Generative AI & Agentic AI Developer Program

Añadido: 2026-05-27

[00:00:42]Hi guys, good morning.

[00:00:54]Can you see my screen?

[00:00:59]Hi yes right >> you can write. Hi Nares good morning.

[00:01:05]Hi, good morning. Morning Pendra. Good morning. Suja, good morning. Vinita, good morning. Raendran good morning.

[00:01:22]Good morning.

[00:01:27]>> Uh myself Narish from Texas, USAF.

[00:01:31]>> Hi Nar from here. Thank you. Thank you.

[00:01:35]Good evening, Narish. Good evening. How is everything in Texas?

[00:01:39]>> Uh, good evening, sir. It's going well.

[00:01:42]>> It's going well.

[00:01:44]>> Good. Good.

[00:01:45]>> I got my H1 pick this year. So, >> Oh, nice. Congratulations.

[00:01:49]>> I'm starting my vendor company by June 9.

[00:01:53]>> Oh, you are starting your own company.

[00:01:56]>> Yes, sir. Already my cousin brother has a consultancy here. It's been 20 years with my family's here. Oh, nice. I am free now. So, I have no work to do. So, I just want to build my own company now.

[00:02:11]>> Nice. Very nice. Very nice.

[00:02:13]>> I reached out actually I reached out uh Mahes for some help uh regarding my website building.

[00:02:20]>> So, might be I will connect sometime maybe this way coming week.

[00:02:24]>> Oh, nice. Nice. Mhm.

[00:02:26]>> Sir, how is the market in India sir?

[00:02:29]>> Good sir. Market is in India is good.

[00:02:32]calls for latest technologies are really really good like >> nice >> data science AIT journey uh like data engineering these technology calls are really good ML machine learning and all >> got it got it so is this a first class or second class second right >> second class but topic is not it is not relevant to yesterday topic it is a new topic called prompt engineering >> prompt engineer. So I have one small question.

[00:03:05]>> What is the difference between this uh LLMs and uh what is aentic?

[00:03:14]Will you cover this today?

[00:03:16]>> Today I don't cover both. I cover uh about the prompt engineering how it works and all if required I will cover the LM topic is anyway as per my schedule LM topics tomorrow.

[00:03:31]Okay. How many total classes? Free classes.

[00:03:35]>> Five classes.

[00:03:38]>> Okay. Okay. Okay. And one more thing. Uh let me pull my resume. One second sir. I have a small >> in real class. In real time I'll cover all.

[00:03:48]>> That's fine.

[00:03:49]>> Sure sir. Okay. Please go ahead. Yeah.

[00:03:51]Sorry for interrupting.

[00:03:52]>> No problem. No problem. Actually see yesterday we given an overview about what is AI, what is geni, what is agent, what is AI agents, what is ML. All right. I showed the few projects with a demo, what is the road map, everything we have shown.

[00:04:11]>> All right. And today as a topic to make you more understanding of everyone, I have taken the topic of prompt engineering.

[00:04:19]>> Tomorrow I'm going to take the topic of LLM.

[00:04:23]like that. So my goal is they have to decide before joining they should not think that China don't know anything just give the basic idea in the first five class I will cover the various topics so that they get can get a flavor >> got it got it nice >> so how long you've been in this industry sir like do you have some experience on this or you working recently on AI products the day KSR started. Let me so yeah your name so he's having almost you know more than a decade of experience near to 15 years okay >> and currently he's working one of the uh famous bank uh as a vice president okay for the Asian regime >> okay >> okay >> and he's the founder of this KSR institute and he's found mentor both >> so he's having a vast experience okay so right from the uh day one of the data science to today as whatever is there.

[00:05:26]So, enter Asia used to handle them.

[00:05:30]>> Okay. Uh I already joined your uh course data engineering in 2024 I guess. Yeah, 2024.

[00:05:39]Uh it really helped me a lot while finding a job here. So, uh it was very very good course. It was a long course.

[00:05:48]I think 3 months I I did 3 months. I didn't do any quizzes and something you gave the assignments was shared by Santosh I guess but I didn't uh do anything because I was busy in the marketing this vendor stuff implementation stuff getting in contact with the clients so it's uh you know right the US market is it's pretty bad in 2025 right now it's okay so your course was very very good that uh data engineering course I joined I took from KS data your uh company, you are in institute, right? Is it basically institute or company?

[00:06:26]>> We are into both. Uh see we are in a product development company even because we develop applications. Now you can see clear my interview which was our born baby newly born baby.

[00:06:39]>> Okay.

[00:06:40]>> Oh yeah we do teach uh do trainings and even we develop the products.

[00:06:46]>> So do you place candidates also in India in Bangal? assistance. We don't place the candidates anywhere but yeah we we give you the assistant till you get placed but at the same time we do have the tieups with the multiple startup companies as well as few of the MNC's also where you will get the uh uh referrals with our alumini and all these processes uh all the ways.

[00:07:08]Okay, great. Great. Okay, sir. Okay.

[00:07:11]Thank you. Thank you for your time.

[00:07:19]>> Okay. Hi Gangadi, good morning. Hi Dasaris, good morning. Hi Vishnu Sai, good morning. We'll wait. We'll start the session one minute. Uh Manohar, good morning. Parendra, good morning. Prasad, good morning. Praika, good morning.

[00:07:36]Rajita, good morning. Akila, good morning.

[00:07:38]Admay good morning Shiva good morning Sucha good morning Sarendra good morning Suryas good morning good morning good morning wena good morning venita good morning Venu good morning good morning good morning guys good morning how many are the new uh uh new new people who were not in yesterday's class how many of them are you they have joined today only they have not attended yesterday's class panindra ready okay okay okay okay only one what about >> even my myself al also I joined today I can check here >> oh okay no problem no problem um yesterday okay let me record this session oh sorry already recording sorry my bad okay hi guys Good morning everyone. In yesterday's class we were Can you see my screen right everyone?

[00:08:46]>> Yes sir it's visible.

[00:08:48]>> Yeah in yesterday's class I I discussed about the overall about the what is AI what is machine learning I have given some example and some demos on machine learning.

[00:09:06]In today's class, in today's class, I'm going to talk about one of the nice concept called prompt engineering.

[00:09:18]Prompt engineering is really really helpful.

[00:09:23]It is like for example, let me ask one simple question to everyone. If you want if you want to join in any organization across India or US I'm talking about the IT company one thing which is really required what is that what is that for everyone irrespective of the technology one thing there should be >> we need to have a profile >> if you go to if you're working anywhere in India US everything one thing you should have to have they cannot not comp anyone cannot compromise on it. I'm talking about the only IT jobs. Can anyone guess what is that? Any guess >> resume?

[00:10:10]>> Uh resume is not mandatory right even after getting the job also.

[00:10:14]>> Resume profile is helpful till you get the job. After that one >> the question is how to get into the >> No, I'm not talking I'm not talking about how to get into the job.

[00:10:26]Communication skills.

[00:10:28]>> Communication skills. Simple to say more way better way simplified more >> technical.

[00:10:36]>> Qualification.

[00:10:37]>> Forget about the qualification all the things till you get the job.

[00:10:42]Communication they said more simplication.

[00:10:46]>> Simplify that. Simplify the only the communication. Can I say English?

[00:10:51]>> English.

[00:10:52]>> Yes.

[00:10:53]>> Yes or no? I mean I'm talking about the more simplified word. Some people said communication technical skills everything is mandatory and correct but prior to the communication and all you must have to have English language you must have to have a knowledge in English. So with if you know the English then only you can able to communicate with others right without knowing the English will you able to get a job?

[00:11:22]Will you able to get a job?

[00:11:26]>> Yes or no?

[00:11:28]Yes or no?

[00:11:29]>> No.

[00:11:30]>> Yes. No. Like the way in our daily life the way how English is useful.

[00:11:38]Similarly in AI world prompt engineering is equivalent to English language.

[00:11:48]If you are unable to give the proper prompt engineering prompt, your AI will consume more and more tokens.

[00:11:58]How many of you watch How many have seen the uh latest news in AI?

[00:12:06]How many of you seen the latest news in AI?

[00:12:10]Any idea? Anyone? What is the latest update in the AI?

[00:12:16]Any guess?

[00:12:18]Multimodel agentic models regarding Microsoft Microsoft.

