MS AI NSI - Internship - April 2025

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Summary

Join Edunet Foundation's internship program for April 2025, offering insights into Microsoft Azure, AI, and machine learning. The program guides students through various technical updates, project requirements, and essential tools for completing the internship successfully. From understanding the necessity of course completion for obtaining certificates to practical demonstrations of cloud services like Azure machine learning and GPT-4, the course ensures a comprehensive learning experience.

Highlights

Microsoft Azure services are emphasized for their role in cloud computing and AI applications. 🌥️
The internship requires completion of specific courses available on the LMS platform, pivotal for certificate eligibility. 🏆
Students learn to use Azure AI Foundry for developing AI models and automating workflows. 🤖
Hands-on experience with GPT-4 and AI tools prepares students for future tech challenges. 🕹️
Practical tasks include creating and deploying projects using Azure's cloud services. 🖥️

Key Takeaways

Attending the internship provides essential insights into Microsoft Azure and AI services for students to develop practical skills. 🚀
Course completion on the Learning Management System (LMS) is crucial for receiving internship certificates. 📜
Understanding cloud services like Azure can be applied to real-world projects, enhancing career opportunities. ☁️
Projects should focus on AI applications, reflecting real-world problem-solving and innovation. 🛠️
Successfully uploading completed projects before the deadline is critical for certification. 📅

Overview

The internship begins with a series of introductions to Microsoft Azure and its significance in AI and machine learning. Students are encouraged to finish mandatory courses on the LMS to unlock their full potential in using these technologies effectively. During the session, clarity on uploading completion certificates and pasting course links is provided for the smooth acquisition of internship certificates.

Throughout the internship, participants explore various functionalities of Azure, such as virtual machines, app services, and advanced AI features. These elements are crucial for developing robust AI applications, with practical sessions on deploying projects and leveraging cloud infrastructure for scalable solutions. Students are guided to handle real-time data, employ Azure's cognitive services, and execute efficient analytics operations.

The program culminates in a hands-on project where students apply their knowledge by creating AI-driven solutions using cloud-based tools. The focus remains on innovation and applying machine learning models to solve tangible problems. By adhering to submission guidelines and deadlines, students leverage this internship to solidify their understanding and readiness for tech-driven career paths.

Chapters

00:00 - 09:00: Introduction and General Announcements The chapter titled 'Introduction and General Announcements' begins with a greeting and a check on the audibility of the speaker. Students respond to confirm they can hear her. The speaker acknowledges their responses and prepares to commence the session after a brief wait of two minutes.
09:00 - 27:00: Course Completion Requirements and Updates The chapter titled 'Course Completion Requirements and Updates' seems to be focused on informing participants about joining a session. The mention of 'Peace' may imply a session focused on mindfulness or a peaceful environment, though the context is limited. It revolves around ensuring everyone is aware of the necessary steps or updates related to completing the course, possibly by attending a mandatory session.
27:00 - 47:00: Interactive Session with Technical Trainer The chapter begins with a greeting from the technical trainer to the students as they prepare for an interactive session. The trainer acknowledges the messages from students and indicates that the session will begin shortly, as they are waiting for a couple of minutes for everyone to join.
47:00 - 59:30: Introduction to Microsoft Azure The introduction chapter sets the stage for a series of discussions, emphasizing the importance of participation and completion of advanced courses related to Microsoft Azure. It encourages participants to invite more peers to join and highlights that the completion of these courses is mandatory. The chapter ends with a brief pause, suggesting a wait for more participants to join the session.
59:30 - 92:00: Features of Microsoft Azure The chapter titled 'Features of Microsoft Azure' begins with a session introduction.
92:00 - 114:00: Demonstration of Azure AI and Project Creation In this chapter, the speaker welcomes the audience, indicating the beginning of a demonstration or presentation about Azure AI and project creation. It sets the stage for discussing the capabilities and applications of Azure AI, likely followed by an explanation or demonstration of creating a project using the platform. The tone is formal and technical, directed towards an audience with interest or involvement in AI technologies.
114:00 - 144:00: Practical Steps to Creating Azure AI Projects Welcome and Introduction: The chapter starts with a welcome message, setting the tone for the practical steps to be discussed for creating Azure AI projects.
144:00 - 190:00: Project Submission Guidelines The chapter 'Project Submission Guidelines' appears to discuss important instructions related to the submission process for projects within the context of internship sessions. However, the provided transcript is incomplete, making it difficult to extract detailed guidelines or procedures mentioned in the chapter.

MS AI NSI - Internship - April 2025 Transcription

00:00 - 00:30 Good evening students. Uh I hope I'm audible to everybody. If I'm audible, you can put good evening in the chat or s in the chat please. Uh yes ma'am you're audible. Uh yes thank you sir. Thank you. Good evening. Good evening everybody. I can read your messages as well. Right. So we'll be starting the session in the next 2 minutes. Please
00:30 - 01:00 inform everyone to join in the session Peace.
01:00 - 01:30 Yeah, very good evening students. I can read your messages. We'll be starting the session in the next 2 minutes. We're waiting for
01:30 - 02:00 more participants. Maybe you can drop a reminder to your friends to join in the session as well. We hope you're all completing your courses from the LMS. Right? Completing all those mandatory code uh advanced courses is mandatory. We will discuss that. But let's wait for two more minutes before
02:00 - 02:30 we start the session.
02:30 - 03:00 Yes. Uh very good evening uh to all of
03:00 - 03:30 you. Once again I welcome you all to
03:30 - 04:00 this uh internship sessions. Right. So
04:00 - 04:30 uh to begin uh the session I would like
04:30 - 05:00 to give you few updates. Okay. These are like old updates only. Um like you have to complete all those courses available under advanced. Okay. Let me share my screen once and I'll show you so that you will get some clarity. Okay. So, uh
05:00 - 05:30 whatever courses available under advanced, okay, there are six courses. As you can see, there would be multiple modules to it. Okay. But you have to complete all these courses under advanced option. Okay? You have to complete each of them. And this bar should show you 100%. Right? Even after that some of you keep on asking about this download certificate option. Please please note that there are other eligible criterias as well for this
05:30 - 06:00 internship certificate. Right? It is not just the course. You have to complete these courses as well as you have to paste the link and still many of you are asking ma'am where to paste the link. Once you complete the course you will be able to see this view or upload achievements or credentials option. Go there. you'll be able to see this paste link option paste link right so for every post that you complete you will be able to see a link like this so this is
06:00 - 06:30 already completed so when I click on that it will take me to this page I'm clicking on complete module so once I see this achievement page there will be this link option I have to click there and it will show me this achievement option I have to click on this arrow so that the URL is copied now. Okay. Now again I have to go back here. I have to go to that selected course where I have copied the link. I have to go here and I need to paste the link here in this
06:30 - 07:00 section and click on submit. And many of you are asking ma'am I have already submitted the link but again it gives me the option to submit the link. No problem. Once you do that once you see this file uploaded successfully you can just leave it as it is. It is already showing you completed but the only thing we would want you to do is just paste the link for all the completed courses. The respective links has to be pasted for all the courses which you complete. Okay, but remember you have to
07:00 - 07:30 complete all the courses in the same way. Do not skip any course without pasting the link. Okay, so this is one update and the second update is a lot of you keep on asking about the attendance links. Even now I have seen one of the messages says ma'am I did not attend the previous session. I did not fill the attendance also but I have gone through the recording. See in those cases please check your telegram group. You don't have to go and search it anywhere. Every
07:30 - 08:00 detail we are sending it in your telegram group. Yesterday we have discussed about this platform future skills prime FSP. Okay, the same sessions recording FSP uh the you know link and everything is given in your telegram group. Please go there and check the pinned messages. Okay students. So these are two things and the second important update is or third important update is in the dashboard. You all can see your
08:00 - 08:30 dashboard also right? You can refresh it and see that there is this new update. Can you see this upload project option everybody? If yes, you can send me yes. Upload project option. Yes, I can see a lot of SS on my screen. Right. Okay. If it is not there, just log out and relog in. Okay. Or just refresh your browser. Anything would work. Okay. So,
08:30 - 09:00 this is a new update which you can see in your LMS. You all know that to complete all the courses and uploading the link or pasting the link the deadline for that is 5th of May. Okay. 5th of May uh May which is like 5 days from today. Okay. For completing and pasting the link the deadline is 5th of May. Okay. And for submitting the project okay the deadline given for the project submission is 9th of
09:00 - 09:30 May. Okay. Just note it down somewhere because these are uh the two important uh timelines you have. Okay. One for the course completion and pasting the link. The deadline given is 5th of May and for the project completion or project submission is 9th of May. So here you can ask me ma'am what to do here? How to submit my project? Because you just said that we have to submit the PPT only right. So PPT as in you will be
09:30 - 10:00 submitting it as a PDF. Let me also show you how exactly it looks. Okay. So this is our dashboard or LMS we call it. Just click on this upload project which is like right below your offer letter option. Okay. Right below your offer letter option you can see this upload project option. Okay. You click there. If it is a no, Shrea is saying no. Shrata just refresh your browser. You will be able to see the upload project option. Right? Even if not now just do
10:00 - 10:30 it after the session that is okay but you will get to see it because all others are seeing it. I am having it open live here. Okay. So it should work for you as well. Right now once you click on this upload project option you'll be able to see these many questions. Okay. Some of them might ask you to rate your experience and some questions you have to make it a descriptive answer. Okay. Please don't rely on any chart GPT nothing. You have to make it in your own words. You're
10:30 - 11:00 going to share your experience. How do you feel about the program? How do you describe your project in few words? Something like around that. Okay. And uh for these rating questions, the details are also given here. How useful was the training content for your learning? You can just choose uh the options here like 1 to 10. One is uh for like not good and 10 is for excellent, super good, something like that. Okay. So, description is also given here and these
11:00 - 11:30 are few questions and remember all these questions are mandatory questions. Please make it descriptive. Do not give one word answers like good, okay, we don't want that answers but instead make it more descriptive. Okay. So, this is one and if after answering all these questions, if you just come down, you will be able to see this upload project option. You all know that you have to submit your project in a you have you are going to prepare a PPT as your project right.
