AWS-Exam-Simulator / questions /AI-900-v2.json
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[
{
"question": ": The term used to describe solutions where AI agents participate in conversations with humans. Choose t he correct option.",
"options": [
"A. Machine Learning",
"B. Natural language processing",
"C. Conversational AI",
"D. All of the above"
],
"correct": "C. Conversational AI",
"explanation": "Explanation Conversational AI is the term used to d escribe solutions where AI agents participate in conversations with humans. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/get-started-ai-fundamentals/6- understand- conversational-ai",
"references": ""
},
{
"question": ": Bots can be the basis of AI solutions such as below applications. Choose the correct options.",
"options": [
"A. Customer support for products or services",
"B. Automatically translate spoken or written phrases between languages",
"C. Health care consultations and self-diagnosis",
"D. Home automation and personal digital assistants"
],
"correct": "",
"explanation": "Explanation Bots can be the basis of AI solutions f or: Customer support for products or services. Rese rvation systems for restaurants, airlines, cinemas, and other appointme nt based businesses. Health care consultations and self- diagnosis. Home automation and personal digital assistants. Referen ce Link: https://docs.microsoft.com/en-us/learn/mod ules/ get-started-ai- fundamentals/6-understand-conversational-ai",
"references": ""
},
{
"question": ": Most commonly, ___________ solutions use bots to ma nage dialogs with users.",
"options": [
"A. Conversational AI",
"B. Computer Vision",
"C. Custom Vision",
"D. Natural language processing Correct Answer: A"
],
"correct": "",
"explanation": "Explanation Most commonly, conversational AI soluti ons use bots to manage dialogs with users. Referenc e Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/6-understand-conversational -ai",
"references": ""
},
{
"question": ": User can use the following services to create conve rsational AI solutions on Microsoft Azure. Choose t he correct options.",
"options": [
"A. QnA Maker",
"B. Face API",
"C. Azure Bot Service",
"D. Text Translate"
],
"correct": "",
"explanation": "Explanation User can use QnA Maker & Azure Bot Serv ice service to create conversational AI solutions o n Microsoft Azure. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/get-started-ai-fundamentals/6- understand- conversational-ai",
"references": ""
},
{
"question": ": Which cognitive service enables you to quickly buil d a knowledge base of questions and answers that ca n form the basis of a dialog between a human and an AI agent?",
"options": [
"A. Azure Bot",
"B. QnA Maker",
"C. Texmaker",
"D. None of the above"
],
"correct": "B. QnA Maker",
"explanation": "Explanation QnA Maker cognitive service enables you to quickly build a knowledge base of questions and answers that can form the basis of a dialog between a human and an A I agent. Reference Link: https://docs.microsoft.com /en- us/learn/modules/get-started-ai-fundamentals/6-unde rstand-conversational-ai",
"references": ""
},
{
"question": "Which service provides a platform for creating, pub lishing, and managing bots?",
"options": [
"A. Azure Bot",
"B. QnA Maker",
"C. Texmaker",
"D. Azure ChatBot"
],
"correct": "A. Azure Bot",
"explanation": "Explanation Azure Bot service provides a platform f or creating, publishing, and managing bots. Referen ce Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/6-understand-conversational -ai",
"references": ""
},
{
"question": ": Developers can use the ____________ to create a bot and manage it with Azure Bot Service - integrating back- end services like QnA Maker and LUIS, and connecting to channels for web chat, email, Microsoft Teams, and others.",
"options": [
"A. ChatBot Framework",
"B. Bot Framework",
"C. QnA Maker framework",
"D. All of the above"
],
"correct": "B. Bot Framework",
"explanation": "Explanation Developers can use the Bot Framework to create a bot and manage it with Azure Bot Service - integrating back- end services like QnA Maker and LUIS, and connectin g to channels for web chat, email, Microsoft Teams, and others. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/6-understan d- conversational-ai",
"references": ""
},
{
"question": ": What all potential challenges risks are faced by an AI application developer? Choose the correct optio ns.",
"options": [
"A. Errors may cause harm",
"B. Solutions may work for everyone",
"C. Who's not liable for AI-driven decisions?",
"D. Data could be exposed"
],
"correct": "",
"explanation": "Explanation The following table shows some of the p otential challenges risks facing an AI application developer. Bias can affect results Errors may cause harm Data could be exposed Solutions may not work for everyone Users m ust trust a complex system Who's liable for AI-driven decisions ? Reference Link: https://docs.microsoft.com/en-us/ learn/ modules/get- started-ai-fundamentals/7-challenges-with-ai",
"references": ""
},
{
"question": ": Which Microsoft bot is built on Azure Bot Service a nd enables developers to quickly create conversatio nal AI solutions for health care?",
"options": [
"A. Microsoft healthManagement bot",
"B. Microsoft healthcare bot",
"C. Microsoft health bot",
"D. Microsoft healthCure bot"
],
"correct": "B. Microsoft healthcare bot",
"explanation": "Explanation The Microsoft healthcare bot is built o n Azure Bot Service and enables developers to quick ly create conversational AI solutions for health care. To see an example of the healthcare bot:https://www.microsoft.com/research/project/heal th-bot/ Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/6-understan d- conversational-ai",
"references": ""
},
{
"question": ": An autonomous vehicle experiences a system failure and causes a collision. Under which AI challenge th e following example is categorized.",
"options": [
"A. Data could be exposed",
"B. Bias can affect results",
"C. Errors may cause harm",
"D. Users must trust a complex system"
],
"correct": "C. Errors may cause harm",
"explanation": "Explanation Errors may cause harm - An autonomous v ehicle experiences a system failure and causes a collision Reference Link: https://docs.microsoft.com/en-us/learn/module s/get-started-ai-fundamentals/7-challenges-with-ai",
"references": ""
},
{
"question": ": The fraction of the cases classified as positive th at are actually positive (the number of true positi ves divided by the number of true positives plus false negatives). Cho ose the correct option.",
"options": [
"A. Precision",
"B. F1 Score",
"C. Accuracy",
"D. Recall"
],
"correct": "D. Recall",
"explanation": "Explanation Recall: The fraction of the cases class ified as positive that are actually positive (the n umber of true positives divided by the number of true positives plus false negatives). In other words, out of all the patients who actually have diabetes, how many did the model identify? Referenc e Link: https://docs.microsoft.com/en-us/learn/modu les/ create- classification-model-azure-machine-learning-designe r/evaluate-model",
"references": ""
},
{
"question": ": In the case of this binary classification model, th e predicted probability for a negative prediction i s a value between 0 and 1.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation In the case of this binary classificati on model, the predicted probability for a positive prediction is a value between 0 and 1. Reference Link: https://docs.micro soft.com/en-us/learn/modules/create-classification- model- azure- machine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": ROC stands for _______________.",
"options": [
"A. Receiver operating characteristic",
"B. Receiving operator characteristic",
"C. Retransmitting operator characteristic",
"D. None of the above"
],
"correct": "A. Receiver operating characteristic",
"explanation": "Explanation Explanation ROC stands for receiver operating chara cteristic. Reference Link: https://docs.microsoft.c om/en- us/learn/modules/create-classification-model-azure- machine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": If the pipeline does not include _________ and ____ ___ modules, go back to the Designer page and then re- open the inference pipeline.",
"options": [
"A. Web Service Output",
"B. Service Output Features",
"C. Web Service Input",
"D. Service Features Input"
],
"correct": "",
"explanation": "Explanation If the pipeline does not include Web Se rvice Input and Web Service Output modules, go back to the Designer page and then re-open the inference pipeline. Refer ence Link: https://docs.microsoft.com/en-us/learn/m odules/ create- classification-model-azure-machine-learning-designe r/inference-pipeline",
"references": ""
},
{
"question": ": Your inference pipeline predicts whether or not pat ients are at risk for diabetes based on their featu res.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Your inference pipeline predicts whethe r or not patients are at risk for diabetes based on their features. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-classification-model-azure-machi ne- learning- designer/inference-pipeline",
"references": ""
},
{
"question": ": In which classification model, the predicted probab ility for a positive prediction is a value between 0 and 1?",
"options": [
"A. Binary classification model",
"B. Nominal classification model",
"C. Multinominal classification model",
"D. Multi-class classification model"
],
"correct": "A. Binary classification model",
"explanation": "Explanation In the case of this binary classificati on model, the predicted probability for a positive prediction is a value between 0 and 1. Reference Link: https://docs.micro soft.com/en-us/learn/modules/create-classification- model- azure- machine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": You are using Azure Machine Learning designer to cr eate a training pipeline for a binary classificatio n model. You have added a dataset containing features and labels , a Two-Class Decision Forest module, and a Train M odel module. You plan to use Score Model and Evaluate Mo del modules to test the trained model with a subset of the dataset that was not used for training. Which addit ional kind of module should you add?",
"options": [
"A. Join Data",
"B. Split Data",
"C. Select Columns in Dataset",
"D. None of the above"
],
"correct": "B. Split Data",
"explanation": "Explanation Use a Split Data module to randomly spl it a dataset into training and validation subsets. Reference Link: https://docs.microsoft.com/en-us/learn/modules/crea te-classification-model-azure-machine-learning-desi gner/ inference- pipeline",
"references": ""
},
{
"question": ": You use an Azure Machine Learning designer pipeline to train and test a binary classification model. Y ou review the model's performance metrics in an Evaluate Model mo dule, and note that it has an AUC score of 0.3. Wha t can you conclude about the model?",
"options": [
"A. The model can explain 30% of the variance between true and predicted labels.",
"B. The model predicts accurately for 70% of test cas es.",
"C. The model performs worse than random guessing.",
"D. All of the above"
],
"correct": "C. The model performs worse than random guessing.",
"explanation": "Explanation An AUC of 0.5 is what you'd expect with random prediction of a binary model. Reference Lin k: https://docs.microsoft.com/en-us/learn/modules/crea te-classification-model-azure-machine-learning-desi gner/ inference- pipeline",
"references": ""
},
{
"question": ": A form of machine learning that is used to group si milar items into clusters based on their features. Choose the correct option.",