[00:12:24]Exactly. Microsoft use. Yes. Correct.

[00:12:26]Correct. Go ahead, Sindra. You're correct.

[00:12:30]>> Yeah. Microsoft use more tokens. So they got a huge bill.

[00:12:35]>> Exactly. And as Facebook also used tokens that they got $950 million bill also because of use >> then why they are facing this issue because they are unable to use properly AI because they are weak I mean I'm not saying they're weak more few of the employees would have been weak in prompt engineering because of that they are getting the huge bill. So let's start with the one examples one by one. One we will see. Okay, let me ask one simple question guys. Let me ask a simple suppose I ask someone tea.

[00:13:25]Will they understand what exactly I want?

[00:13:29]If you ask your mom, mom, I want tea.

[00:13:32]Do you think mom will uh do you think mom will understand what you want exactly?

[00:13:40]And let's say you went to a hotel.

[00:13:43]I want tea. Let's say you just mentioned I want tea. Will they understand what exactly you want?

[00:13:55]Do I want tea? That means I'm asking whether they drink tea or I'm asking to make I'm asking them to make a tea.

[00:14:04]Which one? Which one is correct? Let's say you went to a hotel or let's say you want to let's say morning just very morning early morning you went outside give me one tea. What they have to think they are you're expecting or waiter may give you are the one who is preparing the tea. He can prepare a strong tea or he can add more sugar or probably would have add less sugar. He would have given in a big cup or a small cup. Could be possible, right? Could be possible. Am I right? Yes or no? Yes or no? Come on, guys.

[00:14:46]Come on. What do you think?

[00:14:47]>> Yes. Chances are more.

[00:14:50]>> Chances are more. Why? Why? Chances are more because you have not clearly given an instruction to the person who preparing a tea. Am I right?

[00:15:07]Suppose >> if I say I need now if I say make strong tea with less sugar and serve it hot in this case. What about now? What about now? Make strongly now >> less sugar and serve it hot.

[00:15:34]The instructions is very clear as the m the moment the instructions are very clear. The results will be much better.

[00:15:46]The results will be much better. So AI is like your helper.

[00:15:54]If you give unclear instructions, we will get unclear answers.

[00:16:05]If you give clear instructions, we get useful answer.

[00:16:15]It is not about the English grammar. So prompt engineering is not about the English grammar.

[00:16:23]It is all about giving clear instructions.

[00:16:29]Clear instructions.

[00:16:32]Okay. Let me ask a simple question.

[00:16:35]Which course is it? What is the course name? What is the course name guys? What is the course name?

[00:16:42]>> Data engineer.

[00:16:44]>> Prompt engineer.

[00:16:46]>> Prompt engineer. Today class name. It is a course name is a IML engineer with j and right manu.

[00:16:52]>> Yeah. Yes. Yes sir.

[00:16:54]>> So if I start explaining so dear no one knows about the what is can you keep the mic in mute man? I'm getting a lot of distance from your >> please. So if you if I talking about the explain machine learning if I ask chart GP let's see let's see okay let's see one simple prompt I'm writing I'm writing a simple prompt I'm just using the chart GPT for now going for we will use the cloud also if I use chart GPT explain uh okay let's see I don't want to use this one I have something Okay, I'm using login. I'm logging some.

[00:18:15]Okay. Otherwise, let's use don't consider my previous uh I'm just information which is available in charge deputy okay because I've used a lot many things right based on it may give okay now I'm just asking the explain machine learning let's see I'm writing the instruction. I'm writing the instruction as per this as per this explain machine learning see explain machine learning means what is machine learning means teaching a computer learn from data make decision it gives some data and what is machine learning one line it is given basic flow right maybe some given something is given Instead of that act as a so I'm writing act see I am explaining about the machine learning to the students like everyone is a student as you're learning so I'm explaining the machine learning to professional act as a trainer this is role so we are telling to how do you want so for example let me ask a simple question you are getting stomach pain where do you go do are you will you go to engineer will you go to a doctor or let's say in the doctor's area also where do you go you are getting severe stomach pain where do you go you go to hospital okay in hospital whom do you meet whom do you meet doctor right which doctor do you meet are you going to meet cardiology cardiologist are you going to make Uh are you going to meet a gastroenterologist?

[00:20:17]Are you going to meet a dentist? To whom you meet?

[00:20:22]To whom you will meet? Come on. Come on.

[00:20:25]To whom you will meet?

[00:20:27]>> Gastroenter.

[00:20:29]>> Let's say gastroenterologist. So the doctor must be an expert in a gastroenterologist. Right.

[00:20:37]The doctors must be gastron registrate all must be expert in the gast g gas gastly stomach pain and all right. Yes or no come on.

[00:20:48]>> Yes.

[00:20:49]>> Yes. Vishnu am I right?

[00:20:51]>> An am I right? Sharita am I right? Manu am I right?

[00:20:56]>> Yep.

[00:20:57]>> Yes. Right. Yes man. That because why you are meeting only particular doctor?

[00:21:06]because you are liking him because he's very nice person or because he's expert in the particular area >> expert in particular area that's why >> expert in the particular that means you are that means his role his role as a guest here also so I'm giving the first one act as a AML trainer because if he's a trainer then only can able to explain you about the AML or machine learning right so and then giving the context I'm giving the context what is the context explain machine learning to be right using a children child m learning mango example child learning apple example Netflix recommendations. I'm just giving the context or examples.

[00:22:12]I'll explain the framework also guys.

[00:22:14]This is how we need to write recommendations and uh sorry see and uh bank loan example I'm just giving the how you want to take an example what example you need to take keep it so the it should be simple keep it simple keep it simple and give and give A short summary.

[00:22:48]See by looking into this context. Can someone read? Can someone read?

[00:22:56]Can someone read?

[00:22:59]Can someone read? Please, please, can someone read? Come on guys. What I have written?

[00:23:05]>> Act as a IML trainer. Explain machine learning to uh beginners using a child learning Apple example, Netflix recommendation and bank loan example.

[00:23:18]>> Okay. So now if you look into here, so you want to learn the machine learning or what is our goal? Goal is need to learn the machine learning. Who will teach you the machine learning? The expert in the machine learning can teach. So as expert means is a trainer can teach. So I'm working I'm asking chart GPT act as a AML trainer that is the role that is the role act as a AML trainer that is the role explain machine learning to beginners using child learning uh child learning. So, so in order to make the machine learning to understand explained with the chain learning, Apple example, Netflix recommendation, bank loan example based on these three example explain me about the machine learning and whatever the results you are giving keep it simple the output and give a short summary to make better understanding.

[00:24:26]Now which one is more good? So just execute.

[00:24:31]Execute it is thinking. Sure. As an AML trainer, I will explain you learning like this. Machine learning is teaching a computer to learn with example. Make prediction or decision. We don't write even manual rules. Right? This is an apple. Read fruits. Apple can be right.

[00:24:51]Netflix recommendation bank loan example. Simple definition is short summary. It has given now earlier what it has given if I ask you AML. So it is giving something which you don't understand some example is given right if I color red then apple right machine learning all one line why do we use machine learning it is given basic flow it is given very simple example house production is given types of machine learning we have given right and machine learning was traditional programming is given real world examples it is given best simple definition it is given now instead of that it is given what is machine learning with three different examples is given and short summary.

[00:25:35]Which is more better? Which is more better guys? Second one. Second one is more better. Why? Why? We defined it clearly what exactly we need. What exactly we need? So I hope now we are understand. So that means we need to give the clear instruction.

[00:25:57]Right? I hope everyone understand the mean. Sir, now you're talking about the example. I'm very clear about this example. Now, can you give me what? Can you talk about what is prompt engineering?

[00:26:09]What is prompt engineering? So, prompt engineering is nothing but prompt engineering means giving the right instructions.

[00:26:21]To whom we need to give the right instructions?

[00:26:24]To whom we need to give the right instructions, guys? to open a to >> open AI. Yeah.

[00:26:30]>> Yeah. Open AI to a so that the moment you give the right instruction will you able to get the right answer?

[00:26:41]>> Yes.

[00:26:42]>> 99%.

[00:26:43]>> 99%.

[00:26:45]AI is powerful. AI can do everything.