11:30 - 12:00 So you have to convert that PPT into PDF. Why? Because the PDF will you know convert you like it will just minimize the size of it right? So please make a PDF and uh the only acceptable format here is only PDF. Okay. So remember that convert your PPT into PDF. Clear all of you right? And your PPD can have five six slides right but please don't go beyond that otherwise
12:00 - 12:30 the size would be like so big so just keep it very minimal and just try to upload your PDF here because that is the only format acceptable here so here is where you have to upload your project and coming to this side uploading your photo okay so you're submitting your project you're submitting all your feedbacks and all this so while you're uploading your photo it Please ensure that it is your recent photograph. Okay, it should be clear. It should be a professional formal photograph. Remember
12:30 - 13:00 that. And the format for that is JPG, PNG and JPEG, right? Usual photograph format. Right? So you can submit it here just by choosing the file and once everything is done just proofread it once and then you can submit it. Okay? This is as simple as that. This is where you have to submit your project. Please inform all others as well. So this is one major update for you all. We have given you the deadline as well for the course completion and for pasting the links. 5th of May is the
13:00 - 13:30 deadline and for the project submission 9th of May is the date. Okay. 9th of May still you have nine more days. So please do work on your project. Already we have shared all those templates details and everything in your uh telegram group. So take inputs from there. refer to your telegram group, go to the pinned messages and check whatever we are sending, right? And this update is already live on all your LMS. Please do
13:30 - 14:00 go and check this out. Okay. So this option upload project is available just below your offer letter option. Still a lot of you are saying ma'am I have downloaded the offer letter but it is giving me some error and I'm trying to mark the attendance it is giving me some error. So students please understand sometimes the error happens because we are also working on the back end and a lot of you are trying to access the platform in one go sometimes you'll get the error but don't worry you will get
14:00 - 14:30 it back okay just keep trying it may just take one or two minutes of extra time but it will work okay so these are few things that we wanted to share with you all now I'm just handing over the session to the technical trainer over to you sir thank Thank you ma'am. So hi everyone. Good evening. Good evening guys. I'm just making you a co-host. Yes.
14:30 - 15:00 Yeah. Yes. I'm audible. Hope I'm audible. Right. Okay. So guys I just want to ask you one questions. So whatever the projects we done previously. So have you tried from your end which we shared the GitHub links and everything. Have you tried from your end? Okay. Okay. But we asked for some output. You couldn't send us right. Yeah. Hope it is working fine.
15:00 - 15:30 The all projects are working fine for your end that you run right. Okay. Thank you. So the previously the topic that we learn we learn about a generative AI we learn about a machine learning the types of machine learning then after that we learn about a deep learning right and on basis of that particular topic we also created some projects so now it's time for the Microsoft Azure anyone have any idea what is the
15:30 - 16:00 Microsoft Azure What is it? No idea. Okay. Someone will say yes. Okay. No idea. Okay. Uh cloud. Absolutely. It is a cloud. Okay. So tell me why we use the cloud? What is the use of cloud? Anyone? Okay. The most of the people are say key storage. It is only used for the
16:00 - 16:30 storage. It is only used for the storage. Okay. So the most of the people are saying it is used for storage security. Yeah. Right. Absolutely. Yes. Deployment. Yeah. The so many features are there. Right. So one by one I will explain you and we are also going to create some projects uh using Microsoft Azure cloud. Okay. So before that what exactly the cloud we will discuss and then we will move forward. Okay. So the first thing
16:30 - 17:00 uh what is the Microsoft Azure? So basically the Microsoft Azure is Microsoft Azure launch in 2010 mark a qual shift from the onremises data centers to cloud computing by offering businesses a global network of the data centers maintained and managed by
17:00 - 17:30 Microsoft. Azure reduce the time and expense associated with a maintaining on premises infrastructure. Okay. The since its originary launch, Azure continues to offer the extensive capabilities that go beyond the simplifying infrastructure management with comprehensive AI data and application service that work
17:30 - 18:00 together. Azure delivers a unified approach to cloud computing that unique in the industry. It's open flexible cloud platform is designed to support each company's business strategy and the stage of the AI transform transformation. Okay. So the things uh basically AI is launch Microsoft Azure basically launched in 2010 and from that it is working so many features are there. So what we do the
18:00 - 18:30 one by one basically we will discuss the features. So here I have mentioned some features. Uh so the first we can say the compute service the storage services data based services. Okay. Then AI ML the machine learning service artificial intelligence and machine learning services then analytics and big data services. Okay. These are the services basically we can use and more than that also we can use. Okay.
18:30 - 19:00 So the first service which is nothing but your compute service. So what exactly the compute services uh which service basically provide you the virtual machine right the service basically provide you the virtual machines. The virtual machine which is a scalable customizable virtual server. Okay. Have heard about the virtual machine previously? Okay. Everyone again asking about the yes so many people some people
19:00 - 19:30 say no okay those who say no don't worry I will tell you those who know it's very good okay but the most of the people are asking doubt about the already madam told you uh we also told you we also provide you the topics on basis of you can create that projects right yes that know the future crime where to get the again the same things they are asking uh the topic are already explained you about the project template guys you know into that project template uh you can at
19:30 - 20:00 the last you can add the GitHub again you are asking same questions okay so now let's focus over here so what is a virtual virtual machine okay virtual machines basically we can say which is a web based uh system web- based machine where we can perform the all task okay the the machine inside the local machine that we can simply say which is nothing but your virtual machine which runs on
20:00 - 20:30 your browsers. Okay. So into the uh Microsoft Azure we have that virtual machine as well. I will show you the service that particularly then app services the fully managed platform for the web and the API app support uh NodeJS Python and etc. Okay. So app based services means what you can deploy your projects over here and it's support to the so many languages right uh you
20:30 - 21:00 can do so many APIs from that particular cloud and you can integrate the things with your web applications and your web applications uh see whatever be service whatever be things you train on the cloud uh you can use the things from there and you can implement the things into your web applications. The second scenario we can say that whatever web applications you have which is created in any technology to that web applications what you can do you can host you can deploy on the cloud. Okay.
21:00 - 21:30 Whether it is dynamic whether it is a static website any types of the application you can deploy over here. Then again the Azure functions the serverless computing to run code on demands right. Then Azure Kubernetes service is also there which the manage the Kubernet for the container which is the one type of the container uh which is handle the life cycles of that particular thing whatever we think things you are handling over there. Then again Azure batch service is there which is a large scale and parallel high
21:30 - 22:00 performance computing is there. Okay. If we talk about the next service uh next feature basically the next feature which is nothing but your storage services. Okay. So Microsoft Azure storage service which is divided into two parts as you can see here. Okay. Access accessible via restp. Okay. And then design for the Microsoft Azure virtual machines. Okay. These two
22:00 - 22:30 things uh as you can see into the design for the Microsoft Azure virtual machine. These two things which you can access within a system okay within and this system this particular features is only for the virtual machine whatever things you are doing over there. If suppose you are deploying your particular uh applications on the cloud. So there you can use that services but that another services like secure storage, table storage and the block storage these particular services you can access into
22:30 - 23:00 the outside of that particular virtual machine means you can implement into your uh your own systems. Okay. So the first thing I just want to ask you so the last time also I told key API API the again and again this word comes in picture like API API okay have you heard about the API? What is the API? Uh someone asked me REST API. Okay, the API we simply call the application programming interface. The API uh
23:00 - 23:30 basically which is used to communicate between the two applications. Okay. The with the help of the API what we can do we can communicate between two applications and there is uh no language like limit. If suppose I have created uh one application in Python and the second application I have created in Java and I want to make communications between them. I want to do the communications between them. So in that case basically what we do we use the APIs. APIs is
23:30 - 24:00 nothing but simple URL simple link but with the help of that link your communication is get happen. Okay. So how it is happen even you heard about whenever there is a web application right web application. So that particular dynamic web application there are the three parts have heard about it dynamic web application the fullstack web application it's contain the three three parts like a front end then again we have back end and then database okay the three parts are there so have you
24:00 - 24:30 ever imagine or the you got any questions like how they communicate suppose I whatever I am searching okay and when I search then my request goes to somewhere And how I get that result? Have you ever wonder about it? How exactly it is work? Yes. V routes. Okay. Routes again. Uh said right. API. Absolutely. Absolutely.
