who are returning after taking a career break.
And warning that said, if you have an opportunity to get back, of course, get back first. Absolutely. No company is going to say, you can't do a AML program, just know your joint, that's not going to happen, I doubt. But that said, If, as I suspect you are likely to face a little bit of resistance and reluctance and coming back, this may be a good way to lubricate. That's the long and short of my judgment on demand. All the best in your attempt to return to the field. We need people we particularly look for this field is wonky, because it doesn't, doesn't have enough. Yes.
Another question that I'm seeing over here is Judo, people want to understand the curriculum of the program a little bit more, what is covered? What's not covered? Can you throw some light on that, please?
That's, that is essentially reading a laundry list. Okay, the program the seat of Fortune units, the first unit talks about the review of some of the math and programming and the classical algorithms, because many things are built on top of these classical algorithms. And the second and we also help talk about how do you define a problem. If you look at any book, I'm fond of saying this, you look at any machine learning book to start with regression, because regression has been well understood for more than three centuries. Great names like Isaac Newton's read rich Gauss have all contributed to it. But if you look at a good classical machine learning boopie to start with as scary looking about regression and into wages, that scary looking equation, we can scare you to grow your moustache, it will sprout a tail and some arms will start growing on it. That's it. And then finally, the chapter is over another scary looking equation starts on another top. But this program is for practitioners. So we want you to understand the conceptual background and a little bit of the necessary amount of maths. But you don't just want to start with the math. So, we talked about what is this tool, what is this particular algorithm, how does it work in practice? And then proceed to explain the basis or explain the math and a bit of the other theory. So, he focused on how do you define a problem? Because somebody I kept asking different ways can you give me a use case, the point is the job of the machine learning engineer is to translate a problem in your domain information when someone is trying to say you know, what I want to identify whether this is a copy this particular essay is a copy can be really matter with it. Yes, you can. How that's your job, you have to now understand the existing natural language processing algorithm systems do ABCD type of jobs now how do I translate this problem into that? So the way to translate that this will be you know what, I will take this one text and another text and find out how similar the sorry the similarity score is more than 90% I would conclude it's a coffee. Now, this restatement of the problem is what is expected by a machine learning engineer in reality. So that is what we focus on in the early modules. Later modules. We talk about neural networks later in deep neural networks and the last last unit we talked about You're advancing this happen, no, we don't, this is built in a spiral manner each topic is visited to three times at least. So, in the first time, you will just get a flavor of it, you will get the only the most simple the general case, then all additional nuances will be added as part of the algorithm or further technique in a later session, it will be applied for a larger problem, then we will take off from their own view or development. So, the center course is built on that spiral methodology. So, to some extent, the list of topics doesn't do justice, because each topic is visited at increasing level of sophistication and detail multiple times. But if you look at the coverage, it will be the same for 80% of the coverage will be identical for 80% of the programs having a mld s in the subject line.
And, you know, as I just to, you know, talk to people over here, it's, it's about, you know, the kind of feedback that we get from the people, you will all be getting access to some of the feedback that we have recently received from cohort, you know, 15 that graduated just about a week back. And, you know, you will see that the the methodology that are spoken has been talking about is something that is very well appreciated by the participants who end up completing the program, and we have probably amongst the highest completion rates in the entire industry. And definitely, if we talk about the satisfaction scores, we follow NPS Net Promoter Score, the the NPS for this program is actually amongst probably amongst the highest in the industry, it's well above 80. And just to talk about it, you know, Tesla, Google Tesla, which which are, which Google, I mean, you would think of it that, you know, it would have very high or Apple, for example, has an NPS of somewhere in the range of 6065. Last I checked, so that base, the program is a real value add for the participants who end up graduating from it. So okay, with a thesis Oh,
hi. Hi. You said, How much are you paying for a standard student in your, in our school and city? How much is the fees? insane? What is that great job, check or say, substandard? Come on. This piece is low. Exactly. If you feel this is not valuable, then if this piece is high, I seriously think you're really think about what you can get out of this program.
If you really look at it, even from the market perspective, it's not of images, which is very high. But you do have options of, you know, interest, pmis, and all of that. So that that kind of takes care of a lot of the issues that people you know, people have in terms of, you know, putting in the money, but you should look at it as an investment in yourself. And, and the returns that you get will probably pan out over the next five, seven years. If you look at it from that perspective, you're investing in yourself, it will probably not look like that the fee is very high. Because, again, the benefit that you get out of it, should you be able to pick up the skills will be much higher than what you're going to be investing for the
program. How do we go through yet? I don't know how to interpret this. But let me try one last thing. If you pick up a Venn diagram, there will be a subset of A and BSD will have large amount of ml and something sticking outside. That means up to Yeah. Okay. Yeah.
Yeah, that's always been a very classical problem. Everybody seems to be having this issue. Yeah, no raise dance. If any raised hands any more questions people have we have almost at the end of the webinar. I'm also launching a small poll. If you guys can respond to it, that would be good. Any good books to refer to pain to Gumby has a question there is an
excellent book by Stuart dinorwic. called artificial intelligence, a modern approach fondly referred to as a me that is a very good summary of pre 2010 12. state of the art lovely summer very formal, nice book. And the biggest advantage of it is its prices in the three digits. That's the most wonderful thing. Let me see whether I can locate. Yeah, good. Is the Amazon page that we take the Amazon dot imp? Yes.
Really appreciate you taking this effort, I hope and I know you're sitting in the midst of a bar cat.
match, okay. Doesn't matter. There you go. That's the book. I wrote my day for everybody. There is also another one called this looks like because much smaller, to more modern, which is one of the reference groups the site for this program.
Okay, so thank you. Thank you. So can you know sharing?
Can I sign off? Yes, there's
so much people having you
and see whether I can find the source of the power.
Absolutely. Thank you so much. I hope you will get the power back very soon. Thank you again for coming in and spending some time with us today. Lovely having you here.
It is lovely here. Hope to see you all in the class. Thanks a lot people. All the very best in your Mo. JOHN.
Thank you so much nicer. shokan. Good night. So yes, thank you, everybody, for joining us today, I would request you guys to send us you know, any comments that you have if we couldn't answer any questions? Without any question, Vishnu, they are the program. You know, part of the program team without any is the program manager, you can reach out to her. And admissions are on for our 17th cohort, which is going to start sometime late March, early April, you can talk to below the me and the team to look at information about that site. It's currently it's an online session. It used to be a classroom session, but then we moved it online. And it's not had any feedback in terms of negative feedback. It's it's live online classes. So you can basically, you know, talk to a shokan just like you know, we have been talking on the webinar over here, you will be able to look at bt notes that he shares, everything is possible in terms of you know, group exercises, and all. Incidentally, post this, we are going to be sharing some feedback from the cohort 15 students, they were the first students who actually moved completely online, thanks to the pandemic that's there, the feedback is actually become more positive compared to what we had been receiving when it was just a classroom program. There's been other changes, also the program time has been lengthened, etc. And there's also a new variant of the program where you it's a longer program that's available and you get a more advanced certificate as a result of that. We know the knee can help you talk about and you know, make a call whether you are interested in pursuing either of the options. But it's an online program and you know, it's but feedback has been fabulous for it. I thank everybody for joining us today over here. It's been lovely having you. And we look forward to having some of you in class. Thank you so much for joining. Stay safe, all the best. Bye. Thank you.
Thank you, everyone.
Watch the entire interview here https://www.youtube.com/watch?v=FjKsDjGKbvs&feature=emb_logo