"options": [
"A. Time series forecasting",
"B. Clustering",
"C. Classification",
"D. Regression"
],
"correct": "",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": A researcher might take measurements of penguins, a nd group them based on similarities in their propor tions. Choose the correct option.",
"options": [
"A. Classification",
"B. Regression",
"C. Time series forecasting",
"D. Clustering"
],
"correct": "D. Clustering",
"explanation": "Explanation Clustering is a form of machine learnin g that is used to group similar items into clusters based on their features. For example, a researcher might take measurements o f penguins, and group them based on similarities in their proportions. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-clustering-model-azure-machine- learning- designer/introduction",
"references": ""
},
{
"question": ": Choose the metrics used for clustering from the fol lowing.",
"options": [
"A. Average Distance to Other Center",
"B. Number of Edges",
"C. Average Distance to Cluster Center D. Number of Points"
],
"correct": "",
"explanation": "Explanation The metrics used for clustering are as following: Average Distance to Other Center, Averag e Distance to Cluster Center, Number of Points, Maximal Distance to Cluster Center. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-clustering-model-azure-mach ine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": Evaluating a clustering model is made difficult by the fact that there are no previously known true va lues for the cluster assignments.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Evaluating a clustering model is made d ifficult by the fact that there are no previously k nown true values for the cluster assignments. Reference Link: https://docs.m icrosoft.com/en-us/learn/modules/create-clustering- model- azure- machine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": To create clustering models by using a drag and dro p visual interface, without needing to write any co de. Choose the correct option.",
"options": [
"A. Azure Machine Learning Studio",
"B. Azure Machine Learning designer",
"C. Microsoft Azure Machine Learning dashboard",
"D. None of the above",
"A. Average Distance to Other Center",
"B. Average Distance to Cluster Center",
"C. Number of Edges",
"D. Number of Points"
],
"correct": "A. Average Distance to Other Center",
"explanation": "Explanation Average Distance to Other Center: This indicates how close, on average, each point in the cluster is to the centroids of all other clusters. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/create - clustering-model- azure-machine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": It is an example of __________, in which you train a model to separate items into clusters based purel y on their characteristics, or features.",
"options": [
"A. Semi-supervised machine learning",
"B. Supervised machine learning",
"C. Unsupervised machine learning",
"D. All of the above"
],
"correct": "C. Unsupervised machine learning",
"explanation": "Explanation Clustering is an example of unsupervise d machine learning, in which you train a model to s eparate items into clusters based purely on their characteristics, or features. There is no previously known cluster valu e (or label) from which to train the model. Reference Link: https://docs.mi crosoft.com/en-us/learn/modules/create-clustering-m odel- azure-machine- learning-designer/introduction",
"references": ""
},
{
"question": ": You use Azure Machine Learning designer to create a training pipeline for a classification model. What must you do before deploying the model as a service?",
"options": [
"A. Create an inference pipeline from the training pi peline",
"B. Add an Evaluate Model module to the training pipe line",
"C. Clone the training pipeline with a different name",
"D. None of the above Correct Answer: A"
],
"correct": "",
"explanation": "Explanation You must create an inference pipeline t o deploy as a service. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-classification-model-azure- machine-learning-designer/inference-pipeline",
"references": ""
},
{
"question": ": You train an image classification model that achiev es less than satisfactory evaluation metrics. How m ight you improve it?",
"options": [
"A. Reduce the size of the images used to train the m odel.",
"B. Add a new label for \"unknown\" classes.",
"C. Add more images to the training set.",
"D. All of the above"
],
"correct": "C. Add more images to the training set.",
"explanation": "Explanation Generally, adding more images to the pr oject an retraining the model is likely to improve performance. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/classify-images-custom-vision/2-azure-i mage- classification",
"references": ""
},
{
"question": ": Which of the following results does an object detec tion model typically return for an image?",
"options": [
"A. A class label and probability score for the image",
"B. Bounding box coordinates that indicate the region of the image where all of the objects it",
"C. A class label, probability, and bounding box for each object in the image",
"D. None of the above"
],
"correct": "C. A class label, probability, and bounding box for each object in the image",
"explanation": "Explanation An object detection model predicts a cl ass label, probability, and bounding box for each o bject in the image. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/detect-objects-images-custom-vision/1a- what- is-object- detection/",
"references": ""
},
{
"question": ": You have published an image classification model. W hat information must you provide to developers who want to use it?",
"options": [
"A. Only the project ID.",
"B. The project ID, the model name, and the key and e ndpoint for the prediction resource",
"C. The project ID, iteration number, and the key and endpoint for the training resource.",
"D. None of the above"
],
"correct": "B. The project ID, the model name, and the key and e ndpoint for the prediction resource",
"explanation": "Explanation To use a published model, you need the project ID, the model name, and the key and endpoin t for the prediction resource. Reference Link: https://docs.microsoft.co m/en-us/learn/modules/classify-images-custom-vision /2- azure-image- classification",
"references": ""
},
{
"question": ": You can use the Custom Vision cognitive service to train an image classification model based on existi ng images.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Yes, you can use the Custom Vision cogn itive service to train an image classification mode l based on existing images. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/classify-images-custom-vision/2 - azure-image- classification",
"references": ""
},
{
"question": ": Which workload is used for identifying key infrastr ucture for major disaster preparation efforts?",
"options": [
"A. Image analysis",
"B. Image processing",
"C. Image classification",
"D. Image manipulation"
],
"correct": "C. Image classification",
"explanation": "Explanation Disaster investigation: identifying key infrastructure for major disaster preparation effo rts. For example, identifying bridges and roads in aerial images can help disaster relief teams plan ahead in regions th at are not well mapped. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/classify-images-custom-vision/1-introdu ction",
"references": ""
},
{
"question": ": You plan to use a set of images to train an object detection model, and then publish the model as a pr edictive service. You want to use a single Azure resource with the sa me key and endpoint for training and prediction. Wh at kind of Azure resource should you create?",
"options": [
"A. Cognitive Services",
"B. Custom Vision",
"C. Computer Vision",
"D. All of the above"
],
"correct": "A. Cognitive Services",
"explanation": "Explanation A cognitive services resource can be us ed for both training and prediction. Reference Link : https://docs.microsoft.com/en-us/learn/modules/dete ct-objects-images-custom-vision/1a-what-is-object- detection/",
"references": ""
},
{
"question": ": What percentage of class predictions did the model correctly identify? Choose the correct evaluation m etrics for given example.",
"options": [
"A. Precision",
"B. Mean Absolute Error(MAE)",
"C. Recall",
"D. Average Precision (AP)"
],
"correct": "C. Recall",
"explanation": "Explanation Recall identifies what percentage of cl ass predictions did the model correctly identify. R eference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/2-azure-image-classificat ion",
"references": ""
},
{
"question": ": The Computer Vision service can not generate thumbn ails.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation The Computer Vision service can generat e thumbnails like creating small versions of images . Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/2-image-analysis-azure",
"references": ""
},
{
"question": ": You want to use the Language service to determine t he key talking points in a text document. Which fea ture of the service should you use?",
"options": [
"A. Sentiment analysis",
"B. Key phrase extraction",
"C. Entity detection",
"D. All of the above"
],
"correct": "B. Key phrase extraction",
"explanation": "Explanation Key phrases can be used to identify the main talking points in a text document. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/3-exercise",
"references": ""
},
{
"question": ": You plan to build an application that uses the Spee ch service to transcribe audio recordings of phone calls into text, and then submits the transcribed text to the Text A nalytics service to extract key phrases. You want t o manage access and billing for the application services in a singl e Azure resource. Which type of Azure resource shou ld you create?",
"options": [
"A. Speech",
"B. Text Analytics",
"C. Cognitive Services",
"D. None of the above"
],
"correct": "C. Cognitive Services",
"explanation": "Explanation This resource would support both the Sp eech and Text Analytics services. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/1-introduction/",
"references": ""
},
{
"question": ": You can use NLP to build solutions that extracting _________ from text or speech, or that formulate __ _____ in natural language.",
"options": [
"A. Meaningful responses",
"B. Language meaning C. Meaningful requests",
"D. Semantic meaning"
],
"correct": "",
"explanation": "Explanation You can use NLP to build solutions that extracting semantic meaning from text or speech, o r that formulate meaningful responses in natural language. Reference Link: https://docs.microsoft.com/en-in/learn/modul es/ analyze-text- with-text-analytics-service/3-exercise",
"references": ""
},
{
"question": ": Which model converts the audio signal into phonemes ?",
"options": [
"A. An acoustic model",
"B. A Speech model",
"C. A language model",
"D. An object model"
],
"correct": "A. An acoustic model",
"explanation": "Explanation An acoustic model that converts the aud io signal into phonemes (representations of specifi c sounds). Reference Link: https://docs.microsoft.com/en-in/learn/module s/recognize-synthesize-speech/1-introduction/",
"references": ""
},
{
"question": ": Which model maps phonemes to words, usually using a statistical algorithm that predicts the most proba ble sequence of words based on the phonemes?",
"options": [
"A. An acoustic model",
"B. A Speech model",
"C. A language model",
"D. An object model"
],
"correct": "C. A language model",