24:30 - 25:00 And the many times see now guys the many time the things are happen. Suppose uh you are creating your back end in Java. Okay. Your back end is created in Java. And the second thing whenever you are creating your front end front end the front end is creating in JavaScript right either your back end is created in Python, PHP but your front end is created using a JavaScript it can be you can say the ReactJS, AngularJS okay using any technology but the
25:00 - 25:30 backend technology is completely different and the front end technology is completely different. So I have wonder like how they are connecting or the how they communicate with each other. Like suppose the front end is created in ReactJS, back end is created in Python even they are communicating the whatever result I want whatever the operations I want to perform that all operation performed by this applications. Okay. So how they communicate? How this system is
25:30 - 26:00 communicate based on APIs, right? The system is basically communicate based on uh APIs. APIs contain some methods. The methods are like post, get, put, patch. The some types of the uh methods over there and the each method have their uh particular task right. So based on that our particular things are getting uh communicated. Suppose you are searching
26:00 - 26:30 on the front end. Suppose whatever things you are searching what is a AI and you are getting a result means what you are sending a request right you are sending a request then from that you are getting a response and that all communication is happen with your API. So the simple thing that you have to keep in your mind what exactly the API the API is nothing but your simple it is a full form of the API is application programming interface and the work of the API to connect one or more applications. Okay or it is used to
26:30 - 27:00 communicate between the another application. It is nothing but your simple API. If you see API now the API is nothing but your simple URL which contain which contains some methods getting which is nothing but your API. So simp okay this is clear for you. Still anyone have any doubt about API? I hope it is clear to you. Yeah someone say not clear. No doubt. Okay. No doubt you
27:00 - 27:30 okay. I thought no clear. Okay. Cle clear clear getting thank you. So now see these are the features. So basically this use inside in the cloud only. Okay. And these features you can uh use outside of that particular uh virtual machines also with the help of the APIs you can communicate with that particular things. Okay. So we'll go to the next
27:30 - 28:00 features. So now next feature is like we can say the databases. So there are some different databases are here. Azure SQL database which manage the relational database with the built-in intelligence. Then Cosmos DB the globally distributed NoSQL database with the low latency. Then again we have the Azure database for MySQL posts and then manage the opensource databases. Then Azure Synapsy Analytics then over the big data and the
28:00 - 28:30 data warehouse. Okay. So these are the databases that you can use from the Azure. Okay. If you want to use you can go with a requirement whichever requirement is there you can use any of database and you can go with this. Now again if we talk about the AI and machine learning service in Azure. So Azure open AI service is there access GPT module securely. Okay. So whatever be that open GP model it is accessible successfully. Then Azure machine
28:30 - 29:00 learning uh build suppose you want to build a machine learning module you want to train it you want to deploy that particular machine learning module so you can use this Azure machine learning module uh then again cognitive services uh which is use the pre-built APIs for the vision speech languages decision making then again uh the board services is there you can build and deploy the intelligent ports as per the requirement nowaday you So
29:00 - 29:30 might you know the port is very demanding everywhere you can see the ports right the boat is nothing but the assistance assistance okay so guys I just want to ask you dear student I just want to ask you one questions so both okay what exactly the boat is and the why it is needed now my uh on the any website nowadays I can see that port the boat is nothing but your uh chart absolutely helper
29:30 - 30:00 Right. Right. assistance that we simply say right even you can see that chat port on your IRCDC websites even the many of the websites there is a chat there are the boards even you can see that board into the Microsoft Azure also this is nothing but your co-pilot you can call the copilot even uh you can see that particular things on WhatsApp Instagram everywhere you can see the assistance okay that basically why we
30:00 - 30:30 required the assistance the many time even if you are using cola if you are using uh rapido the all types of right so everywhere you can see that boards so why basically that boards we required because sometimes if suppose we are calling to the customer services right customer services might be easy you are not getting the instance solution but if you are working or you are asking a doubt to that particular board so the board will provide you the
30:30 - 31:00 instance solutions right even while ordering your products from the flip card there also you can see the port okay so like this even banking websites that's also contain the boards right the chat boards the assistance basically we call so nowadays it is an very important things and which provides a very easy and the first solution to us so that types of the boat also we can create uh the without writing a single line of code on the Microsoft Azure we can
31:00 - 31:30 create it. Okay. So again see the next services is next service is nothing but we can say the analytics and the big data service. Analytics and the big data service uh basically the Azure data factory when ETL you know and the pipeline service for the data integration that you can do over there. Then Azure data bricks, Apach parks based analytics for a IML that you can
31:30 - 32:00 do the Azure streams analytics the real time data processing that you do the power media integrations with the interactive report that you can do again you can do. So now the things what I want to do or what we can do over here we will do a practicals before doing the practicals I will just show you the how exactly uh the Microsoft Azure is look and how we can use and
32:00 - 32:30 what are the services what is the user interface is there okay to go on that particular things what I do I will click over Okay. Is my screen is visible? Can you see this? No. Okay. Okay. Uh I will again share you the screen. I'm again sharing the screen is
32:30 - 33:00 not now. Is it visible? Can you see the user interface like Azure Microsoft Azure? Yes. Yes. Okay. So this is a Azure portal. This is a cloud basically that we call. Okay. So before going to this the cloud I already told you. Okay. And the so many people say the cloud is for the storage. The so many services are there right? Okay. The one more
33:00 - 33:30 important thing that I just want to tell you the cloud is like your virtual machine. The cloud is one types of your systems. They can perform the all task that you perform into your local system. The same task you can perform on the cloud. Okay. The cloud basically contain the three parts. It is like a website but which contain the all features right which runs on the servers right which contain the three parts. The cloud contain the front end with the user
33:30 - 34:00 interface that you can see which is nothing but your front end. And after clicking on that particular buttons whatever be things are happen that things are happen by the back end which is controlled by the back end. Okay. And then again if you I want to store something and it's contain also database right. So three parts are there for that particular cloud and which provide uh the best solutions for your businesses. And the one more important things the useful things of the cloud is
34:00 - 34:30 that basically uh it is we can say key this is not free. Uh some services are free but most of the services are paid right. uh so you have to use but how exactly it is useful that I will tell you so the depends on the hours that services you are using and depends on how that particular uh cloud will charge for you if suppose you have you have created that particular service and you are
34:30 - 35:00 using for that particular house right and for that particular house only this cloud will charge for you okay the charge you for particular hours for it will just charge you the things you wish. Okay. And if you purchase any other servers, smart servers, you have to purchase, you have to pay u that particular amount for that particular time period. But here it is not like this. The whatever be things the whatever time period for that particular
35:00 - 35:30 time period you have to pay. If you are not using the things you don't need to pay the things getting so this is an simple user interface of this uh Microsoft Azure. So here you can see this is the menu button and into this menu button we have so many things over here. Okay. So the dashboard this is the dashboard if you click then all services the services if I want to explore that all services I I I can explore using this. Okay then all resources that the resources which I am going to create if
35:30 - 36:00 either I have created that resource resources that all resources we can explore. Okay. Then the same things again you can see over here right the all resources if suppose I created resources I can visit over here resource group you can see if you you created or the previously the resource groups are available you can click over here this is an simple machine uh simple machine learning service using this machine learning service you can perform you can
36:00 - 36:30 create uh automated flow for that machine learning you can create uh Jupyter notebook require that machine learning and we are going to perform practicals on this. Okay. Again this is another service which is nothing but your Azure AI founding the one of the important service and using this service also we are going to create a simple practical okay the computer vision practical that we say if suppose I want to classify that image or I want to get some insights from that particular images. So there I can use it even for
36:30 - 37:00 the uh generative AI suppose I want to build some generative AI models for this also I'm going to use this Azure uh AI fun okay then then AI Azure AI services is also there then kubernet which we already discussed about it the kubernet which is one one types of the container which handle your life cycle of that particular things suppose I'm developing suppose uh the software for case and the
37:00 - 37:30 whatever things I required I can keep into that using this Kubernet containers. Okay. Uh you can create your own virtual environment uh virtual machines over here. The virtual machine basically if suppose you want to run your another application like you have created applications using Python. If you created application using Java, JavaScript and that applications basically you want to you want to run on the cloud. Okay. So that applications uh you can do over
37:30 - 38:00 here. You can create that virtual machine that environment you can create and you can uh run your models run your application. Again if you want to uh run the things if you want to deploy your project. So to deploy that particular things what you do you can use this uh virtual machine learning service right. So this is a simple dashboard for this. So now what I want to do uh I want to uh create one projects that projects can
38:00 - 38:30 extract the informations or the can write extract the information from the image okay and what that image is containing what is in that images is okay so so that types of the project basically I want to create but before creating that projects so how I can create I just want to ask I'm just curious about this if suppose I want to create any projects okay any projects related to the object detections right
38:30 - 39:00 or I want to extract some information that from images so how I can create the projects like we seen the previously but how we can create the projects what technology and the what tools basically I need first we have to select resources okay use deep learning okay first create resources CNN okay okay there's so many people answering Right. But now see the previously we created everything using write uh writing the code right computer
39:00 - 39:30 regions absolutely the requirements that we can see again CNN you are talking about the deep learning. Okay. And raw material like data. Okay. Absolutely. Absolutely right. Okay. So basically now here we have some services. We no need to uh write a Python code like previously we written now no need to write a Python code without writing that Python code what we
39:30 - 40:00 can do we can create a okay and that your projects can show you like uh can read the captions of that particular image uh also it can detect what is it in that particular image right AI agent okay and also using this particular as I told you Okay, we can also um develop the board chatboard also we are going to create. Okay, so for this basically the first thing uh I have to create a
40:00 - 40:30 resource whenever I'm using the cloud now. So for that cloud so many services are there that we also discuss about the features right the so many features are there. So now what we want to do we want to create that project which can read the caption of that particular image right which can detect the object right so and whatever the things are there into that things I want to create that project data images yeah right data but
40:30 - 41:00 here basically what we are doing we are using that service the service name is nothing but what we say which is nothing but your Azure AI foundry. Okay, as I already explained you using Azure AI foundry, what we can do? We can create any AI related projects, right? We can create any uh generative AI related project that types of the project you can create even using this the same service what I can
41:00 - 41:30 do I can create or we can create a chat board also. Yeah. Can we make a board projects? Yeah, definitely I will also show you guys I will also show how we can create it. Okay. So the first thing what we while using the cloud the first thing that I want to do which is nothing but what we what we have to do we have to create a resource for this you can directly click over here either either what you can do you can search into the
41:30 - 42:00 search box what you can search you can just simply type Azure okay AI okay and then it is you can see into the search if suppose some services you can see into this menu bar but some services might you are not able to see over here so the service you know but you can't see over here so that time what you can do you can simply search also okay so what I did I just search here what I s Azure AI foundry I searched you can
42:00 - 42:30 simply click over here simply click on this service okay once you click so no Azure AI foundry to display means this service we haven't created Okay, the service is not created. So now what we have to do? So we have to create this service. Okay, we have to create the service. Create the service. What you can do here? You can see this button. Can you see this button guys? Okay, still so far it is clear to
42:30 - 43:00 you. Anyone have any doubt about this related to the cloud? Uh it is clear. Anyone have no sir? Okay. Okay. No doubt. Okay. Okay. Is it clear? Okay. The previously we were on the homepage that on dashboard. Okay. From dashboard we understood the so many services was there. Okay. We can see the resource groups also right. Yes it is paid. It is paid. Okay.
