쉐도잉 연습: AI-102 EXAM QUESTIONS 2026 MICROSOFT AZURE AI 102 CERTIFICATION COURSE PART-1 - YouTube로 영어 말하기 배우기

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Hello everyone, welcome back to my channel.
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Thank you so much for your support on AI 900 series.
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And we are back with AI 102 practice question series.
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So in this series,
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we are going to do lots of practice question specifically from the point of view of AI 102 associate,
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AI associate exam.
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So this is a very important exam.
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Actually, this is the like a biggest exam from Azure side for AI perspective.
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So without any further delay, let's get started.
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So first question is which computer vision client library used to analyze image description.
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So this question also like clears many things even if you don't know if you are coming as a beginner.
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This I am going to explain everything from the very starting
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and this exam is also like anybody from beginner point of view also can do it.
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So I strictly suggest you go with our videos
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and I'm 100% confident that you will be able to crack the exam if you follow all these videos strictly.
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So you can see like Computer Vision Client Library is used to analyze image description.
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But you don't know like which Computer Vision Library but it is now just reading question.
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It should be clear in your mind that computer vision is used to analyze image description.
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Okay.
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So which client library we are going to utilize.
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So if you see the option visual features types,
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so all have that visual features type and then it has dot description dot tags dot categories dot colors.
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So I can easily even if I don't know anything about this exam,
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I can easily guess.
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Okay.
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Yes, this would be description.
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it is currently matching if you know like simple english
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because some questions are definitely going to be so simple that
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if you know like english well then you are able to easily make sure get the answer okay
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so here i can see it is visual features drive dot description okay
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but in this video i am going to like not only
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just just going through the practice question i am going to explain you a more bit about it
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so you will get a proper understanding about azure how azure ai works
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because that is also very important okay so i just selected it
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and it seems out it's correct
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but here you need to understand like in exam what they will do they will throw you some code okay
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and they will put in that code they will put it
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and they will ask okay what does this code is doing
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so now you know this is used to analyze image description okay
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so this way you need to understand think into other way like uh these questions
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if you understand the concept then it will be
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if it comes in any type of manner it will be
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easier for you to understand why the they sometimes code c sharp code as well
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because microsoftizers generally throw code in c sharp and
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because it's its own their language and they sometimes throw code in python as well
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so if i just can give you an example
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because this is a like important question i have seen this in real life exam
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and talk with other students as well so what you have to do first
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if you want to utilize
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if you want to do analyze some image description what you have to do you just go here
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and like this code is in python
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so you can just import the computer vision client from this
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azure cognitive services vision dot computer vision then you import the visual features type and just credential then you just
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enter your key and region you enter your credential
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and i have stored my computer vision client endpoint
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and pass the credential
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and stored in this client variable then to analyze it what
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will i do i just do analyze dot analyze underscore image client dot analyze underscore image
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and what do i want to analyze i will provide into
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this visual features okay i want to analyze uh something i
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want to get the text then i will provide visual feature types dot tags
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or similarly for description i will provide visual features type dot description okay
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so this way you can like analyze based on what you want okay
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if i want to get the tags so i can do it
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and here i am printing all those tags
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which after analysis model feel okay these tags can be attached with this image
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or representing that image after it's done with the image analysis okay
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so now you know how to do the image analysis
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and how to pass like particular features just like tags or description
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and we will we are going to discuss more through our question in next.
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So I hope this question will be clear to you.
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Our next question is which computer vision client library used to analyze image tags.
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So now we instantly know.
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Okay, so it is visual features type dot tags.
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So I created it and here I provided the link also.
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You can check it out,
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you can just copy it or take a screenshot out of all these questions and do it yourself.
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Now how to read a file from a local file system.
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You want to read from a local,
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like it's not like a link is somewhere and you want to read
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that from a local file system you want to read.
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So it's file.openread, local file.read,
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read file.local, local read.open file.
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sometimes as i said like code would be generally in two languages python
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or c sharp
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so here it is asking from the c sharp as i can see from the option
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so it is for your understanding in questions also they like they throw you some code okay
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and they will ask okay is this code is reading something from local file system
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and if you don't know okay like which like
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which library basically you utilize to read from local system then it will be difficult for you
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so the here the option you will be file dot open read okay
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so it basically opens an existing file for reading it's a
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system io uh like basically string you have to pass okay then
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which azure service is best suited for analyzing visual content in image
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and videos to categorize content okay
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so it is asking uh like to analyze visual content in images
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and so you want to analyze visually
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so let's see the option azure ai vision it's look like
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uh this can be an option azure cosmo db it's a database
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so like it it can store but i don't know
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if can like analyze
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or something i'm just thinking from a very basic like how you need to like filter out the option
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so this is definitely not in my list Then Azure cognitive search,
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can it do analysis?
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Maybe might be, but it's a look like a search service.
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Then there is a Azure function.
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So like as my more focus is Azure AI vision
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and like I know for like you should be aware like to do anything related to visual content.
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Like if you want to analyze something visually through live cameras,
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images, or like any live feed is coming then you have to use azure ai vision service okay
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so this is a very like self explanatory options like another question is
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which of the following best describe the prediction made by machine learning model okay
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so here question is asking which of these option is best describing
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so remember whenever you are giving any certification exam there might be any chances
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that all options are correct but you have to choose the best one okay which is the best describing your answer
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okay so it is asking what is the like
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if a prediction is made by machine learning model so
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which statement is like representing the predictions okay what does it mean by predictions in simple language
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so is it probabilistic values based on correlation found in training data or or randomly selected values with equal chance of selection.
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So definitely like it's not a randomly selected value.
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Okay, right.
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So this is definitely going to be not my answer.
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Absolutely correct values based on conditional logic.
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So we know like machine learning sometimes can give you wrong answers also.
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So it is not definitely absolutely correct and like conditional loading
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because machine learning models basically rely on training data
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so like a1 is the best suited answer for me
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and it's basically represent probability that's why we see like
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when it gives you like and matching suppose
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if we take an image example it will show it is matching 99 98
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or maybe in terms of confidence score which lies between 0 to 1.
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1 means it is best matching so it says like
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if this image is matching one with confidence score one with banana
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that means it is 100 percent matching and
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if it is saying confidence score zero
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that it is not at all matching it is like machine
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learning model is 100 sure it is not banana okay
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so it basically relies on the correlation found in the training data
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and gives us a probabilistic probabilistic values okay so of course a is is going to be correct.
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And as we discussed, like machine learning models are trained using uh historic data