"explanation": "Explanation A language model that maps phonemes to words, usually using a statistical algorithm that p redicts the most probable sequence of words based on the phonemes. R eference Link: https://docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/1-intr oduction/",
"references": ""
},
{
"question": "You want to use the Speech service to build an appl ication that reads incoming email message subjects aloud. Which API should you use?",
"options": [
"A. Speech-to-Text",
"B. Text-to-Speech",
"C. Translate",
"D. None of the above"
],
"correct": "B. Text-to-Speech",
"explanation": "Explanation The Text-to-Speech API converts text to audible speech. Reference Link: https:// docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/1-intr oduction/",
"references": ""
},
{
"question": ": When might you see NaN returned for a score in Lang uage Detection?",
"options": [
"A. When the score calculated by the service is outsi de the range of 0 to 1",
"B. When the predominant language in the text is mixe d with other languages",
"C. When the language is ambiguous",
"D. All of the above"
],
"correct": "C. When the language is ambiguous",
"explanation": "Explanation The service will return NaN when it can not determine the language in the provided text. Re ference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/3-exercise",
"references": ""
},
{
"question": ": Natural Language Processing (NLP) is a branch of ar tificial intelligence (AI) that deals with ______ & ________ language.",
"options": [
"A. Written",
"B. Spoken",
"C. Reading",
"D. Listening"
],
"correct": "",
"explanation": "Explanation Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that deals w ith written and spoken language. Reference Link: https://docs.microsoft.co m/en-in/learn/modules/analyze-text-with-text-analyt ics- service/3- exercise",
"references": ""
},
{
"question": ": What is concerned with taking the spoken word and c onverting it into data that can be processed - ofte n by transcribing it into a text representation?",
"options": [
"A. Speech recognition",
"B. Voice recognition",
"C. Text recognition",
"D. Object recognition"
],
"correct": "A. Speech recognition",
"explanation": "Explanation Speech recognition is concerned with ta king the spoken word and converting it into data th at can be processed - often by transcribing it into a text representation . Reference Link: https://docs.microsoft.com/en-in/ learn/ modules/recognize- synthesize-speech/1-introduction/",
"references": ""
},
{
"question": ": It is concerned with vocalizing data, usually by co nverting text to speech. Choose the correct option.",
"options": [
"A. Speech recognition",
"B. Speech synthesis",
"C. Speech translation",
"D. Speech analytics"
],
"correct": "B. Speech synthesis",
"explanation": "Explanation Speech synthesis is in many respects th e reverse of speech recognition. It is concerned wi th vocalizing data, usually by converting text to speech. Reference Lin k: https://docs.microsoft.com/en-in/learn/modules/r ecognize- synthesize- speech/1-introduction/",
"references": ""
},
{
"question": ": You use the Language service to perform sentiment a nalysis on a document, and a score of 0.99 is retur ned. What does this score indicate about the document sentime nt?",
"options": [
"A. The document is positive.",
"B. The document is neutral.",
"C. The document is negative. D. None of the above"
],
"correct": "A. The document is positive.",
"explanation": "Explanation Score values closer to 1 indicated a mo re positive sentiment where scores closer to 0 indi cated negative sentiment. Reference Link: https://docs.microsoft.c om/en-in/learn/modules/analyze-text-with-text-analy tics- service/3- exercise",
"references": ""
},
{
"question": ": We expect artificial intelligence (AI) solutions to accept vocal commands and provide spoken responses . To enable this kind of interaction, the AI system must suppor t two capabilities? Choose the correct options.",
"options": [
"A. Speech recognition",
"B. Speech synthesis",
"C. Speech analysis",
"D. All of the above"
],
"correct": "",
"explanation": "Explanation To enable this kind of interaction, the AI system must support two capabilities: Speech re cognition - the ability to detect and interpret spoken input. Speech synthe sis - the ability to generate spoken output. Refere nce Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/1-introduction/",
"references": ""
},
{
"question": ": An example of something a user might say, and which your application must interpret. Choose the correc t term.",
"options": [
"A. Entities",
"B. Intents",
"C. Utterances",
"D. Objects"
],
"correct": "C. Utterances",
"explanation": "Explanation An utterance is an example of something a user might say, and which your application must interpret. For example, when using a home automation system, a use r might use the following utterances.",
"references": ""
},
{
"question": ":You can control whether the short answer from the r esponse by using the __________ checkbox at the top of the test pane.",
"options": [
"A. Display short answer",
"B. Show short answer",
"C. Present short answer",
"D. None of the above"
],
"correct": "A. Display short answer",
"explanation": "Explanation You can control whether the short answe r from the response by using the Display short answ er checkbox at the top of the test pane. Reference Link: https://docs. microsoft.com/en-in/learn/modules/build-faq-chatbot -qna- maker-azure-bot- service/3-create-bot",
"references": ""
},
{
"question": ": The response includes a ________ as well as a more verbose _________.",
"options": [
"A. answer passage",
"B. question passage",
"C. long answer",
"D. short answer"
],
"correct": "",
"explanation": "Explanation The response includes a short answer as well as a more verbose answer passage. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/3-create- bot",
"references": ""
},
{
"question": ": The knowledge base provides a back-end service that client applications can use to answer questions th rough some sort of user interface.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation The knowledge base provides a back-end service that client applications can use to answer questions through some sort of user interface. Reference Link: https: //docs.microsoft.com/en-in/learn/modules/build-faq- chatbot- qna-maker- azure-bot-service/3-create-bot",
"references": ""
},
{
"question": ": To access the knowledge base, client applications r equire following. Choose the correct option.",
"options": [
"A. The knowledge base ID",
"B. The knowledge base Name",
"C. The knowledge base endpoint",
"D. The knowledge base authorization key"
],
"correct": "",
"explanation": "Explanation To access the knowledge base, client ap plications require: The knowledge base ID The knowl edge base endpoint The knowledge base authorization key Refer ence Link: https://docs.microsoft.com/en-in/learn/ modules/build-faq- chatbot-qna-maker-azure-bot-service/2-get-started-q na-bot",
"references": ""
},
{
"question": ": To make the knowledge base available to a bot, you must publish it as a service that can be accessed o ver _________.",
"options": [
"A. FTP",
"B. SFTP",
"C. HTTP",
"D. HTTPS"
],
"correct": "C. HTTP",
"explanation": "Explanation To make the knowledge base available to a bot, you must publish it as a service that can b e accessed over HTTP. Reference Link: https://docs.microsoft.com/en -in/learn/modules/build-faq-chatbot-qna-maker-azure -bot- service/3- create-bot",
"references": ""
},
{
"question": ": When your bot is ready to be delivered to users, yo u can connect it to multiple channels; making it po ssible for users to interact with it through web chat, email, Micros oft Teams, and other common communication media.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "",
"explanation": "Explanation When your bot is ready to be delivered to users, you can connect it to multiple channels; making it possible for users to interact with it through web chat, email, Microsoft Teams, and other common communication med ia. Reference Link: https://docs.microsoft.com/en-in/learn/module s/build-faq-chatbot-qna-maker-azure-bot-service/2-g et- started-qna-bot",
"references": ""
},
{
"question": ": The Read API returns a hierarchy of information inc luding",
"options": [
"A. Pages",
"B. Lines",
"C. Regions",
"D. Words"
],
"correct": "A. Pages",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You wish to develop an application which can read s treet signs. Which azure service do you deploy?",
"options": [
"A. Azure Computer Vision",
"B. Conversional Al",
"C. Azure Custom Vision",
"D. Machine Learning"
],
"correct": "C. Azure Custom Vision",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Which Azure services are used for LUIS?",
"options": [
"A. Cognitive service",
"B. Speech",
"C. Custom Al",
"D. Language Understanding"
],
"correct": "D. Language Understanding",
"explanation": "Explanation Explanation/Reference:",
"references": ""
},
{
"question": ": The information that we need to use to access Compu ter Vision service-",
"options": [
"A. IP address of host",
"B. Key",
"C. Endpoint",
"D. URL"
],
"correct": "B. Key",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Azure ML studio uses which type of datastores?",
"options": [
"A. Table",
"B. File",
"C. Blob",
"D. Queue"
],
"correct": "C. Blob",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": We are designing an Al solution to monitor meetings and want to know when facial expressions indicate people being angry or scared. Which cognitive service should we use?",
"options": [
"A. QnA Maker",
"B. Text Analytics",
"C. Speech-to-text",
"D. Face API"
],
"correct": "D. Face API",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ":The Root Mean Squared Error (RMSE) is based on the same units as the label.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You wish to translate a text in French into an audi ble from in English. Which Azure service can you us e?",
"options": [
"A. Speech recognition",
"B. Translator Text",
"C. Language Understanding",
"D. Cognitive service"
],
"correct": "B. Translator Text",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": is often the foundation for any AI system by which it is trained to make predictions.",
"options": [
"A. ML",
"B. AI",
"C. Analyst",
"D. Azure"
],
"correct": "A. ML",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You wish to monitor your business's revenue to be a lerted of sudden drops In revenue. Which Azure serv ice would you deploy?",
"options": [
"A. Azure Custom Vision",
"B. Azure Machine Learning designer",
"C. Azure Anomaly detector",
"D. Azure Computer Vision Correct Answer: C"
],
"correct": "",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You are building a machine learning model to determ ine a local cab price at a specific time of a day u sing historical data from a cab service database. This is an exampl e of-",
"options": [
"A. Linear",
"B. Regression",
"C. Supervised",
"D. UnSupervised"
],
"correct": "B. Regression",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": To generate thumbnails, Computer vision can only ch ange the aspect ratio to fit the target thumbnail dimensions.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": What is the maximum file size for the Read API?",
"options": [
"A. 2OMB",
"B. 5OMB",
"C. 30MB",
"D. 2GB",
"A. Use the Computer Vision service - Face cannot per form facial recognition",
"B. Use Face to retrieve age and emotional state for each person",
"C. Use Face to create a group containing multiple im ages of each named individual, and train a",
"D. None of the above"
],
"correct": "B. Use Face to retrieve age and emotional state for each person",