43:00 - 43:30 Uh the paid service I'm using. Yes. So now what you can do again? So now what what you can do guys see we came we use this particular service then what we did I search for the Azure AI foundry once I search now I directly redirected on this particular page once I redirected on this page this service haven't created if you previously create that service you can
43:30 - 44:00 directly uh redirected on that particular launch page but it is we can't see anything else so now what we want to do we can create that service to create this particular service here you can see so many buttons right so many buttons are here but what you have to do we have to click on this create all button simply we can click on this button once you click on this button so now what it is asking it is asking the collaborative organiz so now what we want to do we
44:00 - 44:30 want to create the projects right create that projects so you can see the options project you can simply click on this project. Once you click on this project guys, so now here you can see this user interface. Okay. So this user interface they are asking for the basic information. Okay. So basic information is like suppose the first thing that you want to do which is nothing but you have to create the resource group. Okay. So
44:30 - 45:00 to create resource group the you can click on create new. You can click on create new. Okay. Click on create new. Then after that you can write whatever you want to create. Okay. So you can write the name for that particular. So now I am using the AI foundry. So what I do I can simply say AI projects. Simply I have written AI
45:00 - 45:30 projects. You can write any name also. any name either you can write the computer vision projects either you can write the object detection uh detection project you can either write the image classification the information extraction anything you can write I just write AI projects okay once I write I will click on okay what I do I will simply click over here on okay once I click okay then again uh resource details I have to fill so name the same name I can also write or either you if
45:30 - 46:00 you want to write the another name that also you can write but I'm writing the same name AI project again I'm writing the same name okay so once I write this name again what I want to do uh so again once I created okay so here I have written the resource scope then I have written the resource details for that particular things then now again here you can see one option which is nothing but your for this you have to
46:00 - 46:30 create it to create This is a plugin you can click on create new. Okay. Once you click on create new here again you have to give name for it. Okay. You can write. So what I can write name AI hub I can write the name. Okay. Because we are creating one AI hub over here. For this I can simply write the name. Is it clear to everyone? Anyone have any doubts still
46:30 - 47:00 so far? Yeah. No. Okay. Yeah. No. Now, how can we make it? Yeah. Using this things, we we can clearly make the things. Okay. But this is this one is a paid. Okay. If you want to create a project, you can purchase. It's up to you. It's up to you. getting if you want to create projects on this you can do either you
47:00 - 47:30 can create projects using a pythons and so many things also okay here just focus what we are doing and the how we can do the things right so I have written the name for this particular hub here I have written name once I written the name now here you can see the region uh HQ US 2 from this I will make the east US from the east US to you
47:30 - 48:00 have to make it east US once you make this again you can write this name resource details you can write the same name again like I'm writing the AI of okay I have written once you've written this name so check once you check you have to check whether everything is fine or not yeah just check the name is okay this is the location is right this is right no error nothing is missing Okay, you can keep the another things as it is. So everything is okay. So now what
48:00 - 48:30 we can do? We can simply click on create. Again I will explain you from starting what we did. We log to the portal.asure.com. Uh we were on the homepage. From that homepage we seen so many services. Okay. And there so many options over there we seen one by one that all options. After that what I want to do I want to create that particular projects. Okay. which can read the captions of that particular image. For this what I did, I searched for the
48:30 - 49:00 service. The service name is nothing but the uh Azure AI foundry. So I search then I redirected on that particular page where I couldn't find that particular service. To create that service I seen that create button then I click on that create button. After that I click on the projects. Okay. Once I click on that projects then I redirected on that particular page where they asking for me a resource group. Then again they asking for the resource details for the name then fly name I entered. Then after that what I did I
49:00 - 49:30 wanted to create that hub for that hub I have written the name as a hub. You can write any name. It is not compulsory that you have to write a hub only. Okay. Then after that what we did we uh select the region over here. The region is nothing but your east US and then after that everything is clear. Everything we have written. The other thing you can keep as it is. Okay. The default things you can keep as it is. No need to make changes over here. Then
49:30 - 50:00 after that here you can see the button which is nothing but your review plus create. So now what we do we will create on that button review and create. So now here my project is getting ready. Okay. It will take some little bit time some seconds and some minutes. Okay. Still it is getting uh loaded. It is getting loaded. Okay. You can see over here.
50:00 - 50:30 Okay. Okay. It is getting loaded again. Within minute it will get working. Okay. So can we make the final side app or the website? Yeah, definitely you can make you can make the final side app or the website you can make. Guys, will you repeat please? Yeah. Which step are you asking to repeat? Which step you are asking to repeat? Uh I couldn't see your name. Which steps? Okay, I can I can explain you.
50:30 - 51:00 Don't worry. Don't worry. Okay for this so whatever we learn that you are asking for the repetition guys can you show how we can deploy Microsoft create yeah definitely definitely definitely don't worry don't tap create okay tap create okay so now what we done now here the previously the first thing I will again explain you from the first okay the firstly what we did we go into this search box into the
51:00 - 51:30 search box we Search for the service. The service which is nothing but your Azure AI found. Once you search for that service then we see there haven't created the service. There was no service. So now what we need to do we wanted to create the service. Then for this we create click on that create. After that we click on projects. Then whatever we the detailing they ask we filled. Then after that whatever we detailing we filled. Then review and create button was there. We click on
51:30 - 52:00 that then they get load and then after that you can say the validation pass means the whatever the names the whatever the things we given there. So the all things pass over there and now our project is created successfully. Okay. So our you can see you can check your resource group which is nothing but your AI hub. The name again AIHub default project resource. The default project resource group is nothing but your AIHub again. Then region which we have selected which is nothing but your
52:00 - 52:30 is US reason you can see over here. Okay. And this service AI services the name which is automatically default created. Okay. This name the storage which is also created over here. Okay. The key values these are also created over. Okay, because for this particular project we want or we need the storage and which is already there while using that particular service. Okay, it is created. So now what we can do we have to create on
52:30 - 53:00 click on create. Okay everything is clear. We give name we created a hub the validation is passed now. So what we do we will click on create. Okay, once you click on create, so now uh your that particular model the service is getting read. Okay, might be it will take a little bit time not much time. Uh it is getting deploying the things as you can see it is getting loaded. Okay, so now it is asking the portal.asure.com says your unsaved edits
53:00 - 53:30 will be discard. Yeah, absolutely. If suppose I haven't saved it will discard it. So what I do? I will click on okay. Once I click on okay, I will be redirecting on this particular page. The page is nothing but Microsoft machine learning services. Okay, this is the page. Uh this is also the one of the menu bar. Here you can see uh it is getting deploying uh which is in the progress and here also you can see the resources what the resources were getting. See the storage account is
53:30 - 54:00 okay right? All resources which we are created that all resources getting ready only. Okay. Once the deployment is getting ready then we will go or we will redirect on that particular page where we can perform that particular operation that we want to perform. Getting okay. Still so far again I am asking any doubts the students can we make the projects on the object machine using Python and regular? Yeah you can make projects on this. You can make projects
54:00 - 54:30 on this. Absolutely. Even uh if you remember now into the generative AI we use some chat boards there also you can you can make the projects if you are interested in that particular things you can create projects of this also. You can create project using Python. It is absolutely right. Yeah. Yeah. No doubt. Okay. Thank you. Thank you. Okay. Is it clear for you? Okay. Okay. No doubt. So now I'm seeing okay it's clear okay now see so
54:30 - 55:00 the things are ready over here the service which we created the service is ready now so here we can see deployment details into that deployment details the things which we created that we can see the storage we can see that particular service name the resource name resource group name you can see okay and once you close here you can see the next step the next step is nothing but what we have to do we have Simply click on go to the resources. Okay. What we do? We can
55:00 - 55:30 simply click on go to the resources. We will we can simply click over here. Once you click over here then again it is checking the things resource group locations projects uh resource group everything it is again checking. Once it is everything is fine. So now what we can do we can simply click on the launch Azure AI form. We can simply click on this. So now simply click on launch uh Azure AI front. I click over here. Once
55:30 - 56:00 I click on this, so it is redirected on the another page in front of you. You can see this is the another page. Can you see this page everyone? Yes, you can see this. Yes. Still so far any doubt any doubt about it? Whatever will be done over here. Any questions related to
56:00 - 56:30 this? Yeah, I can do it. Okay. Abishek asking for the again. Okay. All understood sir. Okay. Thank you. Thank you. All understood sir. Okay. Uh those who are asking to do it again now. So what I do? See uh right now what I done? Right now I created I'm in the flow. Okay. So after completing this particular things I will again repeat. So don't worry about this what I have done I will again repeat. Don't worry
56:30 - 57:00 about this. Don't worry this. Okay. So okay if you want to make you can purchase the things over here right. Uh the first thing that I will tell you this is not free. If you want to go with that paid plan you can go. It's up to you. Is up to you. And using this you can create a projects. No problem. No problem. Okay. But it's up to you. It's up to you. Uh we just have to launch AF only, right? Yes. We have to first
57:00 - 57:30 create the things and then you have to go into the resource uh groups and then resource list and then from that you have to launch. Once you click on this launch uh AF you can redirected on this page of this particular page. Okay. So I can submit corresponding Google drive. Uh if you are learn about the GitHub it will be the good it is good you can take the your friend help and you can create your G please do that but
57:30 - 58:00 please uh upload the G link also only is got it. Okay got it everyone. So now we redirected on this particular uh after launching the things. Okay. So here again the so many options are here the things which we have created the deploy model uh three the so many things are here right the things we are going to discuss one by one but before going to this things what we do now guys we will create a project okay once you
58:00 - 58:30 launch your particular things once once you launch launch that particular service once you launch that uh resource so what you need to do it is asking for to create a project. Okay. So now you have to create a project. To create a project, what you can do? You can click on new projects. Here you can see the simple option. See this is a simple option. Here you can click on the new projects. New projects. So here you can
58:30 - 59:00 see I can see I have that default name. Okay. So I will replace that default name. If you want to keep that default name, you can keep as it is. Either if you want to change the name you can also change the name. So what I do okay object I can say the captioning I can write the name the object captioning. So the name is we can write the name and then after that what we do we can simply click on create simply click on just give the name the
59:00 - 59:30 hub is already created by us and the hub is nothing but your aim. Now it is asking the project name you can simply write any name to it. Okay. So I have written because I am going to uh get some captions or I'm going to write that descriptions for that particular image by the AI. And for this I have written the object captions for okay from image I want to extract some information. So then after that what we do we can simply click on
59:30 - 60:00 create. There's a create button that you can see. Okay. Simply you can click on create. So you can see here. So it is getting loaded. Just wait for seconds. Okay. Is it clear to everyone? Still so far. Any questions? Just
60:00 - 60:30 Okay. Okay. Yes. Understood. Okay. Understood. Right. So now we direct redirect. See here you can see your project name is here. Okay. This is your project name. Object captionings. Okay. I just mistake. Okay. Object captioning the name is here. Then after that what we have? We have the API. Okay. Again just give me a minute. What I do? I have return
60:30 - 61:00 the captions. Okay. So captioning I just clear this. Okay, edit the name because I'm missing one later over here. So now again what we do it is getting saving. So for this just we have to wait for this. But here you can see the so many things and the keys. Okay the endpoint keys are nothing but and the the keys are working as APIs. The keys are nothing but your APIs. Like see the endpoint keys and these are nothing but
61:00 - 61:30 your APIs. So why might be you might be have some doubts why this API keys are here? Anyone have any doubt why API have wonder about it? Why API key is here? Why why the keys are here and what is the keys are? Yes. So to create projects Microsoft is compulsory. It is not compulsory. It is not compulsory to use. But if you want to create project related to this
61:30 - 62:00 the project like this so that time you can use but again I'm telling you this is and the paid version if you are interested you can purchase but for this you have to give that cards and all things okay but you can create project using plain python like the pre in the previous sessions we seen using pure python we have created some projects Okay. Okay. So again see here you can
62:00 - 62:30 see API key. Okay. So why this API key is here. Suppose whatever the things I'm doing over here and in future suppose I want to connect these things with my web applications either I want to connect these things with my uh Android applications or any applications with the any applications or the any I want to implement these things with in another website. So for that basically what I do I can simply copy this API and that particular endpoint and I can use
62:30 - 63:00 it it will get a communicate with okay for to communicate the whatever module you are creating and that module should communicate with that another things and for this basically the API key is here the API key is available but for now we are not integrating with any applications okay we are running our practicals over here on this so I'm not copying this but In future if you want to implement with that any other application that that you can there you can do this. Okay. So again uh this is a