[00:26:49]But guys trust me I cannot read your mind and it respond remember I cannot read our mind it responds only I can respond I'm talking about the jennai say prompt engine is part of jennai it respond based on what we given instructions or what we ask right what we ask.

[00:27:25]Okay. So, let me say something. If you tell a crab driver only go, if you tell it, let's say you ask auto guy, let's say you're going on road, you're asking auto guy, uh, let's go. What you will ask guys? What you will ask?

[00:27:44]What you will ask next? Will you go?

[00:27:47]Let's say you are walking on a road. You stop a auto. You stepped into the auto and you ask them let's go. What will happen next? What will happen Vishnu?

[00:28:01]>> He will ask where we supposed to go.

[00:28:04]>> Yes, definitely right. You will ask where >> where he supposed to go.

[00:28:09]>> Exactly.

[00:28:11]But if you give Okay, that's true. Why you ask? Because your instructions are not clear. Instead of that, if you give a pickup or a destination and root preference, he the auto guy can help you properly, right?

[00:28:31]>> Yes.

[00:28:32]>> Okay. Let's say if you ask open chart GPD, explain Excel.

[00:28:38]Let's say the question is explain Excel, MS Excel, Microsoft Excel. It may give you general answers norm. But if you say explain Excel formulas to beginners with examples then answer become what will what is going to happen? The answer becomes is more general or more useful?

[00:29:03]More general or more useful?

[00:29:04]>> More use.

[00:29:05]>> More useful. Better can I say better instruction will give better output. Do you agree very true? Yes.

[00:29:13]>> Y >> yes. Right. Okay.

[00:29:18]Let's understand with examples. Let's understand. So now in the prompt engine let's based on the two slides. What is your understanding? What is more important? Based on the two slides guys everyone based on the last two slide. What is more important?

[00:29:37]What is more important? Writing better prompt >> instruction >> or instruction. Writing better prompt or are giving the right instructions which is more writing better >> giving right instructions to the AI itself better okay so the instructions is very very important same yeah I the results change let's say if I say explain AI if I say explain AI The answer may be too broad.

[00:30:16]But if I say explain AI to beginners using YouTube maps uh like face unlock examples like the answer becomes easy, right?

[00:30:34]Any questions? Any doubt?

[00:30:37]Any question?

[00:30:51]Okay. Any questions?

[00:30:52]>> No question sir. No question. But yeah there is a lot of questions but still we don't have we don't question on like the session. The different question comes in our mind but with a different >> okay ask questions which are related to the same >> related to the same sir but actually one thing I just want to understand if >> even we are writing a good prompt like not a good good instructions to AI >> and we get the result is it possible to integrate with any application to use the similar prompt in the next or like in a repetitive task and how is it possible Can you repeat the question? Can you repeat the question please? The question is that yeah the question is that even we are writing a right instructions >> to g right in okay you're giving the uh right instruction to open a okay >> yes and we get the right output that we required >> okay >> that output I want to use in future perspective for complete my repetitive task >> is it possible to integrate that prompt to the going forward yeah kind of things that this is again uh it is not drawback of this it is the drawback of LLMs. So that is a uh what it happens here LLM cannot remember they cannot store in the memory they cannot remember everything but if you given the summary this is what we discussed earlier this is what you given output if you given a example kind of thing then it will give the better result that is called few short prompting >> so it means AI will not uh AI will not work on our repetitive task if I'm >> it will it will work on the repetitive task but if you give the instructions >> okay instructions only >> yes okay so let me go with the slide okay can the same person give different answers depending on how we ask what do you say >> yes sure sir >> yes yes he definitely he can >> the same person give different answer depending on how we ask what do you say it it's possible sir he can the person is giving the different answer the AI to also does the same but the results the output change based on what based on the instruction weak prompt gives average output the strong prompt gives useful outward.

[00:33:38]For example, explain. Yeah. So the next example to whom explain the beginner.

[00:33:46]What is the beginner mean? Can beta graduate is a beginner. Can 10th class student can be a beginner? Can be a uh working professional can be a beginner.

[00:33:56]Right? If I would have mentioned here very clearly explain AI to 10th class student using examples like YouTube maps recommendations and face unlock.

[00:34:12]Now both prompts are asking about explain AI but the second one the strong prompt will give the much better direction. Can you tell me why?

[00:34:25]>> We have we have given uh and our instructions are well defined.

[00:34:30]>> Well, the instructions are well defined.

[00:34:33]Okay. Now, let me ask you, imagine same photographer. Let's say I have a photographer. If you simply take photo, what he does? You have photographer. The first instruction take a photo. What he does? You want to take one photo. You want to take a photo. You went to the photographer. Ask me to take photo. What kind of photo you will take?

[00:34:57]>> Just take a random pick.

[00:35:00]>> Can simple to say normal prompt, normal image, normal photo.

[00:35:04]>> Yes.

[00:35:05]But if you say take a professional uh marriage profile a marriage proposal photo I need to send to girl photo with a plain background let's say to make more professional only take a professional LinkedIn profile photo or take professional passport photo with plain background and good lighting. So I'm just giving the one instruction you I'm just writing the let's take an example to make you better understanding. Let me take the notepad.

[00:35:41]Let me take the notepad.

[00:35:44]Okay.

[00:35:46]Photographer. I'm taking example of photographer.

[00:35:50]So uh prompt one.

[00:35:54]Prompt one. Okay. Take photo. Take a photo. Okay. Take photo. Simple words.

[00:36:02]Take photos.

[00:36:05]The next prompt to prompt to take a professional let's say LinkedIn as everyone are using LinkedIn profile photo with a plain background. ground and good lighting.

[00:36:39]Now the result will the results will be the same for both the prompt. Are the results the same?

[00:36:48]Ask which prompt is better and why second >> which prompt is better.

[00:36:55]>> Okay. Why?

[00:36:57]Instructions are very clear.

[00:37:00]instructions are very clear. H let me take another example. Write about data science prompt one I'm talking about the one write about data science.

[00:37:18]Second one is about explain data science to beginners using a supermarket sales example.

[00:37:39]H now tell me which one will give the which one is giving the more better results? Which one give us better result guys? Again it's second one. Again it is the second one. The same AI different prompts different quality. So simple to say the prompt which giving the clear instructions will give you the better results. Am I right Shiva? Am I right? Sujana SRI Surya Venu. Right. Simple to say right that is about the the AI did not change only the change is the instructions has been changed. I hope everyone clear I hope everyone clear right now let me ask a simple question.

[00:38:37]Next AI tools. Now everyone are using the right AI tools are everything everywhere. Everyone are talking about the AI agent right agents and all right today where we are seeing all everywhere we are seeing the AI. Now tell me today where are we seeing AI?

[00:39:01]Today where are we are seeing? Can you tell me can we see in charg?

[00:39:09]>> Yes.

[00:39:10]>> Can we see in our phones?

[00:39:14]>> Yes. Can we see in YouTube?

[00:39:18]>> Everywhere. Everywhere AI everywhere like coding tools everywhere. Excel, Canva, Google, everywhere we are see AI is no longer only for software engineers. AI can be useful no longer only for the software engineers. It is entering every field guys everywhere like teaching, marketing, HR, sales, you ask marketing.

[00:39:50]Hey, give me one nice strategy how to attract the tier three city people. It will give one strategy content. It will it is there in the customer support. In the customer support there are the any number of support mails and everything come. So they don't know which to address all this thing. Some emails could be belong to the building, some will belong to the network issue, some belong to the account issue like based on the type of the issue we need to categorize there we are using. So prompt engineering guys in all the industries where using AI. So for them only the basic skill is required is prompt engineering. Prompt engineering, prompting is becoming a new workplace skills just like as your email writing, just like as your communication skill, just like as your Excel, prompt engineering also becoming very important in going forward. The way companies while hiring the people the way they check communication of a person along with the technical skills they will also check the your prompt engineering.

[00:41:10]Okay. Now tell me let me ask you where can you use AI in your daily work or learning? What is the answer where you are using? Where can you use AI in your daily work or or in your learning? work or learning. Can you tell me where can you use EI in your daily work or learning?

[00:41:33]Come on. Come on everyone answer it guys.

[00:41:36]>> Chopity right? Copilot anything. It is an AI tool right is AI tool. Co-pilot is a tool. Where you are using these things? Where you are using the AI? For what purpose we are using the chip? For what purpose you gem?