"explanation": "Explanation Creating a group that contains multiple images of named individuals enables you to train a facial recognition model. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/detect-analyze-faces/2-face-anal ysis- azure/",
"references": ""
},
{
"question": ": You want to extract text from images and then use t he Text Analytics service to analyze the text. You want developers to require only one key and endpoint to access all of your services. What kind of resource should you create in your Azure subscription?",
"options": [
"A. Computer Vision",
"B. Cognitive Services",
"C. Text Analytics",
"D. All of the above"
],
"correct": "B. Cognitive Services",
"explanation": "Explanation A Cognitive Services resource support b oth Computer Vision for text extraction, and Text A nalytics for text analysis. Reference Link: https://docs.microsoft.co m/en-us/learn/modules/read-text-computer-vision/2-o cr- azure/",
"references": ""
},
{
"question": ": You plan to use the Computer Vision service to read text in a large PDF document. Which API should you use?",
"options": [
"A. The Read API",
"B. The OCR API",
"C. The Recognize Text API",
"D. None of the above"
],
"correct": "A. The Read API",
"explanation": "Explanation Not only is the Read API better suited for larger images but it runs asynchronously so it will not block your application while it is running. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/read-t ext- computer- vision/2-ocr-azure/",
"references": ""
},
{
"question": ": The Computer Vision service can not moderate the co ntent.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation The Computer Vision service can moderat e the content, detecting images that contain adult content or depict violent, gory scenes. Reference Link: https://docs. microsoft.com/en-us/learn/modules/analyze-images- computer-vision/2- image-analysis-azure",
"references": ""
},
{
"question": ": You plan to use the Form Recognizer pre-built recei pt model. Which kind of Azure resource should you c reate?",
"options": [
"A. Computer Vision resource.",
"B. Form Recognizer or Cognitive Services resource",
"C. Only Form Recognizer resource",
"D. All of the above"
],
"correct": "B. Form Recognizer or Cognitive Services resource",
"explanation": "Explanation Both the Form Recognizer resource and C ognitive Services resource provide access to the Fo rm Recognizer service. Reference Link: https://docs.microsoft.com /en-us/learn/modules/analyze-receipts-form-recogniz er/2- receipts-azure/",
"references": ""
},
{
"question": ": You are using the Form Recognizer service to analyz e receipts that you have scanned into JPG format im ages. What is the maximum file size of JPG file you can submit to the pre-built receipt model?",
"options": [
"A. 2 MB",
"B. 200 MB",
"C. 50 MB D. None of the above"
],
"correct": "C. 50 MB D. None of the above",
"explanation": "Explanation The maximum file size for the pre-built receipt model is 50 MB. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/analyze-receipts-form-recognizer/2 -receipts-azure/",
"references": ""
},
{
"question": ": Speech patterns are analyzed in the audio to determ ine recognizable patterns that are mapped to words. To accomplish this feat, the software typically uses m ultiple types of models, such as below. Choose the correct options.",
"options": [
"A. An acoustic model",
"B. A Speech model",
"C. A language model",
"D. An object model"
],
"correct": "",
"explanation": "Explanation Speech patterns are analyzed in the aud io to determine recognizable patterns that are mapp ed to words. To accomplish this feat, the software typically uses m ultiple types of models, including: An acoustic mod el that converts the audio signal into phonemes (representations of spec ific sounds). A language model that maps phonemes t o words, usually using a statistical algorithm that predicts the mos t probable sequence of words based on the phonemes. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/1-introduction/",
"references": ""
},
{
"question": ": You are developing an application that must take En glish input from a microphone and generate a real-t ime text- based transcription in Hindi. Which service should you use?",
"options": [
"A. Translator Text",
"B. Speech",
"C. Text Analytics",
"D. None of the above"
],
"correct": "B. Speech",
"explanation": "Explanation The Speech service can translate from a udio sources to text. Reference Link: https:// docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/1-intr oduction/",
"references": ""
},
{
"question": ": The model that is used by the text -to-speech API, is based on the Universal Language Model that was t rained by Microsoft.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation The model that is used by the speech-to -text API, is based on the Universal Language Model that was trained by Microsoft. Reference Link: https://docs.microsof t.com/en-in/learn/modules/recognize-synthesize-spee ch/2- get-started- azure",
"references": ""
},
{
"question": ": You need to use the Translator Text service to tran slate email messages from Spanish into both English and French. What is the most efficient way to accomplish this g oal?",
"options": [
"A. Make a single call to the service; specifying a \" from\" language of \"es\", a \"to\" language of \"en\",",
"B. Make a single call to the service; specifying a \" from\" language of \"es\", and a \"to\" language of",
"C. Make two calls to the service; one with a \"from\" language of \"es\" and a \"to\" language of \"en\",",
"D. All of the above"
],
"correct": "A. Make a single call to the service; specifying a \" from\" language of \"es\", a \"to\" language of \"en\",",
"explanation": "Explanation You can specify a single \"from\" languag e and multiple \"to\" languages. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/1-introduction/",
"references": ""
},
{
"question": ": Real-time speech-to-text allows you to transcribe t ext in _______.",
"options": [
"A. Visual streams",
"B. Text streams",
"C. Audio streams",
"D. None of the above Correct Answer: C"
],
"correct": "",
"explanation": "Explanation Real-time speech-to-text allows you to transcribe text in audio streams. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/2-get-started-azure",
"references": ""
},
{
"question": ": The recognized words in Speech recognition are typi cally converted to text, which can be used for vari ous purposes. Choose the correct option.",
"options": [
"A. Providing closed captions for recorded or live vi deos",
"B. Creating a transcript of a phone call or meeting",
"C. Automated note dictation",
"D. None of the above"
],
"correct": "",
"explanation": "Explanation The recognized words are typically conv erted to text, which you can use for various purpos es, such as. Providing closed captions for recorded or live vide os Creating a transcript of a phone call or meeting Automated note dictation Determining intended user input for furth er processing Reference Link: https://docs.microsof t.com/en- in/learn/modules/recognize-synthesize-speech/1-intr oduction/",
"references": ""
},
{
"question": ": You need to provision an Azure resource that will b e used to author a new Language Understanding application. What kind of resource should you create?",
"options": [
"A. Text Analytics",
"B. Language Understanding",
"C. Cognitive Services",
"D. All of the above"
],
"correct": "B. Language Understanding",
"explanation": "Explanation To author a Language Understanding mode l, you need a Language Understanding resource. Reference Link: https://docs.microsoft.com/en-in/learn/modules/crea te-language-model-with-language-understanding/1- introduction/",
"references": ""
},
{
"question": ":You have published your Language Understanding appl ication. What information does a client application developer need to get predictions from it?",
"options": [
"A. The endpoint and key for the application's predic tion resource",
"B. The endpoint and key for the application's author ing resource",
"C. The Azure credentials of the user who published t he Language Understanding application",
"D. None of the above"
],
"correct": "A. The endpoint and key for the application's predic tion resource",
"explanation": "Explanation Client applications must connect to the endpoint of the prediction resource, specifying an associated authentication key. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/create-language-mod el- with-language- understanding/1-introduction/",
"references": ""
},
{
"question": ": It should be run in an asynchronous manner because the batch jobs are scheduled on a best-effort basis . Choose the correct option.",
"options": [
"A. Business Transcription",
"B. Real-time transcription",
"C. Phonetic transcription",
"D. Batch transcription"
],
"correct": "D. Batch transcription",
"explanation": "Explanation Batch transcription should be run in an asynchronous manner because the batch jobs are scheduled on a best- effort basis. Normally a job will start executing w ithin minutes of the request but there is no estima te for when a job changes into the running state. Reference Link: https://doc s.microsoft.com/en-in/learn/modules/recognize-synth esize- speech/2-get- started-azure",
"references": ""
},
{
"question": ": A speech synthesis solution typically requires the following information. Choose the correct option.",
"options": [
"A. The text to be spoken",
"B. The speech to be spoken",
"C. The voice to be used to vocalize the speech",
"D. All of the above"
],
"correct": "",
"explanation": "Explanation A speech synthesis solution typically r equires the following information: The text to be s poken. The voice to be used to vocalize the speech. Reference Link: https: //docs.microsoft.com/en-in/learn/modules/recognize- synthesize-speech/1- introduction/",
"references": ""
},
{
"question": ": You are authoring a Language Understanding applicat ion to support an international clock. You want use rs to be able to ask for the current time in a specified cit y, for example \"What is the time in London?\". What should you do?",
"options": [
"A. Define a \"city\" entity and a \"GetTime\" intent wit h utterances that indicate the city intent.",
"B. Create an intent for each city, each with an utte rance that asks for the time in that city.",
"C. Add the utterance \"What time is it in city\" to th e \"None\" intent.",
"D. None of the above"
],
"correct": "A. Define a \"city\" entity and a \"GetTime\" intent wit h utterances that indicate the city intent.",
"explanation": "Explanation The intent encapsulates the task (getti ng the time) and the entity specifies the item to w hich the intent is applied (the city). Reference Link: https://docs.microsoft. com/en-in/learn/modules/create-language-model-with- language- understanding/1-introduction/",
"references": ""
},
{
"question": ": For customer support scenarios, it's common to crea te a bot that can interpret and answer frequently a sked questions through a website chat window, email, or voice interface.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation For customer support scenarios, it's co mmon to create a bot that can interpret and answer frequently asked questions through a website chat window, email, or voice interface. Reference Link: https://docs.micro soft.com/ en- in/learn/modules/build-faq-chatbot-qna-maker-azure- bot-service/3-create-bot",
"references": ""
},
{
"question": ": You can use the ________ to create and host a bot t hat uses the knowledge base to answer user question s. A. Azure LUIS Service",
"options": [
"B. Azure QnA Maker Service",
"C. Azure Bot Service",
"D. None of the above"
],
"correct": "C. Azure Bot Service",