63:00 - 63:30 simple things. So now once we reach here so here you can see the so many options. See the model catalog is here. This is simple overview. Then after the overview you can see the model catalog. Into the model catalog you can see the so many pre-trained the LNM models are here. Right? The the module which is already trained we just want to implement that we can implement but these are the LNA modules which are the pre-trained
63:30 - 64:00 already trained models are available okay the playground is available the playground is used for that particular chatboard and all things if suppose I want to create but after this particular project I will show you that okay I will show you the playground which is the one and we are also going to use this particular things okay then after that you can see the AI service okay so into this AI service once you click on this AI service. So there are some some uh services I here like you can see infuse
64:00 - 64:30 uh the services basically which is related to the computer visions okay and using these services we are going to perform our practicals but before that I will explain the things again you can create your agent for that particular agent here we have some pre-esigned template that we can use and into the fin also uh if we want to add something in your predefined models if you want to modify that you can do over here. Okay. And then again assets we have, what assets
64:30 - 65:00 we have and using this all things we are going to do we are going to work on this. Okay. So now what we do uh I want to read the captionings from that particular project. Okay. So for this here you can see the page services here there the language translation is there. Then again you can see uh the vision plus document is there. So what I do I will simply click on the vision plus document. Okay. For that image captioning what I do I will simply click
65:00 - 65:30 on the uh the vision plus document. Vision plus document. So simply click over here. Once you click over here so here also you can see the uh three things. Okay. See we are on that particular page. Now it is here for the document. If you want to do something for the document that you can do. Then here you can see the face and then after that you can see the image. But now what I want to do I want to read caption from that particular image. And to read that
65:30 - 66:00 caption from that image. So what I do I will simply select this image all options. Okay. Once I select this here you can see the common object detection using this service. You can detect your common object and then if you want to read the image captioning that you can do then here what the things are available that particular image and the everything you want that you can extract from it okay and then image search also you can do okay but now what I'm doing
66:00 - 66:30 I'm going to do the image capture but still so far it is clear to everyone is it any is there any doubt is there any doubt personal. No. Okay. Any questions? I can personalize passion recommendation system. Yeah, you can make you can make personalized passion recommendation system. Absolutely. I can do uh sorry for the interruption. Yes sir. So lot of students are asking about the project part. So uh I would like to
66:30 - 67:00 request student to uh see the demo how Shellar is working on the Azure platform. kindly observe the steps and what are the things can be achieved and after this in later on stage we can just uh have a discussion about about the project part. Okay. Yes. Thank you. Thank thank you everyone. Okay for for now you can ask the question related to this cloud the whatever projects we are
67:00 - 67:30 creating. Okay. But for your final projects we will at the last we will definitely discuss about this. But now I just want to focus you on this particular things. Just focus on this. Just focus on learn this. Okay. Okay. Okay. Getting so just focus over here. So see so what I do over here I can simply click on the image captioning. I can simply click on the
67:30 - 68:00 image captioning over here. And here now it is connected with the Azure AI service. Yeah, here you can see the service which we created for this service. We have the location which is nothing but your east US right the service is created and these are this text. So now what I want to do I want to read some captioning also to read that captioning again what you do suppose uh they have they provided some images over there again we can also upload our images that I also can show you but
68:00 - 68:30 before we will use with this okay the image is over here. So what I do I will click on this image. Okay. And this is the image and that image is retained by the AI using AI. What happened? The group of cows in field. Right. The group of cows ging in field. Here you can see it is detected the man holding a serboard on the rock. Here you can see so many things. See but this already provided
68:30 - 69:00 pictures that I am using. If you want to upload your images that you can also upload over here. Okay. Suppose I want to upload this image the image I have I uploaded over here. Okay. Now group of chickens in the grass that you can see see again we can upload the other image like suppose I want to upload this image the puppy running in the grass. Right. So you can I either if you want
69:00 - 69:30 to take im your image you can take and like this this particular system can uh detect the things and write the caption for this write the caption for this particular image again again again if suppose I'm taking another image suppose I'm taking this image uh this image is about the frog in the pond that you can see over right so here this is the first service What we are doing we are getting the captions for
69:30 - 70:00 this particular image. Uh whether you can see the already images are here that you can see over here either you can upload your image and that it can write the caption for this. Uh again if I go back okay I will just go back one step. I will show you again another service. If I go one step back okay so image captioning is here. So now what I want to do I want to detect the common object for that particular things. Okay. So
70:00 - 70:30 this service also we can try once you click over here from this you can detect the common objects like this if I click over here. So what the common objects like a person this is a person then again it is a person then subway you can see the subway right. So the common objects are detected by this. Again if you click here on this image from this image also the footweares it is detected. See here you can see the footwear the footwear also detected.
70:30 - 71:00 Then again the person is detected laptop is detected there the sitting is detected person another person is detected again another person is detected the sitting the sitting the things the sofa set the things are detected the table is detected. Right? So from this particular image the insights which taken by this for this which service we are using the service which is nothing but your detect a common object in image from that image
71:00 - 71:30 to detect the things we are using this service. Uh if uh you want to upload your own image that also we can do. Suppose we have some images. So what I do okay I will upload the image. Okay. So I will just upload this image simple image. Okay, in this image it is only detected the elephant. There are we can't see the more things over here. What we do? We will upload the another image. Another image. Another im. Okay. We will upload
71:30 - 72:00 this image. This image. Okay. So this is the image which is uploaded by us. So the image into the image there you can see the person then person and then member. Okay. The things are here. This you can see again these are the things okay what you do you are just able to see and what we observe over there we just uh what the things like we read the captions right then after that the
72:00 - 72:30 common things we extract from that image what are the things are available okay I just came back so again I will go to this particular page then here you can see we were on the images okay then pages the common things what is here then again we can do the change captioning means the caption in detail that we can see uh captioning the caption in details that you can do over here like how if I select this particular image okay I select this
72:30 - 73:00 particular image and that image scene here you can see the caption in detail the woman sittings on the couch with a laptop and right you can see that the this is this is caption for this whole image Then dog standing on truck. Then person holding a laptop. The woman sittings on the couch with the laptop. Then white cuff on the red. So everything you can see over here everything is detected. And for that everything it is write uh
73:00 - 73:30 written the captions for this for everything like the same if you want to upload your image also you can upload that image. But before going to that image, I will also show you this this one into this the man driving a tractor in the farm right that you can see over here the man driving a tractor the blurry images of the trees the trees images you can see see the blurry images see the some tree images are there but
73:30 - 74:00 this is the blurry images so that you can see the man riding tractor the the blue sky above the mountain that you can see the blue sky above the mountain that you can see the tractor in the field see the field and inside that field you can and it detects the tactics. So for this uh it has written the captions. Again I will click on browse for this. Then what we do uh we will upload something
74:00 - 74:30 this. Okay. So into this again the person standing in the field the woman in the dirty field means uh the farmer that we can see the wooden structure in the grassy area that Buddha wooden structure we can see the person walking in the field the person in the blue heads car right so many things are here so many things are the person walking in the field the green field with the like so many things for everything it is
74:30 - 75:00 writing the captioning that you can see again I am uploading the another image. Suppose I am uploading this simple image. A simple image. Okay. So, man insue. The man insuit. The man with the dark hair. The person wearing a tie. See this things extracted from this particular image. These things has extracted from this particular image. If suppose I upload another image, the image suppose I upload another image like this. Okay. Suppose I upload this
75:00 - 75:30 image. From this image you can it is writing a man wearing a face mask the man wearing a gray jacket uh pose of of the person's names right so see see so the for this uh our system is writing the captions hope it is clear to everyone how to use the service how this service is basically working is there any doubt so
75:30 - 76:00 far Okay. Okay. Not detect the person name. No, it will not detect the person name. Yeah, this is a good questions. Uh whether it is he is famous or not. Even see now I am uploading that celebrities pictures. They are the famous. No, everyone's knows them like but then it is not detected that person. Uh but the things what are in that particular pictures that's only detected by good questions.
76:00 - 76:30 Yeah. Nice. Again any questions? How can we train the model to detect the disase? Yeah, we can also train that model with the help of the images, right? Uh you have to pass so many things, so many images over there uh images data set of that particular disase and based on that we can train them. Yeah. Yeah. Okay. Okay. Yes. Right. So here also we are going to discuss about the another
76:30 - 77:00 service also I will tell you. Uh still so far what we done we write the caption then we detect the common things from here. Okay. So now uh I want to detect the face detections right the face detections. So for the face detection what you can do you can simply click on the face uh from the image we into the image we extract some insight from that image. But now what we want to do we want to detect the face. For the face detection you can click over here and
77:00 - 77:30 you can simply click the click on try demo. Once you click on try demo the already there are so many images are here. So you can click over here. It is only for the face detections. And now it is showing uh the face mask. No the one face is here right but there is no face mask. There is no face mask but there is one face is there. Okay. Now again the how many faces are there it will also be detect the one face the face mask no again here
77:30 - 78:00 you can see the face one and the face two the one face this is face one this is face two and the both faces haven't wear the mask again if we click over here so this is the face again the face one the face mask is the face mask covering nose and the mouth uh if suppose There is a face mask right and that face whether that face mask is covering uh the nose and mouth. So if it
78:00 - 78:30 is yes it is showing yes uh even you can also upload your images. So now I am uploading my image like this. There's a person uh the person the face is not wearing the mask. Okay. Then again I can upload the another image. You can see here uh this image. You can see the person face one not wearing the
78:30 - 79:00 mask. Okay. Now we will upload the mask color image. Okay. Those who have made the mask. So this one. So what I do? I will just click on open face one. Uh the face mask. Yes. Whether it is cover the mask mask covering the nose and mouth. Yes, it's cover the nose and mouth. Right? Getting this? Okay. Hope this is a clear for everyone. This is clear for everyone. Okay. So, still so far what we
79:00 - 79:30 done uh we uh write the we extract the information from that particular images. Right. Uh right. And again we also detect the face over there. So now what we can do uh we can create we can also create a simple a chat port also. Okay. So now I will tell you how we can create that chat port also. Okay. How we can create that chat port? I will
79:30 - 80:00 tell you to create that chat port. Uh at the left hand side you can see one option. The option which is nothing but my assets or option. You can see can you see this everyone? Yes. Okay. Okay. So, someone asked me the chatboard in VS code. See guys, uh we can't create the chat port uh using that VS code. If you
80:00 - 80:30 want to create the chatboard for this, you have to write the number of lines. Okay? You have to train your modules your like using the coding writing Python codes you have to train and using that Python or the any other language using that uh you have to design your own user interface it will be very time consuming if it is I'm not saying you cannot create using the VS code but if you are going uh using that VS code so there you have to write a
80:30 - 81:00 manual course every time you have to write that codes for the user interface you have to write the Then to train the module to train that particular chartboard, you have to train your machine learning module manually. Okay. But the cloud is providing the things uh which is we can say within a less time we can train our module and after training after creating that module we can easily deploy that module wherever you you want. So here no need to use a uh we can say the no visual studio code
81:00 - 81:30 and the rep no need to use it. no need to use. Okay. So that's the advantage of the cloud means what without writing a single line of code what you can do you can create the things only without writing a single line that you can do. Okay. Yes it is acceptable real estate project using ML it is acceptable. Absolutely it is acceptable. Okay. So now just just focus over here what we
81:30 - 82:00 have to do we want to create our chart to create a chart again what we do we can see you can see this option at the left hand side there is a my asset one option into this my asset you can see the three option the first option is modules and the endpoint the model index and the web apps from these options what you have to do you can simply click on modules endpoint modules endpoints you can of this model ends. Once you click
82:00 - 82:30 over here, okay, then again you can see uh this is an uh user interface. So now what we are going to do guys, we are going to create a chart. We are going to create a chart. For this to create a chart what we done uh we were on that AI services from that AI services we shifted the model plus endpoint. Is it clear? Yeah, you can do object detection in Jupyter notebook. Yes, you can do guys.