[00:41:56]>> Sir, most of the time actually we are not more confident about the things currently we are handling or doing.

[00:42:03]>> So we so now so nowadays I'm I'm normally using artificial intelligence tool just like claude and co-pilot to check my things the like the email or the statement I'm writing current I'm writing currently is correct or not.

[00:42:21]Once the AI respond then I select yeah this is the good one and then I respond to the stakeholder and >> that means you you are using in your work right >> yes right now let me ask a question guys be open be honest how many of you are using Germany I as a girlfriend or a boyfriend how many of you are using JI as A girlfriend or a friend or a boyfriend?

[00:42:54]Anyone?

[00:42:56]>> No sir, not like this.

[00:42:58]>> Not everyone. No one.

[00:43:00]No one guys.

[00:43:03]>> No one.

[00:43:08]>> But you mention here but you should mention here like uh like connecting with the people or like learning so we can just like do like a conversation. If normally I I face many challenges with the in my communication to I think it is the best way to we can start conversation with any to correct >> any that's what I'm about to tell that's what I'm about to tell Jim I have seen the gemini I've seen few people are using even I've used it >> gemini if you ask few questions hey Mr. Kot. Um, hey, I'm talking Kot. I want to know what my uh friend is doing. Can you tell me something about Mr. Rakkesh?

[00:43:55]Then immediately Jimmy responds, "Which Rakkesh are you talking about?

[00:44:01]I cannot see any Rakkesh in your friend list.

[00:44:05]I have any number of Rakkesh. Can you specifically tell me which Rakkesh are you talking about?" Hey Jimny, I I'm feeling bored today. Can you tell me some funny things I can so that I can get a stress relief?

[00:44:20]Then I I mean Jimmy can talk about those things. He can I mean Jim I can give you few a few prompt I mean few jokes and all like if someone want to improve your communication I would suggest talk to Jimny.

[00:44:37]It will give you the it will I mean over that time you can improve your communication skills also.

[00:44:44]Am I right? You can improve your communication skills also. Am I right guys? Are you clear about this? Now let's say so you're talking about prompting and prompting. What is the definition of prompt? What do you think prompt means?

[00:44:59]Prompt is a simple instruction, message, question or command which given tool.

[00:45:10]A prompt can be small or detailed. It can be a question, task, role instructions, format instruction or complete requirement.

[00:45:27]Let's say if you're given one document summarize this paragraph explain pivot table in Excel create a LinkedIn post in simple English act as a interview coach ask me 10 different questions prompt is like simple to say prompt is like ordering food in a restaurant ordering food in a restaurant if order is clear you will get the right food. If your order is unclear, you may not get what you expected. Okay, let me tell you one simple example.

[00:46:09]If you been to one continental restaurant or new restaurant some I mean be honest guys be honest everyone. How many of you face these kind of issues in your life? You've been to a restaurant like famous restaurant, very new, latest restaurant with the when when you look into their menu, you could not able to see any item which you never seen or which you never heard. They given some some different different names, right?

[00:46:39]What will you order? What will you order? How many of similar situation?

[00:46:46]Okay, if you ask food, what you'll order generally? Come on. What kind of food you order generally?

[00:46:53]What kind of food you order generally?

[00:46:56]Come on. Come on. I'm not asking any some rocket science.

[00:46:59]>> Normal normal local foods that we use in our daily Yeah. daily >> like biryani, chapati, roti curry, chicken curry, mutton curry, fish curry and all. Right. Arish. Arish Patel Paladi. Am I right?

[00:47:14]>> Yes sir. But if you go to some Japanese Japanese Japanese restaurant, you never been there earlier. No one knows you've been I mean along with the I mean along with the two other family members you've been there. You are the only person you have to order it.

[00:47:32]You never seen any food item there. You don't know the items which are in the menu. What will you do?

[00:47:38]What will you do?

[00:47:41]Will you able to give the right food?

[00:47:44]Will you able to order the right food?

[00:47:47]>> No.

[00:47:48]>> No sir. We take some assistant from AI nowadays.

[00:47:51]>> I mean you'll take forget about the for timing. Forget about the AI for timing.

[00:47:57]So will you able to order the right food?

[00:48:01]>> No.

[00:48:01]>> No. Why? Because you are not sure what food you need to order.

[00:48:08]Am I right? Do you agree with me everyone? Vishnu, do you agree with me?

[00:48:13]Do you agree with me?

[00:48:15]Right.

[00:48:17]What? So then what happens? You will get you will get the you may get you may not get what you expected.

[00:48:28]You may not get what you expected.

[00:48:32]Okay. For example, uh Okay. So let me say I'll tell you said write email.

[00:48:42]I'm talking about write email.

[00:48:47]Okay. What will what will happen? So so let's say if I ask the same thing to write email what what add >> very generic and context is missing.

[00:49:00]>> Very generic right? Am I right? Very generic. Example sir sure please tell me email purpose and now charge is asking please tell me email purpose and to whom write an email student about tomorrow machine learning class write an email to placement offer for training proposal whose email for what is the message or topic tone do you want a professional friendly strong followup how do you want tell Right? So if I write something right a polite so that is what tone I'm talking about polite professional and polite right polite email to my manager asking for leave tomorrow due to personal work.

[00:50:02]Keep it short and professional.

[00:50:09]I'm talking about the professional is a tone.

[00:50:13]See, I have written all the three points. I have covered all the three points. Who is the email for?

[00:50:20]To whom you writing the email?

[00:50:24]To whom you writing the email?

[00:50:27]>> Manager.

[00:50:28]>> To manager.

[00:50:29]>> Manager. What is the message or topic?

[00:50:33]>> Professional work and leave.

[00:50:35]>> No, leave tomorrow.

[00:50:38]Leave for tomorrow.

[00:50:39]>> Leave for tomorrow. Due to personal work.

[00:50:41]>> Due to personal work.

[00:50:42]>> What tone you have written here? Is it a friendly?

[00:50:45]>> Polite.

[00:50:46]>> Polite.

[00:50:48]>> Polite and professional. Right.

[00:50:51]Professional tone. Right.

[00:50:52]>> Yes. Yep. Yep.

[00:50:53]>> So that means are we covering all the three points?

[00:50:57]Yes.

[00:50:59]Right. Let's see. Leave request. Dear manager, I would like request for leave tomorrow due to some personal work. I will ensure any pending task are managed before my leave. Kindly approve my leave request. Now see now is the message is clear. The output is clear. Why the output is clear? Because your input instructions are clear. That is what the meaning.

[00:51:22]Are you clear about this now?

[00:51:25]Are you clear about this now?

[00:51:27]>> Yep. Yep.

[00:51:29]Right? Are you clear about this? Right?

[00:51:31]That is what the meaning about this prompt. Right? A prompt is not a just question. It is an it is an instructions with direction I'm writing. So a prompt is not just a question.

[00:51:53]It is an instruction with direction guys.

[00:52:01]It is an it is an instruction with direction. So So now what one thing you understand while writing the prompt you need the clarity right what you are writing and all. Am I right? Yes or no?

[00:52:15]So why clarity matters?

[00:52:19]Look into this example.

[00:52:22]What happens when you give unclear instructions?

[00:52:28]What happens when we give unclear instruction to people?

[00:52:35]What happened?

[00:52:40]When you told something to your friends and family members which is not clear, what is going to happen?

[00:52:47]>> Results may ended with something else.

[00:52:49]You may you may get confusion mistakes you may do delay wrong output your manager has something to do you are not clear what to do what will happen what is going to happen what is going to happen definitely the results may go wrong the same thing happens with I the same thing whatever we discuss same thing is going to happen with I yeah AI doesn't know our background unless we explain it.

[00:53:27]AI doesn't know our background unless we explain it. AI cannot know who is our audience, what level I'm talking about just as what tone we need to speak, what what is the purpose. So clarity, so clarity matters because AI feels missing information by guessing. When AI guesses, the answer may not match as per expected.

[00:53:57]Okay, there is example. If I given us something to eat, hey, give me something to eat. You went a restaurant, you ask the simple question, give me something to eat. What waiter say?

[00:54:11]What waiter says?

[00:54:15]What waiter say?

[00:54:16]>> Yeah. He ask what?

[00:54:18]>> What? Right. What does he want? Spice.