"explanation": "Explanation You can then use the Azure Bot Service to create and host a bot that uses the knowledge ba se to answer user questions. Reference Link: https://docs.microsoft.c om/en-in/learn/modules/build-faq-chatbot-qna-maker- azure- bot- service/3-create-bot",
"references": ""
},
{
"question": ": Your knowledge base is based on the details in the _______ and some __________.",
"options": [
"A. QnA Maker",
"B. pre-defined responses",
"C. Database",
"D. FAQ document"
],
"correct": "",
"explanation": "Explanation Your knowledge base is based on the det ails in the FAQ document and some pre-defined responses. Reference Link: https://docs.microsoft.com/en-in/learn/module s/build-faq-chatbot-qna-maker-azure-bot-service/3-c reate- bot",
"references": ""
},
{
"question": ": Once you create your bot, you can manage it in the Azure portal, where you can do the following. Choos e the correct options.",
"options": [
"A. Extend the bot's functionality by adding custom c ode",
"B. Test the bot in an interactive test interface.",
"C. Configure logging, analytics, and integration wit h other services.",
"D. All of the above"
],
"correct": "D. All of the above",
"explanation": "Explanation After creating your bot, you can manage it in the Azure portal, where you can: Extend the bot's functionality by adding custom code. Test the bot in an interactive test interface. Configure logging, analytics, and i ntegration with other services. Reference Link: https://docs.microsoft.co m/en-in/learn/modules/build-faq-chatbot-qna-maker-a zure- bot-service/2- get-started-qna-bot",
"references": ""
},
{
"question": ": You can always use the QnA Maker portal to edit the knowledge base to improve it, and republish it.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation You can always use the QnA Maker portal to edit the knowledge base to improve it, and repu blish it. Reference Link: https://docs.microsoft.com/en-in/learn/module s/build-faq-chatbot-qna-maker-azure-bot-service/3-c reate- bot",
"references": ""
},
{
"question": ": The _______ shows the full text in the FAQ document for the closest matched question, while the ______ is intelligently extracted from the passage.",
"options": [
"A. answer passage",
"B. long answer",
"C. short answer",
"D. question passage"
],
"correct": "",
"explanation": "Explanation The answer passage shows the full text in the FAQ document for the closest matched questio n, while the short answer is intelligently extrhttps://docs.microsoft. com/en-in/learn/modulacted from the passage. Refere nce Link: es/build- faq-chatbot-qna-maker-azure-bot-service/3-create-bo t",
"references": ""
},
{
"question": ": Predicting age of a person is an example of _______ __________.",
"options": [
"A. regression",
"B. classification",
"C. clustering",
"D. All of the above"
],
"correct": "",
"explanation": "Explanation Predicting age of a person is an exampl e of regression.",
"references": ""
},
{
"question": ": Below principles fall under the category of respons ible AI? Choose the correct options.",
"options": [
"A. Fairness",
"B. Reliability and safety",
"C. Excludeness",
"D. Inclusiveness"
],
"correct": "",
"explanation": "Explanation Fairness, Reliability and safety, Inclu siveness are the part of principles fall under the category of responsible AI. Reference Link: https://docs.microsoft.com/en-u s/learn/modules/get-started-ai-fundamentals/8-under stand- responsible-ai",
"references": ""
},
{
"question": ": An innocent person is convicted of a crime based on evidence from facial recognition. Under which AI challenge the following example is categorized.",
"options": [
"A. Solutions may not work for everyone",
"B. Who's liable for AI-driven decisions?",
"C. Users must trust a complex system",
"D. Errors may cause harm"
],
"correct": "B. Who's liable for AI-driven decisions?",
"explanation": "Explanation Who's liable for AI-driven decisions? - An innocent person is convicted of a crime based o n evidence from facial recognition ? who's responsible? Reference L ink: https://docs.microsoft.com/en-us/learn/modules /get- started-ai- fundamentals/7-challenges-with-ai",
"references": ""
},
{
"question": ": People should be accountable for AI systems. Which principle defines this requirement?",
"options": [
"A. Transparency",
"B. Accountability C. Inclusiveness",
"D. Fairness"
],
"correct": "B. Accountability C. Inclusiveness",
"explanation": "Explanation Accountability: People should be accoun table for AI systems. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/get-started-ai-fundamentals/8-unde rstand-responsible-ai",
"references": ""
},
{
"question": ": A loan-approval model discriminates by gender due t o bias in the data with which it was trained. Under which AI challenge the following example is categorized.",
"options": [
"A. Data could be exposed",
"B. Bias can affect results",
"C. Errors may cause harm",
"D. Users must trust a complex system"
],
"correct": "B. Bias can affect results",
"explanation": "Explanation Bias can affect results - A loan-approv al model discriminates by gender due to bias in the data with which it was trained Reference Link: https://docs.microsoft. com/en-us/learn/modules/get-started-ai-fundamentals /7- challenges-with- ai",
"references": ""
},
{
"question": ": AI systems should be understandable. Which principl e defines this requirement?",
"options": [
"A. Transparency",
"B. Accountability",
"C. Inclusiveness",
"D. Fairness"
],
"correct": "A. Transparency",
"explanation": "Explanation Transparency: AI systems should be unde rstandable. Users should be made fully aware of the purpose of the system, how it works, and what limitations may be e xpected. Reference Link: https://docs.microsoft.com /en- us/learn/modules/get-started-ai-fundamentals/8-unde rstand-responsible-ai",
"references": ""
},
{
"question": ":At Microsoft, AI software development is guided by a set of _______ principles.",
"options": [
"A. seven",
"B. Bsix",
"C. five",
"D. Four"
],
"correct": "B. Bsix",
"explanation": "Explanation At Microsoft, AI software development i s guided by a set of six principles. Reference Link : https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/8-understand-responsible-ai",
"references": ""
},
{
"question": ": AI systems should empower everyone and engage peopl e. Which principle defines this requirement?",
"options": [
"A. Transparency",
"B. Accountability",
"C. Inclusiveness",
"D. Fairness"
],
"correct": "C. Inclusiveness",
"explanation": "Explanation Inclusiveness: AI systems should empowe r everyone and engage people. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/8-understand-responsible-ai",
"references": ""
},
{
"question": ": Designers and developers of AI-based solution shoul d work within a framework of _______ and __________ that ensure the solution meets ethical and legal standar ds that are clearly defined.",
"options": [
"A. governance",
"B. organizational principles",
"C. protocols",
"D. Law"
],
"correct": "",
"explanation": "Explanation In Accountability, Designers and develo pers of AI-based solution should work within a fram ework of governance and organizational principles that ensur e the solution meets ethical and legal standards th at are clearly defined. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/8-understan d- responsible-ai",
"references": ""
},
{
"question": ": AI systems should perform unreliably and safely.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation AI systems should perform reliably and safely. Unreliability in these kinds of system can result in substantial risk to human life. Reference Link: https://docs.mi crosoft.com/en-us/learn/modules/get-started-ai- fundamentals/8- understand-responsible-ai",
"references": ""
},
{
"question": ": What is the function of Average Distance to Other C enter metric in clustering?",
"options": [
"A. This indicates how close, on average, each point in the cluster is to the centroids of all other",
"B. This indicates how close, on average, each point in the cluster is to the centroid of the cluster.",
"C. The number of points assigned to the cluster.",
"D. None of the above"
],
"correct": "A. This indicates how close, on average, each point in the cluster is to the centroids of all other",
"explanation": "Explanation Average Distance to Other Center: This indicates how close, on average, each point in the cluster is to the centroids of all other clusters. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/create - clustering-model- azure-machine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": You are using an Azure Machine Learning designer pi peline to train and test a K-Means clustering model . You want your model to assign items to one of three clusters . Which configuration property of the K-Means Clust ering module should you set to accomplish this?",
"options": [
"A. Set Number of Centroids to 3",
"B. Set Random number seed to 3",
"C. Set Iterations to 3",
"D. All of the above"
],
"correct": "",
"explanation": "Explanation To create K clusters, you must set the number of centroids to K. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-clustering-model-azure-mach ine-learning-designer/deploy-service",
"references": ""
},
{
"question": ": In clustering, this metric indicates how close, on average, each point in the cluster is to the centro id of the cluster. Choose the correct option.",
"options": [
"A. Average Distance to Other Center",
"B. Average Distance to Cluster Center",
"C. Number of Edges",
"D. Number of Points"
],
"correct": "B. Average Distance to Cluster Center",
"explanation": "Explanation Average Distance to Cluster Center: Thi s indicates how close, on average, each point in th e cluster is to the centroid of the cluster.",
"references": ""
},
{
"question": ": You can think of machine learning as a way of defin ing a function (let's call it f) that operates on o ne or more features of something (which we'll call x) to calcu late a predicted label (y).",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Mathematically, you can think of machin e learning as a way of defining a function (let's c all it f) that operates on one or more features of something (which we'll c all x) to calculate a predicted label (y) - like th is: f(x) = y Reference Link: https://docs.microsoft.com/en-us/learn/module s/use-automated-machine-learning/what-is-ml",
"references": ""
},
{
"question": ": Once you create and run a pipeline to train the clu stering model, you can create an _________ that use s the model to assign new data observations to clusters.",
"options": [
"A. Deployment pipeline B. Performance pipeline",
"C. Inference pipeline",
"D. All of the above"
],
"correct": "C. Inference pipeline",
"explanation": "Explanation After creating and running a pipeline t o train the clustering model, you can create an inf erence pipeline that uses the model to assign new data observations to cluste rs. Reference Link: https://docs.microsoft.com/en- us/learn/modules/create-clustering-model-azure-mach ine-learning-designer/inference-pipeline",
"references": ""
},
{
"question": ": You use Azure Machine Learning designer to create a training pipeline for a clustering model. Now you want to use the model in an inference pipeline. Which module sh ould you use to infer cluster predictions from the model?",
"options": [
"A. Score Model",
"B. Assign Data to Clusters",
"C. Train Clustering Model",
"D. None of the above"
],
"correct": "B. Assign Data to Clusters",
"explanation": "Explanation Use the Assign Data to Clusters module to generate cluster predictions from a trained clus tering model. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-clustering-model-azure-machine- learning- designer/deploy-service",