82:30 - 83:00 Okay, is it clear now? What we are going to create guys? I want from your side. What we are going to create now? What we are creating now? Okay. What we are creating now? I just want from your Okay. Chatboard. Yeah, you can use API. Yeah, AI chatboard. AI chart. Absolutely. Absolutely. Yeah, you are there, right? Uh I thought you sleep but no you are here. Good. Okay. So
83:00 - 83:30 now yeah you can create any projects. Okay based on AI aim. Okay. So once I create this is your our simple user interface. From this user interface what we do again we can click on deploy model. Deploy model. Click on this. So again here we have some model the base model and the fine-tuned model. Okay. So what we do we can click on the deploy
83:30 - 84:00 model the finetune model. Have you heard about the fine tune model? Anyone have any idea about the finetune model? What is the finetune model? Uh someone say no. No no. Yes. Yes. Someone say yes. Okay. What is it? Was it it? Those who are saying key they no. So what is what is this balance model improve model? Okay. Uh it is exactly with the absolute data train existing model. Right. So
84:00 - 84:30 that I was expecting what we are providing training to the existing model which is nothing but your fine tuned model and we are starting from scratch which is nothing but base that we can simplify means the weight and the bias are existent train pre-trained model with our data right the pre-train the which already the model already available the train and we have to pre-train that particular model with our data which are fine tuning that we are doing okay but we are not using that fine tuned model. So what we are going to do we are using here uh the base
84:30 - 85:00 model to for this what we can do you can simply click on deploy base module okay simply click over here deploy base model once you click on this okay so there are the predefined modules these are nothing but your links now so from these links what we have to do we have to select one which is nothing but your charge GPT 4.0 this way. Okay. So what we done? We
85:00 - 85:30 click on the project and from that project what we done we click uh on this simple that deploy the base model and then after deploy base model we redirected on this page on the once we redirected on this page we can see so many L&M model the predefined model the pre-trained modules are here from this pre-trained model you have to select the GPT4 O alarm this this module you have to select okay So to select this you can
85:30 - 86:00 simply click over here once you click now it is the task chat completion then JP4 offer the sweet and how modules interact with the multimodules okay so the model will train the things over here okay so what we can do here updates the text image processing JSON code par function so many things we can do over here okay these are the resources so now what I do I can simply click on I can simply click on
86:00 - 86:30 confirm. Okay, we can simply click on confirm. Once we click on confirm again is uh here you can see the detailing of this the connect the AI sources okay key and then project's name the project name we already written this the capacity of the token per minute the everything is here the resource location is here okay everything is here once you can see this now what you can do you have to simply click on
86:30 - 87:00 deploy simply click on deploy once you click on deploy Now again again you can see the endpoint and API as I already explained you. So why we need this endpoint and API key in future or if you want connect this particular chat with your application to connect this you have to use this. If you are not using these things you are not able to uh you
87:00 - 87:30 are not able to connect this chatboard with your any application. Okay. And also for this they have provided the guidance. So how you can do the things what things you require if suppose you are using that particular things using your Python. Okay. For this you have to uh import that OS which is nothing but your root directory then you have to from open AI you have to that Azure open AI. The steps all steps are mentioned over here. And like this you can
87:30 - 88:00 implement your chatboard with your any web application. Any web application the all guidance are provided also. Okay. So here you can see what is the data. So all guidance and everything are provided in here. From this you just need to use this API key endpoint and after using this API key and end point you can implement into your projects and you can use the chatboard in your projects. Okay. In any application that you want to implement it. Okay. Once this done
88:00 - 88:30 now what we do now we have to check our chat right the whatever the chatboard we have created that chatboard what I want to do I want to check whether it is working fine or not to check the chatboard now what I do I can simply click on open in playground okay you can directly click from here either you can directly click from here so what I do I can simply click from here open in playground simply click here. Okay.
88:30 - 89:00 Simply click here. Once you click here, you can see your chat is ready. Now, see, this is your chat book which is ready. And you can ask any questions. Any questions. So, now what I do? I will ask what is AI? Okay. I will ask what is EI? So, here you can see the out. See the AI the artificial intell refers to
89:00 - 89:30 simulate the human intelligence in the machine learning that programs things right the all information see the key features with this all things you can see over here it's written everything the types whatever you want to ask this is your child you can ask anything to anything to uh suppose I ask one questions uh what is uh [Music] 1 + 1 is equals to I suppose I
89:30 - 90:00 entered same here you can see it's also perform the mathematical operations this operation performed by the chat and to that chatbot using API key using that endpoint you can integrate with your web app that I can see okay is there any doubts still so Can we talk? Yeah, you can. Okay. Any doubts
90:00 - 90:30 still so far we're talking? Yeah. No. Okay. Again. Okay. No doubt. No doubt. Okay. Hope this process is clear to everyone. This process is clear. Can we generate the image? Yes, absolutely. Okay. Likewise, but basically you have to train the model. Uh still now basically the assistance
90:30 - 91:00 will only provide you some text till now, right? Uh we can't get that image now or we are not generating the image. As you can see the response format here. We can only get the text for we are not getting the units. Okay. Again, what are the alternative to modules? Yeah. Yeah. You can you can definitely
91:00 - 91:30 share definitely we can find the model right fine. But for this we required the lots of data and we have to pass that particular data uh model based on own output and then feed. Yeah, we can do can we design the image based? Yeah, absolutely we can do we can do that's also we can do using L&M we can do the things and our module will get trained and based on that we will get power. Okay. So hope this is clear right and
91:30 - 92:00 that you can implement with your project. Okay. Uh the all the process is clear for you. But the one more important thing that you have to focus over here the thing is uh what you have to do you know uh whenever you are using that resources. Okay. If suppose you are using that resources but at the aim uh once you use that particular things or the once you done the practice if you are the students and you you are doing the
92:00 - 92:30 practice after the practice you have to delete that particular resources leading resources because it is generate the bills based on how the how much duration you are using based on that it will raise the bill getting okay this is a simple one project okay that what we done uh into this particular project which service we have used guys I just want to ask what service we use to create this
92:30 - 93:00 project Azure AI service AI service but the exactly the service name what is the exact service name AI foundry lure AI foundry right Azure AI foundry which is the service name right which is the resource name which we created what was the first step the first step we created that once we created that for that again we gave some names we created some resource group then resource hub and then after that we redirected on
93:00 - 93:30 this page and after redirecting on this page here we are we seen how we can extract the information from the image how we can write the captioning for that particular image how we can detect the common object in this particular image from that particular image how many faces are there then again We done the phase detection over over there right the phase detections also we done uh the how many faces are there whether that face cover with the mask or not these
93:30 - 94:00 also we learn over there right these are the modules again uh then after that what we done we go to the my asset from this my asset uh what we done we just created the modules plus endpoint and model plus endpoint from here we have created the chat board Okay. What is plus endpoint? Yes. Yeah. Service and chart. Right. Okay. So again if you have any doubt I will again tell you how we created this chartboard. The initially
94:00 - 94:30 we were here right on that phase detection. But now I want to create this. So for this what we done? We create on this. We click over here. From this we have one option. the option which is nothing but your projects right from that projects we just deploy the base model and from that we selected the things based on from that we selected the charge GP see here you can see the charg 4 right and
94:30 - 95:00 then we created that chart if you want to go on that chatboard again what do we do we can simply click on opening playground and here we can check whatever you want to ask you can ask the question any types of the question you can ask that should be it will be getting in the text. Don't ask for the images and so on. Okay. So this is our one projects. Hope you clear about
95:00 - 95:30 this. Uh as a AI tool PowerBI basically used for the analytics now. I think you asked the same question yesterday. Yeah. Clear. Okay. So now for the projects again I'm telling you uh the first please complete your all A1 courses which are available on your portal. Okay and already madam explain you the ma'am already explained you the
95:30 - 96:00 deadlines for the project submissions. We already provided you the templates for that projects right? Can we make the car price prediction project? Yes, you can make you can make that project you can make, right? Uh the projects on housing predictions and the spam detections may Yes, you can make that. Okay. The PPT is already provided provided to again at the last 10 minutes I will explain you but before this uh I will tell you about the another service also. the one service within 10 minutes
96:00 - 96:30 I will tell you which is uh which is very good and the service basically is the machine learning service and using that service what you can do now you can create your Jupyter notebook into on the cloud on cloud no need to use your Jupyter notebook in your local machine you can use your Jupyter notebook on the cloud so I will tell you how we can create that Jupyter notebook on cloud to create that Jupyter notebook okay now just focus over here guys just focus on the cloud just focus over here. Okay, just focus here. Just focuses uh
96:30 - 97:00 create spam detection. Yes, you can attach on box or not. Yes, you can do that definitely. Okay. So, now just focus over here. What we have to do? We have to create a machine learning uh service. Okay. And that service using that service what we can do uh we can create a Jupyter notebook over here and you can run your Python codes, right? The whatever codes you want to do you can run over here. So for this uh what I do okay I will go on this page. This is
97:00 - 97:30 your page. Now from here what I do I can simply click on the homepage. Okay we can come on this homepage. This is our homepage. As you can see over here this is our homepage. Right. Once you come on this homepage uh you can see the all resources the resources which we created previously. These resources created by us for the previous project. Okay, this resource. You can also delete the this resources. But now I'm not deleting this. Uh what I do? Okay, I will create the another uh service. The service name
97:30 - 98:00 is nothing but your Azure AI Azure machine learning. Okay, for this I will search the Azure machine learning. Azure machine learning. So I just search Azure machine. See this is a service Azure machine learning. I can simply click on here. Okay. So for this again this service is not created. Right? The services is not created. To create a service again what I do I can simply click on create. From this then new workpiece. Okay. For this what you have
98:00 - 98:30 to do? You have to click on new workace. So simply click over here. Once you click over here again what we do we can simply uh write the resource group like a previous step. Okay. So for this what you do? We can click on create a new once we click 10 what we do we will do ML uh I can simply say the project the previously we return the AI project now I return the ML projects
98:30 - 99:00 then what we do we can simply click on okay after that workpress detail they're asking for the workpress detail for the workplace detail we can write it the ML again same name I am providing over here project and region that we want to select. The region we can select here the east US. Okay, this is the option east US option is here and then everything you can keep as it is. No need to do anything here. No need to
99:00 - 99:30 change anything. No need to create the hub because there is no option for to creating hub over there. So for this what you do you can simply create click on the review and the create review and the create again same it will take some little bit some little time over here now it is validated right everything is validated the resource group the regions and the names that we provided everything is validated over here once it is getting validated so
99:30 - 100:00 after this what we can do again we can click on be create. Okay. Again we can click on again we can click on create. So just wait for here. Okay. Uh you have to choose the region or uh whatever you want. I you can it is most probably use the
100:00 - 100:30 Just wait. Just wait. Just wait. Okay. Once you wait then again it is getting ready over here. Deployment is in process. Okay. The same the another services are getting uh ready for here. Uh within seconds or the minute it will date.