[00:54:21]Do you want spicy, sweet, veg, non veg?

[00:54:24]Do you want breakfast, lunch or dinner?

[00:54:27]As it is unclear, give me something to eat. Likely chance he may bring some noodles. He may bring some dssha. He may bring some fruits or like ice cream. Or you can bring some like paneer curry.

[00:54:40]Right? Wait can bring anything because the input is not clear. The output is also not clear. Hence it is not useful.

[00:54:48]If he says something very clearly, please give me one hot ve lunch. Let's say example I given south Indian, north Indian like this. We prefer south Indian meal and less spicy. Are I prefer north Indian less spicy or more spicy? Please give me one hot veg lunch. I prefer South Indians or let's say North Indians less spicy. Got it? Okay. Hot veg lunch.

[00:55:18]South Indian. These are the instruction.

[00:55:19]Less spicy.

[00:55:21]The waiter will give you whatever yours.

[00:55:24]Exactly. Am I right? Yes or no? That is what the meaning clarity importance. Let me ask you something. Let me give one more example to make you better understand.

[00:55:37]You went to a booking. You went a book ticket.

[00:55:42]Let's say you ask your friend book ticket. What your friend says?

[00:55:47]You all of you reach your friend or you called your friend. Hey book ticket.

[00:55:52]What your friend response? What your friend response?

[00:55:56]>> Whom and for where?

[00:55:58]>> All right. What the first question? To whom and what? That is what you ask.

[00:56:04]If I if I call you Manu, hey Manu, book ticket.

[00:56:09]What you ask? As a friend, what how do you respond? Your friend call you, hey Manu, book ticket. How do you respond?

[00:56:16]>> Definitely uh forbearer and to whom you want to >> that's what you'll ask or you'll ask what ticket >> and which ticket normally? Yeah, it is for movie or it is for train or travel.

[00:56:30]movie ticket, train ticket, flight ticket and you ask for whom, which date, what budget.

[00:56:38]But instead of that if I say book a train ticket from Hyderabad to Bangalore for tomorrow evening sleeper class.

[00:56:53]What about now?

[00:56:55]>> The result will be Dr. >> The instructions is clear. The instructions is clear.

[00:57:02]Right.

[00:57:04]Right. Let's say if you want to Okay, that's what the mean. So confused output. Confused outputs create confused output.

[00:57:19]Have you ever asked yeah something? And then asked again, no no I meant this. I meant like that. I meant like this. Have happened to anyone? I hope to manyone including myself and in the initial days.

[00:57:34]Have you ever something you have something and then asked again?

[00:57:39]No, no, no.

[00:57:41]What does happen?

[00:57:45]Okay.

[00:57:46]>> It creates confusion. Yeah.

[00:57:49]>> Yeah. It create to a also it create that means your first prompt was not clear enough enough. So the confused input means what is a confused input means?

[00:58:03]Confused input mean simple to say the prompt doesn't have enough details. It may be too short, too broad or mixed with multiple unclear task. For example, let me say so as ch make project make project. What is going to happen? I just given the instruction make project.

[00:58:33]What is going to happen?

[00:58:38]Is it confused?

[00:58:39]>> Yeah, it's confused.

[00:58:41]>> Yeah, I will confused or not.

[00:58:43]>> Yeah, definitely it's confused.

[00:58:44]>> Nar.

[00:58:45]>> Yes, sir. Yes, sir.

[00:58:46]>> Yeah, you will get confused. very confused because the instruction is not clear like what >> doesn't know what AI doesn't know project topic tool level data set audience output format right let's say make project so let's see what happens sure you start asking the question so it is given instruction to me what type of projects do you want brother please share Tell me three topic basic level output need something like because we're talking about the class right we just given the instruction other actor trainer right that is the reason so create a let's say suppose if I write something create a beginner friendly Python sales analysis let's say powerbi Okay.

[00:59:49]Sales analysis project let's say not power as a data science right panda sorry back python sales project using pandas with data set explanation code charts and final business insights.

[01:00:25]Now tell me so you need a create a beginner friendly project sales and project using pandas with data set explanation code charts and final business insights. Now tell me what is going to happen. Now tell me what is going to happen here.

[01:00:41]What is happening here? It will create proper step and with clear instruction.

[01:00:47]>> Yeah. Bel below is a beginner friendly project. The sales is upon us. This is the data set they have taken. This is the data set. The example they have taken is creating some examples. Right?

[01:00:57]Sales by product something right wise monthly sales trend right top 10 five charts right this is a short project summary right so now tell me if you given the unclear instruction you'll get the unclear output if you given the appropriate input it is giving the proper outut word. Now what you have learned? You have learned about the prayer instruction.

[01:01:36]Let's say if you ask your friend let's say simple example bring if you ask your friend you tell your friend you tell your friend bring that items from there what you What you ask? You tell your friend bring the titans from there. What you What you will say? What you will say?

[01:02:18]What you will say?

[01:02:21]>> Normally he will also ask what item and from where you want.

[01:02:25]>> Yes, exactly. You'll ask which item right from where? Am I right?

[01:02:35]>> Yep sir.

[01:02:36]>> Same with the AI also guys.

[01:02:41]Same with AI. AI also if not clear the instructions are not clear it may not give the right output.

[01:02:50]Right sir, you're telling about the right instructions and all but I don't know how to give the right instruction.

[01:02:57]Can you explain me? So you're given the instructions also but every time it doesn't work for me right the what are the instructions in my real world I want to use this the clear instruction tell me sir how to do that what to do for that guys I have created a framework which we use in the industry everyone the framework called the framework called the framework called RCT what is the framework guys RCT FE framework the what is the framework guys?

[01:03:32]R >> RCT F >> prompt framework.

[01:03:37]So what do you mean by s this is the role context task format. R means R means role. C means context.

[01:03:46]T means task. F means format. E means example role.

[01:03:55]Tell. Yeah. Who should act as? Act as a data science trainer or act as a doctor.

[01:04:04]Act as a gynecologist. Act as a superman.

[01:04:08]act as a um IAS officer, act as a chief minister. What is your role?

[01:04:18]So what for example you are working you you want to send some instruction to your subordinates. So your role as a manager right? Act as a manager I need send some rules and regulations to my team.

[01:04:38]act as a HR manager. So whatever the role you are expecting for the task that you need to define like if you get stomach pain are you going to meet arthopedist are you going to meet the orthopedic doctor are you going to make gynecologist are you going to meet the some dentist if you get stomach pain to whom you meet to whom you will meet let's say you're getting some chest pain. Are you going to meet uh some arthopedic, cardiologist or dentist? To whom you'll meet? You are getting some chest pain. To whom you'll meet?

[01:05:25]To whom you'll meet? Come on. Come on.

[01:05:28]Hello.

[01:05:30]Hello. Can you hear me?

[01:05:31]>> Yes sir, we can hear. Yeah, we can hear you.

[01:05:33]>> Cardiologist.

[01:05:35]>> You'll meet the cardiologist. So then doctor should be expert in the cardiologist right yes or no as a act as a very very important guys listen carefully this is what you this is what you need to write when you're writing chip prompt anywhere in your real world also the first must be act as a act as a expert in Python development act as a Java coding expert Act as a Java back-end developer expert.

[01:06:14]Act as a data science expert. Act as a credit risk specialist. Act as a sales expert. Act as a uh chief minister, act as a communication coach.

[01:06:33]Like this you need to specify based on your requirement. This is mandatory.

[01:06:40]This is mandatory. Right. R means role.

[01:06:45]That is what the mean. Right. Give background like explain prompt engineering students are beginner something. Tell output should come. What output? How the output should come. So you want output. Give a table examples and practice output.

[01:07:03]Okay.

[01:07:05]using daily life examples like food ordering cap when you visit a doctor we don't just say problem sir I'm getting I'm getting uh headache what you'll ask what doctor will ask do we explain symptoms to the doctor do we explain the age to the doctor do we explain food habits and do we have any medicine history do we explain sir >> yes we have We have to write that context helps the doctor similarly context helps I okay okay let me ask the question let me ask the one simple question I'll write the simple question act as a as act as an excel trainer this time we talking about trainer right trainer Explain V lookup to beginners using a sales data example.

[01:08:22]Give answer. Okay.

[01:08:31]Give the answer.

[01:08:35]in stepbystep format with one practice question.