"references": ""
},
{
"question": ": The maximum of the distances between each point and the centroid of that point?s cluster. Choose the c orrect matrix of clustering.",
"options": [
"A. Maximal Distance to Cluster Center",
"B. Average Distance to Cluster Center",
"C. Number of Edges",
"D. Number of Points"
],
"correct": "A. Maximal Distance to Cluster Center",
"explanation": "Explanation Maximal Distance to Cluster Center: The maximum of the distances between each point and th e centroid of that point?s cluster. Reference Link: https://docs.micro soft.com/en-us/learn/modules/create-clustering-mode l-azure- machine- learning-designer/evaluate-model",
"references": ""
},
{
"question": ": Explain best model option in Automated ML can calcu late feature importance for the best model.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Explain best model: Selected - this opt ion causes automated machine learning to calculate feature importance for the best model; making it possible to determine the influence of each feature on the predicted lab el. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
"references": ""
},
{
"question": ": Operations that you run are called ___________ in A zure Machine Learning.",
"options": [
"A. Programs",
"B. Scripts",
"C. Experiments",
"D. Notebooks"
],
"correct": "C. Experiments",
"explanation": "Explanation Operations that you run are called expe riments in Azure Machine Learning. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
"references": ""
},
{
"question": ": In clustering, this metric indicates the number of points assigned to the cluster. Choose the correct option.",
"options": [
"A. Points count",
"B. Average points",
"C. Number of Edges",
"D. Number of Points"
],
"correct": "D. Number of Points",
"explanation": "Explanation Explanation Number of Points: The number of points assigned to the cluster. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-clustering-model-azure-mach ine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": Azure Machine Learning studio provides a more focus ed user interface for managing workspace resources to data scientists and Machine Learning operations engineer s.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation You can manage your workspace using the Azure portal, but for data scientists and Machine Learning operations engineers, Azure Machine Learning studio provides a more focused user interface for managin g workspace resources. Reference Link: https://docs.microsoft.c om/en-us/learn/modules/use-automated-machine-learni ng/ what-is-ml",
"references": ""
},
{
"question": ": It uses mathematics and statistics to create a mode l that can predict unknown values. Choose the corre ct option.",
"options": [
"A. Machine Learning",
"B. Deep Learning",
"C. Natural Language Processing",
"D. Computer Vision"
],
"correct": "A. Machine Learning",
"explanation": "Explanation Machine learning is a technique that us es mathematics and statistics to create a model tha t can predict unknown values. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/use-automated-machine-learning/ what-is-ml",
"references": ""
},
{
"question": ": This statistic in combination with the Average Dist ance to Cluster Center helps you determine the clus ters spread ?",
"options": [
"A. Maximal Distance to Cluster Center",
"B. Average Distance to Cluster Center",
"C. Number of Edges",
"D. Number of Points Correct Answer: A"
],
"correct": "",
"explanation": "Explanation Maximal Distance to Cluster Center stat istic in combination with the Average Distance to C luster Center helps you determine the cluster?s spread. Reference Link: https://docs.microsoft.com/en-us/learn/modules/cre ate- clustering- model-azure-machine-learning-designer/evaluate-mode l",
"references": ""
},
{
"question": ": Information is required to connect to your deployed service from a client application are REST endpoin t and __________. Choose the correct option.",
"options": [
"A. Primary Key for your service",
"B. Password for your service.",
"C. Token for your service.",
"D. All of the above"
],
"correct": "A. Primary Key for your service",
"explanation": "Explanation You need below information to connect t o your deployed service from a client application. The REST endpoint for your service the Primary Key for your service R eference Link: https://docs.microsoft.com/en-us/lea rn/ modules/use- automated-machine-learning/deploy-model",
"references": ""
},
{
"question": ": The specific operation that the f function performs on x to calculate y depends on a number of factors , including the type of model you're trying to create and the speci fic algorithm used to train the model.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation The specific operation that the f funct ion performs on x to calculate y depends on a numbe r of factors, including the type of model you're trying to create and the s pecific algorithm used to train the model. Addition ally in most cases, the data used to train the machine learning model requi res some pre-processing before model training can b e performed. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/use-automated-machine-learning/what-is- ml",
"references": ""
},
{
"question": "What is the function of Average Distance to Cluster Center metric in clustering?",
"options": [
"A. The maximum of the distances between each point a nd the centroid of that point?s cluster.",
"B. This indicates how close, on average, each point in the cluster is to the centroid of the cluster.",
"C. This indicates how close, on average, each point in the cluster is to the centroids of all other",
"D. All of the above"
],
"correct": "B. This indicates how close, on average, each point in the cluster is to the centroid of the cluster.",
"explanation": "Explanation Average Distance to Cluster Center: Thi s indicates how close, on average, each point in th e cluster is to the centroid of the cluster. Reference Link: https://do cs.microsoft.com/en-us/learn/modules/create-cluster ing- model-azure- machine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": You plan to use Face to detect human faces in an im age. How does the service indicate the location of the faces it detects?",
"options": [
"A. A pair of coordinates for each face, indicating t he center of the face",
"B. Two pairs of coordinates for each face, indicatin g the location of the eyes",
"C. A set of coordinates for each face, defining a re ctangular bounding box around the face",
"D. None of the above"
],
"correct": "C. A set of coordinates for each face, defining a re ctangular bounding box around the face",
"explanation": "Explanation The location of detected faces are indi cated by a coordinates for a rectangular bounding b ox. Reference Link: https://docs.microsoft.com/en-us/learn/modules/dete ct-analyze-faces/2-face-analysis-azure/",
"references": ""
},
{
"question": ": What is one aspect that may impair facial detection ?",
"options": [
"A. Smile expression",
"B. Extreme angles",
"C. Fast shutter speed",
"D. All of the above"
],
"correct": "B. Extreme angles",
"explanation": "Explanation Best results are obtained when the face s are full-frontal or as near as possible to full-f rontal Reference Link: https://docs.microsoft.com/en-us/learn/modules/dete ct-analyze-faces/2-face-analysis-azure/",
"references": ""
},
{
"question": ": You can use the Custom Vision cognitive service to train image classification models and deploy them a s services for applications to use.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation You can use the Custom Vision cognitive service to train image classification models and d eploy them as services for applications to use. Reference Link: h ttps://docs.microsoft.com/en-us/learn/modules/class ify- images-custom- vision/1a-overview-classification",
"references": ""
},
{
"question": ": Which workload is used for evaluating images from X -ray or MRI devices could quickly classify specific issues found as cancerous tumors, or many other medical conditio ns related to medical imaging diagnosis?",
"options": [
"A. Image analysis",
"B. Image processing",
"C. Image classification",
"D. Image manipulation"
],
"correct": "C. Image classification",
"explanation": "Explanation Medical diagnosis: evaluating images fr om X-ray or MRI devices could quickly classify spec ific issues found as cancerous tumors, or many other medical conditio ns related to medical imaging diagnosis. Reference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/1-introduction",
"references": ""
},
{
"question": ": Which programming languages are supported in Azure machine learning Designer?",
"options": [
"A. C#",
"B. Python",
"C. C++",
"D. C Programming Correct Answer: B"
],
"correct": "",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You wish to develop an application which can take v erbal commands. What Azure service should you provision?",
"options": [
"A. Translator Text",
"B. Analysis",
"C. Speech",
"D. Computer Vision"
],
"correct": "C. Speech",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": The Text-to-Speech Neural voices leverage Neural ne tworks resulting in a more robotic-sounding voice.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You have used the wrong language code in Text Analy tics. What sentiment analysis score should you expe ct?",
"options": [
"A. 0",
"B. 1",
"C. 3",
"D. 2"
],
"correct": "A. 0",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ":The OCR API in Azure Computer Vision service Is use d to scan newspapers and magazines.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Computer vision is the best Azure resource for dete cting, analyzing and working with Faces.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": What is the easiest method to define elements of yo ur LUIS model?",
"options": [
"A. ml.azure.ai",
"B. Cognitive service portal",
"C. LUIS portal",
"D. Writing code"
],
"correct": "C. LUIS portal",
"explanation": "Explanation Language Understanding (LUIS) A machine learning-based service to build natural language i nto apps, bots, and IoT devices. Quickly create enterprise-ready, c ustom models that continuously improve.",
"references": ""
},
{
"question": ": Which module should you use to provide a simple met ric to compare the performance of multiple training models?",
"options": [
"A. Evaluate Model",
"B. Score Model",
"C. Compare Model",
"D. Linear regression"
],
"correct": "",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Deploying an Al service that monitors people of cer tain ethnicity for closer inspection in a retail st ore Is a violation of Microsoft responsible Al principle?",
"options": [
"A. Accountability",
"B. Fairness",
"C. Transparency",
"D. Inclusiveness"
],
"correct": "D. Inclusiveness",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You use the Text Analytics service to perform senti ment analysis on a document, and a score of 0.99 Is returned. What does this score indicate about the document se ntiment?",
"options": [
"A. The document is neutral.",
"B. The document Is negative.",
"C. The document is positive.",
"D. None"
],
"correct": "C. The document is positive.",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": If you consider the concept of `Describing an Image ' of Computer Vision, which of the following are co rrect:",
"options": [
"A. Based on the image content, Computer Vision may r eturn multiple phrases",
"B. Each returned phrase will be associated with a co nfidence score",
"C. The phrases will be arranged in ascending order o f their confidence score",
"D. The phrases will be arranged in descending order of their confidence score",
"A.",
"B.",
"C.",
"D."