100:30 - 101:00 So display it. Okay. Okay. Still so far any doubts? If you have doubt, do we need to buy the subscription? It's up to you. It's up to you. It's up to you. If you want to go with this, you can go with this. It's up to you. But what we have to do, right? Okay. So, deployment is getting
101:00 - 101:30 ready again. The one thing is already over here trying to identify emotions of the person. Yeah, it is absolutely okay. Absolutely okay. The project for the sentiment analysis chart. Yeah, sentiment analysis chart is absolutely not an issue with this. You can use that. Okay. See now, now this things our
101:30 - 102:00 service is ready. Now again what we do? We can simply click on go to resources. Once we click on the go to resources then again here you have to do some cross check what the things that you want. You can again cross check over here. Just cross check project check everything is okay. Once everything is okay you can simply click on the launch studio. Okay. Uh so once you click on the launch studio so they uh here the so
102:00 - 102:30 many services are here if you want to go with the generative AI the generative AI services so that you can go with that services so whatever you want to do with that you can do might you remember using the Microsoft copiler studio we done some projects using generative AI right like the similar project you can do over here as well okay also here you can see the predefined module the L modules are available And you can use that module and using that module you can do the things. But for now what we want to do
102:30 - 103:00 uh we have to create a Jupyter notebook right to create the Jupyter notebook uh here you can see at the left hand side you can see one option which is nothing but your Jupyter notebook. But before creating a Jupyter notebook students I just want to ask you see uh we can use that Jupyter notebook in our local machine right? Can you use Can we use? Yes, we can use right because previously whenever we create some projects now
103:00 - 103:30 machine learning projects uh deep learning project that all projects we done uh on your local machine then um why we are using this Jupyter notebook on cloud. Anyone have doubt? We can do the same things on your local machine. Then why we are using uh the cloud on the cloud this on the cloud this Jupyter notebook why we are using Jupyter notebook why we are using it storage but
103:30 - 104:00 we are getting storage on our local system also now due to RAM constraint. Okay, the main important thing is like seeing uh while using on the cloud there is no limit for this right. If suppose uh I am working on the large data the big projects so might there are chances on local system uh my local system it will not getting work properly but if I
104:00 - 104:30 use a cloud on the cloud I can get the scalability right I can use the as much as big datas for this and I can train the things and the more important things I can get the GPU on this cloud that I cannot get in local machine the GPU right the graphics processor units that I can get on the cloud which I am not I cannot get on the local systems again if
104:30 - 105:00 I am using the Jupyter notebook on the cloud the again one more important thing is that I can collaborate I can collaborate the things with the many peoples that I cannot do with the local machine right on the same project Here the multiple people can work together but into the local system it is not possible. Even uh there are the more chances into the local system. If suppose something happened to the local system, there are more chances to lose our project. But on the cloud there are
105:00 - 105:30 no chances to lose your projects. Right? If suppose your system is crashed, what you can do? You can log to the another system and you can just access all the things with it. Right? So these are the advantages and that's what that's that's what we are using uh the notebook on the cloud. Okay. So to use that notebook the first step what you have to do on the Azure you have to search Azure machine learning. Once you search then you have to write the uh group name and then
105:30 - 106:00 details about the resource and then once you write then you have to launch that particular service. Once you launch that service uh you will be direct you have you can be directly redirected on this particular page. On this page you can see the so many things that you want to perform. But from here at the left hand side we can see which is nothing but your notebook. So what we do we can simply click on notebook. Once we click on the notebook okay once we click on the notebook here you can see uh the directory which is
106:00 - 106:30 already created. Okay. The shell the arishella the directory which is already created over there while creating we can say might this directory created while creating our service or might this directory is created when I create that particular account when I got the account by that times also this directory. Okay. But if you want to create another directory you can simply click over here another folder. If you want to create another file if you want to create you can create your own files. Okay. But now what I want to do I want
106:30 - 107:00 to just simply simply create my file. Okay to create this file what I do I can simply click on this inside the arr folder I want to create a file. To create that file what I do I will click on this three dot and then after that I will click on this create new file. Once I click on this three uh create new file here you can see the file name. the file name which is the untitled you can write the name suppose I want to write I can
107:00 - 107:30 write the first okay I written first the file extension should be it is the notebook so IP yp file yeah right then after that uh the override already exist you can do but I'm not clicking over here so what I do I can simply click on so here you can see our file is created successfully This is your file and this file is
107:30 - 108:00 created successfully. So in inside this file you can import the numpy pandas matlock seat learn so many libraries you can uh import and you can keep working on this but still so far I will just print I will just test it whether it is working or not. So what I do I will just click hello one the simple code I just try to run but I click on this run sale but it is not working. So for this again what you do here you can see the compute and
108:00 - 108:30 then after the compute here you can see some option. Okay the serverless sparks compute so available. So what you can do you can select this you can select this you can see confirm the switch compute changing spark full stop. So are you sure you want to continue? So you can just complete you can simply click on this. Once you click on this so again it is just got refresh. So what I do I will just again write
108:30 - 109:00 here hello world. Okay it is getting loaded. Just wait for it. Just wait for it. Once this is get loaded, it will take might see here you can see it might take some 1 to two minutes to finish the finalizations. Okay, this configurations happen over here and once the configurations configurations happens and we can run the file. Okay. Uh so still this is getting loaded. So what I can do? So we can also if suppose you
109:00 - 109:30 have already created some files that files also you can upload over here. If you want to write the code from the scratch, so you can do over here. And if you want to uh upload your previous created file that also you can do. Okay. So see now the process has completed. So what I do I can simply click on this. So again proxation may takes 3 to 5 minutes start if you have defined. Okay. So now it is getting loaded. Here you can check it is getting loaded. Just wait for
109:30 - 110:00 this. Okay. So it is getting loaded. Still so far I will tell you if suppose you have uh already created one file and that file you have to run with this or you want to run that file over here. So that file also you can run. To run that file what you have to do you have to upload that file with data set also right with the help of data set you can upload the file and you can do that to upload the things what you do you can just simply click over here okay you can click here. So now here you can see see the
110:00 - 110:30 countdown is started. Okay it is getting loaded. So if I want to upload that file so what I do I can click over here. So there you can see the option upload files. Upload files. Okay, there is the option. So I can simply go here and from here we can also click here. Once we click I will uploading the same project that movie recommendations. Uh with that project I need a data set. So I select that P IP file and then data set also.
110:30 - 111:00 Once I select this I can click here. Once I click and then we can simply click on upload. Okay. The file is getting upload over here. And at the same time here you can see the sale is also getting run it is a first name that's why it is taking time once it it gets setups it will not take much time you can run all the things so file uploaded successfully now starting Apache spark session pro the session is also going session also going this first sale and that's why it is
111:00 - 111:30 taking time okay otherwise once you once this done for the other cells it will not take much time for Okay. So, hope it is clear to everyone. Is it clear? Yes. Okay. Okay. Okay. So, the similar uh you can create a projects. Okay. You can find the unique
111:30 - 112:00 ideas project. Yeah. If you want to do it is it is again that I forgot to tell you that you can also deploy your website. So suppose you have created website now you can also deploy. Okay. So we also need to create a deploy. Yeah it is. Again people are asking about the GitHub link. You can add your GitHub name into the PPT. PPT into your PPT at
112:00 - 112:30 the last slide. Yes. Yes. Uh was that our Yeah. picture you have to upload it? Yeah. Thank you. Okay. Hope this is clear to everyone. Is there any doubt you can ask uh project submission date 9th of May?