[01:08:46]Now can you identify as per the RCT FE what is the R here? What is the role here?

[01:08:56]What is the role here?

[01:08:59]What is the role here? What is the role here guys?

[01:09:03]Excel trainer.

[01:09:05]>> Excel trainer. Very good. This is the role. Role. What is the context here?

[01:09:11]See uh what is Excel trainer is the role. Okay. What is the context here?

[01:09:16]What is the context?

[01:09:18]>> Learning V lookup for learning context is uh V look explain we look up learning V look up. Okay.

[01:09:30]Hm.

[01:09:31]Okay. R is covered. C is covered. T What is the task?

[01:09:37]Learning V lookup, right?

[01:09:41]What is the task? Learning V look up to whom? What is the task here?

[01:09:46]>> To beginner data.

[01:09:49]>> Explain to beginner.

[01:09:53]Explain to beginners using >> sales data. using sales data example.

[01:10:02]Okay, very good. Now, are you clear about the role? Are you clear about the content? Are you clear about the what format you want to explain?

[01:10:12]>> Step by step, >> step by step.

[01:10:15]>> Step by step with one example.

[01:10:19]>> Step by step. Okay. Step by step is what is he means example, right? So example does it cover the example with one practice question run.

[01:10:30]>> Yes practice.

[01:10:35]Are you clear now? Are you clear now?

[01:10:38]>> Yep sir.

[01:10:39]>> Right. This is what the RCT framework RC context task format example right example right RCT framework role content task format example now many questions any doubt Excel learning V look up. Now this simple format if you able to know if you understand all this my part you are very clear about this right right when prompt use when prompt is weak use this framework to improve it that is what I does in my daily life there's nowhere mentioned in the real world about this this is my own framework which I follow in my daily life I I hope everyone is clear about this.

[01:11:48]Let's see one real example.

[01:11:50]Let's say you're hungry. Let's say you're hungry. If you tell figurative only food, will it understand fully?

[01:12:01]Let's say you're hungry. You're too much hungry. It is 2:30 afternoon. Too much hungry. You haven't had a breakfast. You hadn't have breakfast in the morning from morning onwards you did not eat anything right you tell sigi or either sigy or gummato only food does sigi and gumato will understand it fully >> no >> no right in real life also we give role context text and format without realizing it I need a dinner for two people.

[01:12:43]Vegetarian, less spicy. Budget is 500.

[01:12:49]Suggest nearby option.

[01:12:53]This is called context and constraints.

[01:12:58]So a also need this kind of things, right?

[01:13:05]Let's say let's say planetary. So where you need to plan a trip? How many trip?

[01:13:12]Then plan a trip means it generally give the basic details generic plan may not match per as per our requirement. If you write something plan a 3-day trip to Manali for family on fourth family in fourth I mean family of four in December budget is 25,000 include stay food travel sightseeing give day wise plan in a table format then what happens now do you think will I understand yes the instructions are very here understand what exactly we need. It is a more personalized more relevant right complete plan more well in a well understand or structured table format.

[01:14:06]It is a three-day plan. What is your day? Write what is the food? What is the travel? Where you need to go to the plan for travel to check out. What is the food? What is the travel? What is the total budget? It will give you the very very clear information. Now with this plan will confidently will you travel to Manali with the within under your budget?

[01:14:31]>> Yes sir.

[01:14:32]>> Yes.

[01:14:33]>> Yes. Right. That is how the clarity brings more quality in your life.

[01:14:41]Is AI can capable of you know understanding uh the you know geographical marketing stuffs like you know for example some areas are too costly and and stuff like that.

[01:14:52]>> Yeah definitely yes it does you need to include instruction uh due to my budget and I want to stay in medium range hotels.

[01:15:04]Okay. Or you can say that I want to stay I don't have a constraint about the budget. I want to stay in luxury hotels.

[01:15:17]Right? So that is what the mean.

[01:15:21]Okay. Right.

[01:15:24]That is all about your prompt engineering. Now any questions guys? Any doubt?

[01:15:34]a question not with respect to the today's class in generic I have a question uh to become a uh you know uh gen and you know the as per course like you know >> are you we need any prerequisites things to you know uh take the course this one >> no sir actually what is going to happen let me tell you I mean explained in yesterday's class okay let me open this today's >> because nowadays in the organization they are looking more towards that you know uh multimodel agentic models and and so on. So >> so that's that's the reason we are how we are going to cover if you want to directly agents multimodel you want to implement first we have we are entire thing we have covered into four different >> okay >> right so the first one is a foundation which is starting from the SQL python ed explore data for visualization business insights and all right and then once foundation is done we'll move it to core IML machine learning deep learning NLP and Then advanced gen which is LLM gen rag aent agent the multi-step orchestration is nothing but multimodel agents and then we are building the model in the core ML we are building the model as well as advanced a building the model you need to deploy and once you deploy you need to monitor in with respect to the real world so for that we are going to cover the production so entire course being divided into four different groups are four different modules at high level foundation core ML advanced gen and production sorry production deployment production deployment so for understanding the ML algorithm back end totally it's a maths right so are you going to teach uh both descriptive and inferial stats for that or like how it would be okay >> if you're able to understand the depth of the Mac I'm ready to teach at a deep level I Man, I am a graduated in statistics.

[01:17:39]>> Oh great.

[01:17:40]>> I did my BTE from Hyderabad Jane to Hyderabad campus. I did my MBA from one of the top B schools if in operation research which is purely statistics. In my college days itself we build machine learning without using any tool like Python, SAS or any tool. We build with the formulas we build dashboards, machine learning models.

[01:18:03]If you have a ability to learn depth of mathematics and to teach any extent.

[01:18:12]>> Yes sir, we were really looking for that. So >> we'll cover that.

[01:18:16]>> I got the answer. Yeah.

[01:18:19]>> Next question please.

[01:18:22]>> And computer vision and all it comes under >> deep learning sir.

[01:18:26]>> Deep learning only. Right.

[01:18:27]>> It is a part of neural network. See in everything one side I cannot keep right.

[01:18:32]Yes. Yes. I do understand sir.

[01:18:34]>> Yeah. In the course content browser you have that next question please. Man you have a lot of questions. Laxman >> I have lot of questions sir.

[01:18:44]>> Yes go ahead please. You can ask me. I can answer it or otherwise wait sir wait let other let let other I mean I'll give option sir. Please don't mind. Let others ask small questions. One or two questions. Uh one sir then I can come to you. Any questions guys?

[01:19:03]Sib, Batanya, Tanmay, Akila, Rakkesh, Rajitta, Raika, Nares, Lakshman, John, Gopy, Krishna, Dasari, Vishnu, Ashish, Mishra, Venit, Wangatamna, Sireindra, Srojana.

[01:19:27]Okay, go ahead. other question please go ahead I can answer all the questions on there go ahead manu >> I think sir those are too clear about the courses and also they are they have a like a excellent knowledge about the genai or a IML but actually the thing is that I'm a beginner I'm working as a data analyst currently I'm using powerbi >> and uh my main goal is transition my career in the AI ML and GNAI >> okay >> so and also I have some basic knowledge of SQL not for the others. So someone is already mentioned here is there any pre requisite required for this courses and what is the duration and what is the actual fee of this course >> and if you learn all the things how the how we just like grow in market because normally everyone talking about the AI and genai.

[01:20:22]>> Okay let me go with the one by one.

[01:20:25]Okay. If you have any further questions, you can ask me. If any missed also, please let me. I can answer.

[01:20:30]>> Sure.

[01:20:30]>> First one, how do you want to go? You can get a job opportunities of ML engineer, AI engineer, AML engineers, data scientist, right? Genai engineer, right? Agentic engineer or AI experts, AI consultants, right? product managers. These are the some of the roles people are expected or people are getting after learning this concepts or learning this course.

[01:21:05]Okay. Next thing the course duration is 6 months and the course fees if you pay in one single shot the course fees is 35k.

[01:21:16]Okay. So as a prerequisite no need to learn anything come with the openment I will connect all the dots till multimodel agents or till your recommendations to the business or production deployment and monitoring from starting from SQL. So ESQL is going to have 25 21 to 23 classes which starts from basics to indepth which include the projects also after every topic I explained yesterday class also we are going to cover I mean without SQL I mean topics and all we are going to cover about the 12 different projects all right 12 different projects we are going to cover which including the agentic and agentic workflow right rag LLM powered uh computer vision uh Right. Review sentiment NLP project. Right. Healthcare machine learning deep learning project.