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and they rely on the algorithms to find the like statical relationship in the data
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and yes prediction as we talked it relies on the like probability
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and like they are generally accurate but they are based on the confidence store
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which basically as i said it basically a level of probability
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but in machine learning terms okay now next question is to enhance security
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which of the following steps should be taken to protect account keys for azure ai services okay
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so now you want to secure account keys for azure ai service okay
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so where do you store your account keys you store keys in plain text file on server
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so definitely by reading it i can say you should not store any type of credential
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or secrets into a plain text file
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that is definitely not going to be my answer then store
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account keys in public repository definitely not you don't want to publicize your account keys
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and because you want to secure it the question is asking things
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and you want to enhance the security next is store account keys in environment variable
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so that is also not sure because
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that can be read by others as well or they just write up
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if they read like they type as some commands to read the environment variable
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and it will be visible for me
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so definitely i don't want to do it last option is store keys in azure key vault
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which is the definitely right choice
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so azure key vault is the basically a cloud service for secondly storing
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and accessing secrets just like here we want to protect the account keys
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or anything you want to secure it we utilize azure key vault in azure
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if you want to any secure anything just like api keys password certificates
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or cryptographic keys
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and it also like i provide some additional information here you
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can read it from the like screen basically just more about the key vault okay
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so this way you can utilize our question
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and that's why i want to give more value in less time
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so i want to move to the next question
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so you want to index a collection of text documents
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and search them from mobile application okay so you basically want to index
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so you can would be easily able to search it
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and it's a collection of text document and you want to search them using a mobile application
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which services you should use to create the index you need to understand the two important keywords one is index
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and one is search basically you want to index it
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and search them for mobile application so basically this is and
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which service you want to create the index okay
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so this is the like main lines you need to remember from the question
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so azure ai service azure open ai service azure ai search
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and azure ai index service so index service like
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but there is no such thing like azure ai index service okay
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so this is just to confuse you okay and ai service
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and open ai service this is also like just to distract you uh
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because they like we are not utilizing anything model we just have to create an index for it
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so which is the perfect thing for the azure ai search
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which is used to index document for the search purposes okay
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so it will be helpful
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when you search it you will get uh like major ai search will be helped to index make the index and
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so you can search faster okay a data scientist has used
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azure machine learning to train a machine learning model how can you use the model in your application okay
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so you have already used assure machine learning
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and you have trained the model using that service now you want to use
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that model okay trained more like you already have a trained model you want to utilize it
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so how you can do it
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so first option is use assure machine learning to publish the model as a web service so
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that you need to know like azure machine learning can train
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the model as well as well as it can publish the model
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if you don't know it then you might get confused so like this probably is my
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going to be answer let's read other options as well so
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if you see one answer don't go with it just read all option
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because as i said you have to choose the best option maybe it is correct
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but other option maybe might more correct okay then you have
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to export the model as an azure ai service i don't think there is a need for
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that and you must build your application using the Azure Machine Learning Designer.
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So that is definitely not an like compulsion format.
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So I'm going to choose A.
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So yes, definitely this was the answer
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and you have after publishing the as it as a web
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service you can consume it using your application through its rest interface
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so that is also additional information i have already provided you
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so you just publish it as a web service and then consume using rest interface or ace apis okay
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okay next question is when configuring diagnostic logging for azure ai services
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which of the below actions are necessary define metrics to be collected define diagnostic settings
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and configure log destination definitely
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when we set up diagnostic logging you have to just enable the settings
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and you just provide okay where you want to like put your logs
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and there will be like multiple options available
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so definitely this is going to be my choice
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and last option is setup data export schedule
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so definitely b is my option and you just have to enable the diagnostic settings
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and like you have to select the types of the log
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okay apart from this log destination in the diagnostic setting you
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have to like choose what type of logs you want to collect okay is it performance metrics service specific metric
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or resource specific uh logs what type of log you want
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and you can choose the destination like azure monitor logs azure event hubs or azure storage for different purposes okay
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so like you have to configure the log destination last question is you built a board by using the
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so this is last question for this video i will make like more
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and more videos whatever is specific necessary for particularly for ai 102 exam
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so we are going to do a lot of questions
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and i am 100 sure all the questions are definitely going to help you
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and we will not repeat any question i will definitely try
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that that not a single question got repeated but
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and please let me know like how the session is going
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and how you guys are enjoying the video or not and
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so we will continue doing it and we will do like hundreds of questions okay
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so let's do last question of this session you built a bot by using microsoft bot framework sdk
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and start it on local computer okay
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so you already built a bot using a microsoft board framework sdk
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so you now you know like to build a bot you can utilize microsoft board framework sd
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so always try to learn from questions as well okay
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and you started it on local computer okay now you now
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want to validate the functionality of the board okay you want
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to basically test it what should you do before you connect
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to the board okay how you can um like before you connected how you can basically validate the functionality
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so you run the board framework emulator you run the board framework composer
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or you register the boat with the azure board service
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or you run the windows terminal so definitely
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if you want to like we know from real world also we want to basically emulate it
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so the best service and it is a very powerful service like bot framework emulator
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so my answer is going to be that
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and yes it's like correct answer which allow us to test
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and debug your bot locally so here
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because it is you started in local computer
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and you want to test locally then definitely you are going to utilize both framework accumulator
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so here in the keyword is like it's made using board framework sdk
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and it started on a local computer and you want to test the functionality
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or debug basically so for
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that board framework accumulator is the correct choice even like you may like by seeing the exam
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some may think okay some questions are like feel outdated or this is not considered into
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scope of exam but i am going to like we are going to cover every single question
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which is important for this exam we are not going to
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miss anything we want like good score as well okay
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and we are going to cover anything
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because not all the questions like same some questions you are
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definitely going to miss an exam it's not like you are going to know everything
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and you are going like a full out of full score okay
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so we have to like read all aspect of this ei
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102 exam okay we are not going to miss anything
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so i hope you enjoy this video i hope you sincerely prepare for ai 102 exam
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and i wish you all the best for uh your ai 102 exam
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and we are going to continue it with the lots of question
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and if you have any suggestion
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or feedback for me please let me know in the comment
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section make sure you subscribe the channel for the upcoming videos
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and like this video and share with your juniors and colleagues see you guys in the next one bye