112:30 - 113:00 Can we do ML project? Yes, you can do the ML projects. We have to upload the screenshot. You have to upload that screenshot on the PPD. You can there is a slide in that slide. You can keep your screenshot into that PD. Uh it is nec so many fast also activity object identify projects. Yes you can create that object identify project. You can create I can can we do the diabetic prediction? Yes
113:00 - 113:30 you can do you can do this. You can do see you can create any project but the page should be the aim. The your project page should be on AI. There is no restrictions for you guys. There is no restrictions but the only thing is that you have to create that projects on AI. Your projects should be on basis of the AI. The second thing uh you have to complete that all the courses. Okay. In that addon which
113:30 - 114:00 available on the portal courses you have to complete which is compulsory for everyone. Everyone it is a compulsory right and still so far see I will tell you still so far what we have learned over here right from the first day okay from the first day you have learned so many things you have learned about a generative AI you learn about the machine learning into the machine learning you have learn about what is the supervised machine learning right
114:00 - 114:30 into the supervised machine learning again you learn about the uh regressions classifications right then after that You also learn in this particular internship what we again learn about this we learn about the generative AI. Okay. So for that generative AI I shown you some tools we create some project using the tools right. Uh so using generative AI we created the projects we learn the generative AI what exactly the prompting is how the prompting is
114:30 - 115:00 working that's we learn how we can use the image generator how we can use a code generator how we can generate the text these all things we learn right from the first day in this four week basically we learn the things right the aim AI we learn machine learning what is supervised machine learning then generative AI what is the unsupervised machine learning into the unsupervised machine learning we created the project then into that project we learn about the what exactly the clusters now so
115:00 - 115:30 many things that we learn okay then after that we learn about the deep learning right then after deep learning we learn about the uh Microsoft Azure portal which is nothing but your cloud on the portal we also created the projects on this we also created projects on this see now Our project is run successfully right here. You can see again if you want to run this you can simply click on
115:30 - 116:00 this file recommendation system and from this you can also the one by one you can click here and one by one one by one you can see getting loaded and the one by one you can click on all sales and you will get this clear to everyone what we learn what types of the project we can create everything is clear So uh shellars uh like yes sir so a lot
116:00 - 116:30 of students have still uh confusion like uh what kind of projects they need to do and like how to create a PPD and all. So uh we'll just take a couple of minutes and uh again we're going to explain about what is the submission date and how to submit the BPD as well. Okay. So uh I'll be sharing the screen again just a minute. Okay. Uh so students uh like as uh we
116:30 - 117:00 had uh taken the uh session yesterday as well and uh uh we had told like how to submit your project. Okay. So I'm going to take a recap again like what exactly you need to do. Uh the template of the project PPD template basically we have uh shared in the telegram group as well. uh you can just uh look at that. So in this specific template or the PPT you can see
117:00 - 117:30 we have given a title uh project title you can just add your project name or what kind of project it is you can just give the title of it presented by and few additional details such as student name your college name department email id uh then your eic student ID and after that you'll be mentioning out the outline as well again in the outline line. Uh you can see these are the few things what it is required. Okay. So uh
117:30 - 118:00 you have to uh give the problem statement, proposed solution for that. Uh what is the system approach, algorithm, result, conclusion, future scope and the reference. Uh you'll be mentioning out the problem statement why exactly you're creating that project and what is the cause of that project. You'll be um highlighting that point over here. Hi topic. Can you hear me? Uh yes sir. Yeah. Can you just scroll up please? I just want to add few more points for the students. Sure. Yes. Uh first slide
118:00 - 118:30 please. First slide. As uh students, we require you to upload your photo because there are thousands of students who are uploading their projects, right? We want you to be putting your photo over there in the place of the box which is specifically mentioned for you to add your photo. Right? It is an individual project, not a group project. So it will be easy enough for us to identify you with the image over there. Right? And you know what type of images you have to keep over there. Don't keep any fancy images like you know if if it
118:30 - 119:00 is a passport size photo is also good particularly over there where we can identify you with your face. That's it. Nothing good on that. Right. And please explain your project in a better way that people can understand what project you have done. Right? Students are requested to keep your student name, college name, department where you are from, the email ID, the EIC student ID, you know all these things, right? These are all the things that what was asked
119:00 - 119:30 from you and it is really important for students to be using all those things. Uh putting you know keeping all those things in the front page itself. Coming to the outline these are important things that what you have to keep in your PPT right students you can use the same uh template you can change all those things whatever you it was required so we are sharing you this templates because we need these points importantly in your video are you getting the point and students if you have any other further questions right
119:30 - 120:00 we are also connecting on Friday right so you can keep it over there and you can ask our trainers coffee and sha who are in the telegram group who can help you with the projects as well right not a problem so these are all the points which should be there in your you know ppt that's the major reason why we are sharing this outline for you right coming to the problem statement when you're explaining your problem statement
120:00 - 120:30 make it crisp make it easy for people to understand do not write your solution in your problem statement because that will not help you much over there. All right, I hope students know how to create a PPT. There is no reason I have to adding much more points on the problem statement itself. So the first thing that what we are expecting from you is the problem statement, right? Explain your problem statement explicitly as crisp as possible. If you want to keep images to explaining your problem
120:30 - 121:00 statement, you can put images as well, right? So try to understand those things. Coming to the next one, you have to tell the proposal solution what type of data that what you are collecting, how you are prep-processing your data, what type of algorithms you are using, uh what type of deployment you want are planning or looking forward, the evolvation that what you want to do and other things as well. So these are a flow which we are talking in a proposed solution. Coming to the next slide, as
121:00 - 121:30 you can understand, we are asking you you know the approach or the system approach that what you are planning in your project right where you will be explaining uh you know whatever the strategies that what you are using how you know this approach will make your project better right so you have to explain why you have selected that approach what is the reason behind it you know you could have done many approaches you have select Ed this
121:30 - 122:00 approach you know and you have to explain the reason behind that's how we can understand how good you have done the project right and next one you have to explain about the algorithm and the deploy right what type of algorithm you have used and how you want to deploy it over there so these are some important things that what you have to do and result keep your images majorly in result because we want to see the outcome of the things that what you have done till so uh what outcome you have
122:00 - 122:30 received, how good you have done your project because from that result we can identify how good you have done your project. Coming to the next one, you have to write your conclusion concluding what project you have done and how you have done as well. Next slide, the last slide you if you have any future scope you are planning to do any further future scope uh right please do add in the future scope over there. And the last references you can add your GitHub
122:30 - 123:00 links, you can add your research papers or whatever where or the links that what you have done. Please use it. I had seen some good questions. I would try to answer those questions particularly right now because you know I felt these questions are really important for the students to understand um how to add animation effect in the PPT in every slide. So I hope uh you know you can search in Google rather than asking me on that right and uh what
123:00 - 123:30 type of projects should be create and to submit. So students uh we are telling you you can select any of the projects of your own. If you can't find a problem statement I would request sir and shell sir please share few problem statements with the students to help them understand what type of problem statements that what they can use particularly. Okay, few problem statements uh and you know we can help you with few of the problem statements but it's up to you because in a world
123:30 - 124:00 now we are facing problem statements in every day life right so all these things are really important and [Music] uh yes you can log in you know the LMS after completion of the course as well right you will be getting your certificates directly over there and we are looking forward on doing that uh what language can we do language detection using machine learning? Yes, 100% you can do it. What type of
124:00 - 124:30 projects whatever projects you want to do please do and it is really important for you to understand what type of projects you are doing over there. when it comes to the you know when it comes to the P you know result the major thing that what we are expecting from you is the PPT sorry is uh in the PPT is the images of the outcome that what you are keeping over there. So these are some important points that what you have to keep in mind while you are giving your result what is the major thing that what
124:30 - 125:00 you want to achieve and how you have achieved it is really important for this. Okay. And uh there are new messages. Let me see. Uh so you will be getting this PPT template from your telegram itself. Right? Uh future skills question. Okay. Uh guys, one by one, one by one. Is it mandatory? So students, we are asking you to register in future skills. We are not asking you to do uh you know you have done all the courses.
125:00 - 125:30 That's really good. The courses you have to be doing is in from the LMS itself, right? So it's really important for you to understand that right and uh any other further questions PPTs PTS code no not necessarily we are not expecting code from you we are just trying to get the project if your project seems really good we will be making sure we contact you from your number that what you have
125:30 - 126:00 given to us and we will be requesting for the code and further from there not necessarily you how to submit your code. We are not really looking forward onto the code. We are majorly trying to understand the future things from the uh from the problem statement that what they have done right. We are really want to understand how good they do the pro you know could do the project from the problem statement from the what they have selected. Uh yes students one after one if you don't
126:00 - 126:30 have GitHub link there is no reason you have to keep it is not mandate particularly for any one of you that's right and students still you have any questions students one by one please you know I can't even read what you are asking over there uh can you use another yeah you can use another PPT but these are the things that what we are expecting from you you can use your own template but you know
126:30 - 127:00 these points should be all you know should be there in your PPT where to upload you have to upload your PPTs in the LMS itself you will be seeing uh those updates in couple of days then you can directly upload it if you you know I'm 100% sure in Friday call we will be showing you where to upload and how to upload as well if you feel some challenges over there. Yes, you can do projects on chat bots. It's totally
127:00 - 127:30 okay because the project was asked from your mentality and your freedom to be doing and we are totally okay with it. Right? So, sign language detection you can do that. Yes, you you whatever you know we will be judging you from your projects itself, right? Whatever project you want to do it's you can do it. It's not a mandatory to give a G link. Not at all. It's not at all mandatory to upload
127:30 - 128:00 your project. I mean uh to showcase your project out book recommendation systems. Yes. Uh driver drowsiness project. Yes. You can do all the things. You know there is no reason you have to ask me what projects you want to do. Please do a machine learning project and AI project uh we are good to go with that. Students if you are completing the course right it will uh we will be
128:00 - 128:30 checking that and we will be making sure that you have done that course or not. Please do complete the courses which was asked from you. Uh you know in advanced course you can do all the courses. It is really mandate for everyone to be completing all the advanced courses. Right. Uh you can start with uh basic courses if you want as well as intermediate courses for your understanding and for your upbringing of yourself and but it is really important for everyone to be completing uh you know advanced
128:30 - 129:00 courses. So you know it will work the website is working really fine. I hope you can log in now and you can check as well and the LMS is working really fine. uh MATLAB code you know and we are not expecting any quotes guys I'm 100% telling you we are not expecting any quotes right and students have to convert this PPT into PDF and please upload that PDF over to us right please do make sure that you understand what
129:00 - 129:30 you are uploading over there yeah virtual mouse using hand gesture yes last day for the project 9th of May we are not going to extend we have extended pretty far this time because most of the students came to us telling they have exams and other things as well. That's the date that what we have finalized as the last date. We can't extend more than that. If you have completed prayer it is really good mostly by tomorrow or after
129:30 - 130:00 tomorrow you can see the upload option over there and you can start uploading your projects. We are we are you know we have started uh telling about the projects from past Monday. If you have already done your project, it's really good, right? Keep it with you. We will tell when to upload and you can start uploading your projects in the LMS itself. Yes. Right. So, thank you students. Thank you
130:00 - 130:30 for participating and uh further questions I would recommend you can uh reach out to topic or shell particularly in the telegram group according to the projects and they will be helping with you. Yeah topi. Yes sir. Yeah sure sir sure yeah. So students it's really important for everyone please mark your attendance and bye-bye. Thank you uh Shabas and thank you trainers. So already I have sent the
130:30 - 131:00 recording and the attendance link in the telegram group as well. So students you may refer to that uh unless our uh until you get any new queries like which is not discussed in the session you can DM the trainers otherwise all the updates are shared in the group itself. Okay. So do refer uh to the recordings. Uh I can see a lot of students are joining in the last 15 minutes maybe for the attendance but please do go through the recording to understand the concepts before you uh
131:00 - 131:30 start your project. Okay. Thank you everyone.