[01:22:08]Right. Recommendation is machine learning project. So fraud detection again it is a kind of EDIA project, ML project. Right. EDI like this. We have total 12 different projects we are going to cover in the course.

[01:22:23]Okay. Now the what we are provide. So we'll provide the course as I mentioned if you pay in one shot the course is 35K. All right. And uh we will help you to portfolio building. We have a digital portfolio. Uh we have our own AI powered interview tool which prepared by our students. Uh right almost more than 5,000 people are using it currently. U uh clear my intro.I So we will give the LMS access even if you miss any content or any core class. We will get the recorded videos after every each module or every topic. We will share the projects and assignments and respon corresponding the running notes. We will provide after every class we will create your LinkedIn profile. Nowadays most of the jobs people are getting from LinkedIn and they are checking what you have done. I have learned the code they won't ask. They are looking the project what kind of project you have done for that you require uh projects to showcase your projects and quotes. You must have to have a strong GitHub profile and uh Indian NASCAR is the IT head Indian governing IT governing body. We are certified company of NASCAR and mock interviews will help and the job we will support you till get a job by man mentoring and uh checking your profile taking one-on-one interviews and I'll guide you all these things we can help you did I miss anything manu >> no sir everything explained so if I a powerbi developer is this course is suitable for me or do I need to look for others PowerBI you can it will be okay already in the powerb it will be okay if you have a salary till 20 lakhs 15 to 20 lakh if you cross that salary and you want to grow further your power may not be sufficient you need to look for yeah I now everyone talking about the industry yeah this is the only course which can be prevailing which can help you to survive further even in powerbi also nowadays everyone using the to write the dax functions and all they're using the co-pilot Right. So for that you need to write the prompt engineering. What is happen in the background of the prompt engineering? Again you need to learn the j that means this course is really required.

[01:24:38]>> And sir I am a bcom graduate. So I think it will not create any challenges for me.

[01:24:43]>> So already you are working in the IT industry with the powerbi.

[01:24:47]>> Now no one is going to check your degree. They will check your experience rather than degree.

[01:24:54]No, I'm talking about my own prospective to to learning perspective. If no become see doesn't matter now graduation degree doesn't matter now will you able to learn or not that means we'll able to give time if you give more time how you have learned powerbi you have learned your >> executions yeah >> the same thing >> okay thanks sir thank you for clear all the doubt >> next question please in my case actually I'm working as a senior a data analyst and >> what should I call you first of all?

[01:25:31]Basapa or >> no Kencha is my name sir right that's okay Kencha okay please you can call me Kencha actually uh you know uh I'm working as a senior data analyst and I've been with the same organization since more than 11 years and my CT was very less and actually before this course actually I taken I discussed with Mahish long back and I taken the data PowerBI data analyst course because I wanted to um learn that Azure concepts and all so and same time I I discussed the same thing with him uh before taking that course actually.

[01:26:05]>> Mhm.

[01:26:05]>> If I want to uh you know really increase my CTC and what could be the option for me. I'm look I'm I'm interested in more towards data science and uh now the question is like you know should I uh but because Maisha suggested me like you know you can take a data engineer course and uh uh just to you know increase your CTC like that after that OBI course. So should I take data engineer or data science? The question comes in my mind.

[01:26:35]>> Sir in data engineering also you require >> see uh uh uh let me let me tell you one thing sir. First of all I would request you immediately as soon as possible please change your job as a personal suggestion. The reason is you are staying with the same market for more than 11 years. Your CTC is very less.

[01:27:03]>> Yes.

[01:27:03]>> Right now you are improving the CTC and if you stay continue the same for next five years also your CTC may not increase as we expect and if they start layoffing you they will identify the first person >> right and the most important thing is they're interested in AI and all. So as I told you in the last last I mean last slide also this course we are going to cover all the four things right. So you choose any course at the end of the day geni is important whether you are a power developer whether you're a data engineer jennai is important lm is important prompt engineering important without that no for example you are expert in the jennai sorry you're expert in data engineering or powerb if a resume cannot be selected or cannot be identified for an interviews without the concepts of jennai irrespective irrespective ive irrespective of any course you have chosen this is mandatory so direct ja you cannot understand for that I'm going to talk about the core ML and foundations and deployment this is mandatory course it is like your English language >> course here I noticed one thing like you know the database which you're covering is SQL but nowadays like you know most of the data it's most of the organizations they're migrated towards cloud platforms like Azure, AWS and GC >> sir that is the reason I mentioned here cloud >> cloud deployment >> so pulling the data then you are deploying the cloud means you're pull the data and all right >> aa okay that was there at the end >> see right and if you start explaining everything from day one the cloud your bill get more people could not able to get the practice the same code you write in the cloud All right.

[01:29:01]>> Yes. Once we complete this course, are you capable of you know building our own agentic models using Azure foundry and all?

[01:29:10]>> You does you can does that is my guarantee >> because I attended one of the LLM I mean like uh training which you know scheduled from the organization itself like last week uh build you know uh agentic model using Azure AI something like that. So uh there I notic they use Azure foundry and also >> see you can use anything Azure foundry sage maker as sagemaker right you can use anything right end of the day you need to know the basic concepts like the way you you can use MySQL pushql cloudsql and everything right but the basic concept will be the same way right correct that's Sir then the one month is SQL then Python then ED right?

[01:30:03]>> Yes sir.

[01:30:03]>> It will take around two month.

[01:30:05]>> Yes sir.

[01:30:05]>> Or more than two month.

[01:30:07]>> Two months will be foundation sir. One two month almost one and a half month in uh one and a half month in AML core AML 2 months in uh jennai 15 days will be production that's it.

[01:30:22]Okay got it.

[01:30:28]Next question please.

[01:30:29]>> This batch start in evening or it is morning same time. Same time same time 7 to 8 >> 7 to 8:30 right?

[01:30:35]>> Yes sir.

[01:30:36]>> Thanks >> sir. Lakshman your question. TensorFlow only tensorflow and y means sir tensorflow and pyach we discussing in this course will be covered as part of the deep learning. Laxman.

[01:30:51]>> Uh okay sir. Yeah, >> that's what I mean y and yx. What do you mean by Y and Y? I mean >> uh that that's like a real time uh uh environment.

[01:31:04]>> Maybe it is depends on organization to organization and uh I will cover both tensor and pyarch most of them are using pyarch in the real world industry. So for gen also we require pyarch. So that is the reason we'll cover the pyarch.

[01:31:28]Next please.

[01:31:32]Next thing. Next question please.

[01:31:37]If you don't have any question further question you have any PPT slide for the you know uh syllabus detail syllabus or something. Yes, we have. We have I have uh I will share you that.

[01:32:00]Let me open it.

[01:32:19]So, Jennai and all databases, SQL, all these things join >> if we if we complete this course definitely we will target ourself to get uh 27 to 30 LPA right so >> more than that sir mode.

[01:32:45]>> And you'll be the uh you know instructor throughout the this program.

[01:32:50]>> Yes sir. Yes sir.

[01:32:52]>> Okay.

[01:32:53]>> I will be the only instruction for this course.

[01:32:56]>> Okay. Thank you.

[01:32:57]>> Except Pispark.

[01:33:00]Except Pispark and PowerBI.

[01:33:03]Uh that's fine sir. PowerBI and Pisb you are going to cover in this >> PowerBI basics only 10 days. I will not be I'm not see I am not expert in PowerBI hence I cannot teach that and we'll cover as part of the understand someone asked in interview do you have any idea of PowerBI for that we'll teach the basics of PowerBI only for 10 days okay just every other topics I will take it you will be the one right and psy is not >> park is not actually part of the course as an add value added advantage.

[01:33:48]If someone interested to learn we are giving as a free classes hence whenever other batches trainer conducts that classes I'll pull you I will push you guys into that batch.

[01:33:59]>> So if we learn Python uh I think it is easy to learn pispark as well right?

[01:34:06]>> Yes.

[01:34:08]>> Okay.

[01:34:11]Okay. Yeah. Actually it is also leading you in know one of the tool that is launched by Microsoft that is a fabric.