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인기 동영상

이 비디오로 말하기 연습을 해야 하는 이유는?

이 영상은 AI 102 시험의 여러 연습 문제를 다루고 있어, 영어 학습자가 실제 기술 용어와 문맥을 이해하고 연습하는 데 매우 유용합니다. 특히, 강사는 초보자도 쉽게 이해할 수 있도록 설명을 하므로, 자연스러운 영어 습득에 도움이 됩니다. 영어 쉐도잉 기법을 활용하면 발음과 억양을 개선할 수 있으며, 반복해서 따라 함으로써 더 자신감 있는 말하기를 연습할 수 있습니다. 이런 맥락에서, shadowing siteshadowspeaks와 같은 자료를 활용해보는 것도 좋습니다.

문맥 속의 문법 및 표현

  • Computer Vision Client Library: 기술적 용어를 통해 전문적인 대화에 익숙해질 수 있습니다.
  • Analyze image description: 동사와 명사를 조합해 전문적인 문장을 구성하는 좋은 예입니다.
  • Visual features type: 다양한 시각적 요소를 나열하며, 이를 통해 타입 관련 어휘력을 확장할 수 있습니다.

이런 표현들을 실제 대화에서 활용할 수 있게 되면, 기술 관련 대화에서도 자신감을 가질 수 있습니다. 이러한 문법 구조를 반복적으로 연습함으로써, 영어의 유창성이 향상될 수 있습니다.

일반적인 발음 함정

비디오에서 등장하는 몇 가지 어려운 발음과 억양을 인지하는 것이 중요합니다. 예를 들어, analyzedescription 같은 단어는 발음하기에 까다로운 부분이 있습니다. 특히, 'analyze'는 음절 강세에 주의하여 정확하게 발음해야 하며, 'description' 또한 첫 음절에 강조를 두어야 자연스럽게 들린다는 점을 유의해야 합니다. 이러한 발음 연습은 유튜브 영어 공부와 같은 시청 자료를 통해 반복적으로 접하며 익힐 수 있습니다.

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.

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