],
"correct": "D. The phrases will be arranged in descending order of their confidence score",
"explanation": "Explanation Project ID: The unique ID of the Custom Vision project you created to train the model. Ref erence Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/2-azure-image-classificat ion",
"references": ""
},
{
"question": ": The performance for the trained model is indicated by the following evaluation metrics in custom visio n service. Choose the correct option.",
"options": [
"A. Precision",
"B. Recall",
"C. Mean Absolute Error(MAE)",
"D. Average Precision (AP)"
],
"correct": "",
"explanation": "Explanation Explanation At the end of the training process in c ustom vision, the performance for the trained model is indicated by the following evaluation metrics: Precision, Recall, Av erage Precision (AP). Reference Link: https:// docs.microsoft.com/en- us/learn/modules/classify-images-custom-vision/2-az ure-image-classification",
"references": ""
},
{
"question": ": You plan to use the Custom Vision service to train an image classification model. You want to create a resource that can only be used for model training, and not for pr ediction. Which kind of resource should you create in your Azure subscription?",
"options": [
"A. Custom Vision",
"B. Cognitive Services",
"C. Computer Vision",
"D. None of the above"
],
"correct": "A. Custom Vision",
"explanation": "Explanation When you create a Custom Vision resourc e, you can specify whether it is to be used for tra ining, prediction, or both. Reference Link: https://docs.microsoft.com/en -us/learn/modules/classify-images-custom-vision/2-a zure- image- classification",
"references": ""
},
{
"question": ": The Computer Vision service can detect image color schemes.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation The Computer Vision service can detect image color schemes, specifically, identifying the dominant foreground, background, and overall colors in an im age. Reference Link: https://docs.microsoft.com/en- us/learn/modules/analyze-images-computer-vision/2-i mage-analysis-azure",
"references": ""
},
{
"question": ": Given example, the following restaurant review coul d be analyzed for sentiment. \"Our dining experience at this restaurant was one of the worst I've ever had. The service was slow, and the food was awful. I'll neve r eat at this establishment again.\"",
"options": [
"A. 0.5 B. 1",
"C. 0.1",
"D. 0.9"
],
"correct": "C. 0.1",
"explanation": "Explanation The score for the review might be close r to 0.1, indicating a negative sentiment. Referenc e Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": You can use the _________ capabilities of the Langu age service to summarize the main points for sentim ent analysis.",
"options": [
"A. Sentiment analysis",
"B. Language Understanding Intelligent Service (LUIS)",
"C. Text analytics",
"D. Key phrase extraction"
],
"correct": "D. Key phrase extraction",
"explanation": "Explanation You can use the key phrase extraction c apabilities of the Language service to summarize th e main points for sentiment analysis. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/analyze-text-with-t ext- analytics- service/2-get-started-azure",
"references": ""
},
{
"question": ": Sentiment scores that are close to the middle of th e range (0.5) are considered ___________ or ______________.",
"options": [
"A. Neutral",
"B. Negative",
"C. Positive",
"D. Indeterminate"
],
"correct": "",
"explanation": "Explanation Sentiment scores that are close to the middle of the range (0.5) are considered neutral or indeterminate.",
"references": ""
},
{
"question": ":Using the language service to analyze the text \":-) \", results in a value of unknown for the language n ame and the language identifier, and a score of NaN.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Using the service to analyze the text \" :-)\", results in a value of unknown for the languag e name and the language identifier, and a score of NaN. Reference Link: https://docs.microsoft.com/en-in/learn/module s/ analyze-text-with- text-analytics-service/2-get-started-azure",
"references": ""
},
{
"question": ": A sentiment score may be _______ is in the case whe re the wrong language code was used.",
"options": [
"A. 1",
"B. 0.5",
"C. 0",
"D. 0.9"
],
"correct": "B. 0.5",
"explanation": "Explanation A score may be 0.5 is in the case where the wrong language code was used. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": You can provide the Language service with unstructu red text and it will return a ________ in the text that it recognizes.",
"options": [
"A. List of objects",
"B. List of entities",
"C. List of files",
"D. List of phrases"
],
"correct": "B. List of entities",
"explanation": "Explanation You can provide the Language service wi th unstructured text and it will return a list of e ntities in the text that it recognizes. Reference Link: https://docs.microsoft. com/en-in/learn/modules/analyze-text-with-text-anal ytics- service/2-get- started-azure",
"references": ""
},
{
"question": ": The entity detection service supports _______ to he lp disambiguate entities by linking to a specific r eference.",
"options": [
"A. Entity linking",
"B. Entity relationship",
"C. Entity pairing",
"D. Entity listing"
],
"correct": "A. Entity linking",
"explanation": "Explanation The service also supports entity linkin g to help disambiguate entities by linking to a spe cific reference. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/analyze-text-with-text-analytics-servic e/2-get- started-azure",
"references": ""
},
{
"question": ": The text analytics capabilities in the Language ser vice can do the following for each sentence. Choose the correct option.",
"options": [
"A. Evaluate text",
"B. Return objects",
"C. Return sentiment scores",
"D. Return labels"
],
"correct": "",
"explanation": "Explanation The text analytics capabilities in the Language service can evaluate text and return senti ment scores and labels for each sentence. Reference Link: https://docs.mic rosoft.com/en-in/learn/modules/analyze-text-with-te xt- analytics- service/2-get-started-azure",
"references": ""
},
{
"question": ": For recognized entities, the Entity recognition ser vice returns a URL for a relevant _______ article.",
"options": [
"A. Google",
"B. Twitter",
"C. Wikipedia",
"D. All of the above"
],
"correct": "C. Wikipedia",
"explanation": "Explanation For recognized entities, the service re turns a URL for a relevant Wikipedia article. Refer ence Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": Microsoft Azure Cognitive Services includes the tex t analytics capabilities in the Language service, w hich provides some out-of-the-box NLP capabilities, including the identification of _________ in text, and the class ification of text based on ___________.",
"options": [
"A. Key phrases",
"B. Entities",
"C. Sentiment",
"D. Language"
],
"correct": "",
"explanation": "Explanation Microsoft Azure Cognitive Services incl udes the text analytics capabilities in the Languag e service, which provides some out-of-the-box NLP capabilities, incl uding the identification of key phrases in text, an d the classification of text based on sentiment. Reference Link: https://do cs.microsoft.com/en-in/learn/modules/analyze-text-w ith-text- analytics- service/3-exercise",
"references": ""
},
{
"question": ": The confidence score may be less than 1 as a result of the mixed language text.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation The confidence score may be less than 1 as a result of the mixed language text. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": The Universal Language Model that was trained by Mi crosoft is optimized for two scenarios. Choose the correct options.",
"options": [
"A. Typing",
"B. Conversational C. Transactional",
"D. Dictation"
],
"correct": "",
"explanation": "Explanation The model is optimized for two scenario s, conversational and dictation. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/2-get-started-azure",
"references": ""
},
{
"question": ": when using a home automation system, a user might u se the following term. Choose the correct option.",
"options": [
"A. Entities",
"B. Intents",
"C. Utterances",
"D. Objects"
],
"correct": "C. Utterances",
"explanation": "Explanation An utterance is an example of something a user might say, and which your application must interpret. For example, when using a home automation system, a use r might use the following utterances: \"Switch the f an on.\" \"Turn on the light.\"",
"references": ""
},
{
"question": ": The _________ is a cognitive service in Azure that enables you to quickly create a knowledge base, eit her by entering question and answer pairs or from an existing docum ent or web page.",
"options": [
"A. QnA Maker service",
"B. Bot service",
"C. LUIS service",
"D. None of the above"
],
"correct": "A. QnA Maker service",
"explanation": "Explanation The QnA Maker service is a cognitive se rvice in Azure that enables you to quickly create a knowledge base, either by entering question and answer pairs or fro m an existing document or web page. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/3-create- bot",
"references": ""
},
{
"question": ":Which option is available to create a knowledge bas e on QnA Maker portal?",
"options": [
"A. Initiate a knowledge base.",
"B. Create a knowledge base",
"C. Choose a knowledge base.",
"D. None of the above"
],
"correct": "B. Create a knowledge base",
"explanation": "Explanation In the QnA Maker portal, select Create a knowledge base to create a knowledge base. Refere nce Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/3-create- bot",
"references": ""
},
{
"question": ": If you have already provisioned a free-tier _______ __ resources, your quota may not allow you to creat e another one.",
"options": [
"A. Azure Cognitive Search",
"B. Azure search",
"C. Azure Inference Clsuter (AIC)",
"D. None of the above"
],
"correct": "A. Azure Cognitive Search",
"explanation": "Explanation If you have already provisioned a free- tier Azure Cognitive Search resources, your quota m ay not allow you to create another one. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/build-faq-chatbot-q na- maker-azure-bot- service/3-create-bot",
"references": ""
},
{
"question": ": A knowledge base that consists of question-and-answ er pairs as of following. Choose the correct option s.",
"options": [
"A. Generated from an existing FAQ document or web pa ge.",
"B. Imported from a pre-defined chit-chat data source .",
"C. Entered and edited manually.",
"D. None of the above"
],
"correct": "",
"explanation": "Explanation Once you provision a QnA Maker resource , you can use the QnA Maker portal to create a knowledge base that consists of question-and-answer pairs. These questi ons and answers can be: Generated from an existing FAQ document or web page. Imported from a pre-defined chit-chat dat a source. Entered and edited manually.",
"references": ""
},
{
"question": ": Which service provides a dedicated QnA Maker portal web-based interface that you can use to create, tr ain, publish, and manage knowledge bases?",
"options": [
"A. QnA Maker",
"B. Robots service",
"C. Bots service",
"D. LUIS service"
],
"correct": "",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Underlying the bot interface is a knowledge base of questions and appropriate answers that the bot can search for suitable responses.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Underlying the bot interface is a knowl edge base of questions and appropriate answers that the bot can search for suitable responses. Reference Link: https://doc s.microsoft.com/en-in/learn/modules/build-faq-chatb ot-qna- maker-azure- bot-service/3-create-bot",
"references": ""
},
{
"question": ": Which service to train a language model that can un derstand spoken or text-based commands?",
"options": [
"A. Speech",
"B. Language Understanding Intelligent Service (LUIS)",
"C. Translator Text",
"D. Text Analytics Correct Answer: B"
],
"correct": "",
"explanation": "Explanation Language Understanding Intelligent Serv ice (LUIS) service is used to train a language mode l that can understand spoken or text-based commands. Reference Link: https://docs.microsoft.com/en-us/learn/modul es/ get-started-ai- fundamentals/5-understand-natural-language-process",
"references": ""
},
{
"question": ": Language Understanding Intelligent Service (LUIS) s ervice is used to train a language model for below tasks. Choose the correct option.",
"options": [