[01:34:17]So P is playing good role there.

[01:34:21]>> Yes. Yes. That's true. That is a specific organization. So that is the reason we'll cover as extra added value I mean extra classes which is not part of the course. Those topics I I will I mean I'm expert but I'm expert in price but I don't have a time to complete I need to complete the course within time.

[01:34:36]Right.

[01:34:38]And one question comes in my mind uh if uh so actually we have a class 7 to 8:30 or 7 even >> 8:30 >> 7 to 8:30 okay >> yes plus see 1 plus - 5 minutes plus minutes will be there so >> yeah yeah that is the different thing yeah >> yeah yeah >> so I so we are a working professional uh how much hours every day we have to spend spend on this session to be like a more confident >> at least you need to spend 3 hours sir >> every day.

[01:35:12]>> Yes. The more you practice the benefit you'll get more.

[01:35:19]>> Okay. Got it. But 3 hours is completely >> you can spend 1 hour also doesn't matter but instead of getting job in 8 months you'll get the job in 12 months.

[01:35:30]>> Okay. Okay.

[01:35:32]>> How fre how soon you want to get a job that is important right?

[01:35:44]Next question please.

[01:35:47]Next question please. Ask Mishra.

[01:35:51]Okay. Thank you. Any questions today?

[01:35:55]Sinat Vinit. Thank you guys. See you tomorrow.

[01:36:04]>> Thank you sir. Is it possible to get yesterday's uh recording session?

[01:36:08]>> It is in YouTube sir. Let me share with you.

[01:36:12]>> Okay. Or if I'm the if I log into that you know >> sir >> our portal case sir I can able to get right.

[01:36:22]>> Yes. Yes you can uh >> then then it's fine sir. I'll get from there itself because anyway >> I'm working as a testing engineer background with the horse. If I get LPI, if I go into data science, uh if I get LPIA, if I get into data, it will be restart. Lakshman, I did not understand your question completely. Rakman, so you mean to say that you are getting four 4.5 years of experience, electronic background, I mean background doesn't matter already test engineer. What are you saying? You are already a eight lakh experience. I mean 8 lakh package or what do you mean say?

[01:36:56]I'm not clear with the question.

[01:36:59]Lakshma Lakshman sir hello sir yeah yeah please I'm not here with the question sorry you don't mind please yeah >> yeah yeah sure that's like I'm uh going for a career transition like I am in a testing job as of now >> huh >> so I if I move into suppose if I'm getting a package around like 6 to8 LPA so if I get started again here so I'll be restarting with a low package or how >> no no no you can show the current package you tell that already I'm working in the data science Okay. Okay. But our my company is something like we don't have any data science domain in our >> No. Who they will they will come? Which company are working?

[01:37:40]>> Uh so currently I'm working in a Tata.

[01:37:45]>> Yeah. No one go and check uh you with the help of Tata Alex. Why don't you have projects Tata Alex? You have a lot of projects.

[01:37:52]>> Okay. I do have my students who is working Tata Galaxy. My own cousin, my wife's own brother is working in Tatalaxi.

[01:38:02]>> Okay.

[01:38:02]>> I mean of course he left it now used to work his first job in Tatexi only.

[01:38:08]>> What?

[01:38:08]>> He was there for 4 years. Now he's working in Amazon US UK. Sorry UK.

[01:38:15]>> Mhm.

[01:38:17]Sir I have uh 11 years of experience working currently as an SharePoint administrator and office 65 administrator and having about 22 LPA.

[01:38:27]So will this be able to help me to give a good career switch and good package of one?

[01:38:33]>> Yes sir definitely see by this you can expect the package minimum I mean maximum 50 to 70 lakhs.

[01:38:39]>> Oh great sir so we have to put more efforts. Yes ma see but only thing I can suggest you along with the technical skills very very important nowadays to everyone you need to improve your business skills business domain >> so I will teach the business domain >> banking credit card personal loans retail telecom I'll teach you this >> this is important most of the people they never focus on this area business domain sir okay >> this you need to focus So even AI now AI can write your code.

[01:39:15]Does AI can teach you the business domain? AI can fix your code problem.

[01:39:19]Does AI can tell you about your business? No.

[01:39:24]>> That is where that is where you have to improve your skills.

[01:39:36]yesterday I mean I was I had a discussion with I mean I had a discussion with my manager at high level um he's saying that Mr. XY Z um which they cannot use my name um uh we need to cut down the uh employees by next I mean within 5 years we need to cut down the our workforce by 20%. I said why?

[01:39:58]Because they are redundant. What do you mean by remnant? They can just write the code. They can give us what is output but they don't have a knowledge business knowledge to explain us in detail. So the people in coming days after EI guys irrespect whether you join the course or not that is a different story. I would suggest not along with the technical skills please please learn business knowledge which is really really useful to all of you without that no use don't take me wrong no one tell you about this point ever think in the business aspect which is really really important whether you join here or somewhere else focus on this which is really important. How many of you agree with me this with my statements?

[01:40:52]>> So really I'm I'm also like facing the same challenges currently even because I already mentioned I'm a BCOM graduate and I learned the PowerBI from one of the institution and I >> transition my career in data analytics background but I don't have a business knowledge completely >> and I the same challenges.

[01:41:12]Hm that is what you need to learn sir that is what I'm expert I am an MBA graduate from top-notch college India one of the Indian active all right where we spend lot of time in business so that is the reason now if you see my class also I keep on giving the example with different different example today and yesterday class also >> and sir even my stakeholder all already mentioned in over the call uh so currently like not uh handling And creating a dashboard on a PowerBI. It is also need a good knowledge about the product and business together what actually we are dealing and what is the background and what is the backlog what is the next uh like um the forecasting and what is the next like what I can say >> see one thing I can suggest you whatever stakeholders said 100% correct even I also said the same AI cannot replace you AI can replace your technical skills coding and all but AI AI can never replace your thought process. AI can never solve the problem solving. So while learning going forward guys in your respect to business work try to learn challenge challenges product business. So with respect to that how to improve more efficiently by using AI that's what you need to do that's what we are going to cover in this course also.

[01:42:43]Makes sense guys.

[01:42:45]>> Yes sir. Yes. Thank you.

[01:42:47]>> Thank you. If if you will be added with this domain that will also like a very helpful for us.

[01:42:52]>> Without s without that I cannot teach the class. Even I can show you one example. So this weekend I'm taking the class. Uh I'll show you one example.

[01:43:00]This weekend I'm taking the class for another batch there. I'm teaching them EDA project. They're at the EDA. So EDA project when I created this date is yesterday only. Yesterday night.

[01:43:13]>> Yes. Yes.

[01:43:14]>> So I'm teaching the PPD. See, I'm just see what I'm teaching >> banking customer intelligence dashboard.

[01:43:25]>> Right. The corporate presentation, right? So this is the this is I mean not about the coding I'm talking about. I mean I have this is a coding right? Which customer segment create a highest profit? What loan customers right as risk control? Right? What is the financial behavior? What is all the things? Customer loan data, demographics, data model, key KPIs probably heard you're using the real world, right? Product depth drivers, profitability.

[01:43:58]>> So this has been created in uh PowerPoint presentation.

[01:44:02]>> Yes. Yes. And another thing I just want to ask uh even you use this aenai or aentici to build this dashboard. See first I will give the basic content to for example this PPT this slide I created using the jenna >> because actually my my actually my goal is that uh you know most of the organization on the higher level >> they are still using uh poweroint presentation and they have to for >> they have to >> and they and they normally looking for uh neat and clear the dashboard just like you already mentioned they normally want the business problem business solution what is the goal and also with the some dashboard kind of things they are looking for so if we have a good knowledge about the python and also like a jai prompt and good prompt writing >> so that is the reason I'm just showing the example this is the EDA project I'm taking the dashboard we are building in the python for that I'm showing the pbt what we are presenting how we present to the client how to present also showing to your client.

[01:45:14]>> Yeah, that's great.

[01:45:15]>> See there this is what that's what I'm doing. What what is your business recommendations? I'm not talking that's what I I want to mention that I'm not I'm not only talking about your technical skills we also work on your business skills that is what I'm showing an example the project right vinit any questions >> no sir thank you >> next question please if no questions let me stop here.

[01:45:52]>> Sure. Sure.