"A. To understand spoken commands",
"B. To translate spoken languages",
"C. To understand text-based commands",
"D. To recognize and synthesize speech"
],
"correct": "",
"explanation": "Explanation Language Understanding Intelligent Serv ice (LUIS) service to train a language model that c an understand spoken or text-based commands. Reference Link: http s://docs.microsoft.com/en-us/learn/modules/get-star ted- ai- fundamentals/5-understand-natural-language-process",
"references": ""
},
{
"question": ": A relative metric between 0 and 1 based on the abso lute differences between predicted and true values.",
"options": [
"A. Relative Absolute Error (RAE)",
"B. Relative Squared Error (RSE)",
"C. Root Mean Squared Error (RMSE)",
"D. Mean Absolute Error (MAE)",
"A. Relative Absolute Error (RAE)",
"B. Relative Squared Error (RSE)",
"C. Root Mean Squared Error (RMSE)",
"D. Mean Absolute Error (MAE)"
],
"correct": "B. Relative Squared Error (RSE)",
"explanation": "Explanation Relative Squared Error (RSE): A relativ e metric between 0 and 1 based on the square of the differences between predicted and true values. The closer to 0 this metric is, the better the model is performing. Because this metric is relative, it can be used to compare models where th e labels are in different units. Reference Link: https://docs.microsoft.com/en-us/learn/modules/crea te-regression-model-azure-machine-learning-designer / evaluate-model",
"references": ""
},
{
"question": ": This metric summarizes how much of the variance bet ween predicted and true values is explained by the model. Choose the correct option.",
"options": [
"A. Coefficient of Determination (R2)",
"B. Relative Squared Error (RSE)",
"C. Root Mean Squared Error (RMSE)",
"D. Mean Absolute Error (MAE)"
],
"correct": "A. Coefficient of Determination (R2)",
"explanation": "Explanation Coefficient of Determination (R2): This metric is more commonly referred to as R-Squared, and summarizes how much of the variance between predicted and true values is explained by the model. Reference Link: https://docs.microsoft.com/en-us/learn/modules/crea te-regression-model-azure-machine-learning-designer / evaluate-model",
"references": ""
},
{
"question": ": The closer to 0 this metric is, the better the mode l is performing.",
"options": [
"A. Relative Absolute Error (RAE)",
"B. Relative Squared Error (RSE)",
"C. Root Mean Squared Error (RMSE)",
"D. Mean Absolute Error (MAE)"
],
"correct": "",
"explanation": "Explanation Relative Squared Error (RSE) & Relative Absolute Error (RAE) : The closer to 0 this metric is, the better the model is performing. Reference Link: https://docs.m icrosoft.com/en-us/learn/modules/create-regression- model- azure- machine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": The OCR API in Azure Computer Vision service Is use d to scan newspapers and magazines",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": The ability of a software agent to participate in a conversation is known as",
"options": [
"A. Natural Language processioning",
"B. Conversional Al",
"C. Text Analysis",
"D. Speech Recognition"
],
"correct": "B. Conversional Al",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Which Azure service would you deploy to detect a su dden spike in network traffic?",
"options": [
"A. Azure AutoML",
"B. Azure Conative services",
"C. Azure Anomaly detector",
"D. Azure machine learning",
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": The area of AI that deals with creating software th at understands written and spoken language. Choose the correct option.",
"options": [
"A. Conversational AI",
"B. Responsible AI",
"C. Natural language processing (NLP)",
"D. All of the above"
],
"correct": "C. Natural language processing (NLP)",
"explanation": "Explanation Natural language processing (NLP) is th e area of AI that deals with creating software that understands written and spoken language. Reference Link: https://docs.m icrosoft.com/en-us/learn/modules/get-started-ai- fundamentals/5- understand-natural-language-process",
"references": ""
},
{
"question": ": NLP enables you to create software that can do the following. Choose the correct options.",
"options": [
"A. Analyze and interpret text in documents, email me ssages, and other sources.",
"B. Reservation systems for restaurants, airlines, ci nemas, and other appointment based businesses.",
"C. Interpret spoken language, and synthesize speech responses.",
"D. Interpret commands and determine appropriate acti ons."
],
"correct": "",
"explanation": "Explanation NLP enables you to create software that can: Analyze and interpret text in documents, emai l messages, and other sources. Interpret spoken language, and synth esize speech responses. Automatically translate spo ken or written phrases between languages. Interpret commands and determine appropriate actions. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/get-started-ai-fundamentals/5-unde rstand-natural-language-process",
"references": ""
},
{
"question": ": In Starship Commander game, it uses ______________ to enable players to control the narrative and inte ract with in- game characters and starship systems.",
"options": [
"A. Conversational AI",
"B. Natural language processing (NLP)",
"C. Responsible AI",
"D. Chatbots"
],
"correct": "B. Natural language processing (NLP)",
"explanation": "Explanation Starship Commander, is a virtual realit y (VR) game from Human Interact, that takes place i n a science fiction world. The game uses natural language processing to enable players to control the narrative and intera ct with in-game characters and starship systems. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/get-st arted- ai- fundamentals/5-understand-natural-language-process",
"references": ""
},
{
"question": ": Text Analytics service is used to do the following. Choose the correct option.",
"options": [
"A. Extract key phrases",
"B. Detect entities",
"C. Evaluate sentiment",
"D. Translate spoken languages."
],
"correct": "",
"explanation": "Explanation Text Analytics service can be used to a nalyze text documents and extract key phrases, dete ct entities (such as places, dates, and people), and evaluate sentiment (how positive or negative a document is). Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
"references": ""
},
{
"question": ": Which service is used to analyze text documents and extract key phrases, detect entities, and evaluate sentiment?",
"options": [
"A. Text Analytics",
"B. Language Understanding Intelligent Service (LUIS) C. Speech",
"D. Translator Text"
],
"correct": "A. Text Analytics",
"explanation": "Explanation Text Analytics service is used to analy ze text documents and extract key phrases, detect e ntities (such as places, dates, and people), and evaluate sentiment (how pos itive or negative a document is). Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
"references": ""
},
{
"question": ": Which service is used to translate text between mor e than 60 languages?",
"options": [
"A. Language Understanding Intelligent Service (LUIS)",
"B. Text Analytics",
"C. Translator Text",
"D. Speech"
],
"correct": "C. Translator Text",
"explanation": "Explanation Translator Text service is used to tran slate text between more than 60 languages. Referenc e Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
"references": ""
},
{
"question": ": Speech service is used to recognize and ________ sp eech, and to _________ spoken languages.",
"options": [
"A. Synthesize",
"B. Analyze",
"C. Transcribe",
"D. Translate"
],
"correct": "",
"explanation": "Explanation Speech service is used to recognize and synthesize speech, and to translate spoken languag es. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
"references": ""
},
{
"question": ": Which service is used to recognize and synthesize s peech, and to translate spoken languages. A. Language Understanding Intelligent Service (LUIS)",
"options": [
"B. Speech",
"C. Translator Text",
"D. Text Analytics"
],
"correct": "B. Speech",
"explanation": "Explanation Speech service is used to recognize and synthesize speech, and to translate spoken languag es. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
"references": ""
},
{
"question": ": For production, you should create an inference clus ter, which provides an _______________ cluster that provides better scalability and security.",
"options": [
"A. Azure Kubernetes Service (AKS)",
"B. Azure Container Instance (ACI)",
"C. Azure Inference Clsuter (AIC)",
"D. Azure Compute Instance (ACI)"
],
"correct": "A. Azure Kubernetes Service (AKS)",
"explanation": "Explanation For production, you should create an in ference cluster, which provides an Azure Kubernetes Service (AKS) cluster that provides better scalability and securi ty. Reference Link: https://docs.microsoft.com/en-u s/learn/ modules/create- regression-model-azure-machine-learning-designer/in ference-pipeline",
"references": ""
},
{
"question": ": You are creating a training pipeline for a regressi on model, using a dataset that has multiple numeric columns in which the values are on different scales. You want to transform the numeric columns so that the values are all on a similar scale based relative to the minimum and max imum values in each column. Which module should you add to the pipeline?",
"options": [
"A. Select Columns in a Dataset",
"B. Normalize Data",
"C. Clean Missing Data",
"D. All of the above"
],
"correct": "",
"explanation": "Explanation When you need to transform numeric data to be on a similar scale, use a Normalize Data mod ule. Reference Link: https://docs.microsoft.com/en-us/learn/module s/create-regression-model-azure-machine-learning- designer/inference- pipeline",
"references": ""
},
{
"question": ": A form of machine learning that is used to predict which category, or class, an item belongs to. Choos e the correct option.",
"options": [
"A. Time series forecasting",
"B. Clustering",
"C. Classification",
"D. Regression"
],
"correct": "C. Classification",
"explanation": "Explanation Classification is a form of machine lea rning that is used to predict which category, or cl ass, an item belongs to. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-classification-model-azure-machi ne- learning- designer/introduction",
"references": ""
},
{
"question": ": Classification is an example of a __________ techni que in which you train a model using data that incl udes both the features and known values for the label, so that th e model learns to fit the feature combinations to t he label.",
"options": [
"A. Semi-supervised machine learning",
"B. Supervised machine learning",
"C. Unsupervised machine learning",
"D. All of the above"
],
"correct": "B. Supervised machine learning",
"explanation": "Explanation Classification is an example of a super vised machine learning technique in which you train a model using data that includes both the features and known values fo r the label, so that the model learns to fit the fe ature combinations to the label. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/create-classification-model-azur e- machine-learning- designer/introduction",
"references": ""
},
{
"question": ": You can use Microsoft ____________ to create classi fication models by using a drag and drop visual int erface, without needing to write any code.",
"options": [
"A. Azure Machine Learning Studio",
"B. Azure Machine Learning designer",
"C. Microsoft Azure Machine Learning dashboard",
"D. None of the above"
],
"correct": "B. Azure Machine Learning designer",
"explanation": "Explanation You can use Microsoft Azure Machine Lea rning designer to create classification models by u sing a drag and drop visual interface, without needing to write any code. Reference Link: https://docs.microsoft.com/e n- us/learn/modules/create-classification-model-azure- machine-learning-designer/introduction",
"references": ""
},
{
"question": ": The inference pipeline assumes that new data will m atch the schema of the original training data.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation The inference pipeline assumes that new data will match the schema of the original trainin g data. Reference Link: https://docs.microsoft.com/en-us/learn/module s/create-regression-model-azure-machine-learning- designer/inference- pipeline",
"references": ""
},
{
"question": ": What all are the metrics used in Classification pro blems? Choose the correct options.",
"options": [
"A. Accuracy",
"B. Call",
"C. Precision",
"D. Recall"
],
"correct": "",
"explanation": "Explanation Explanation Metrics used in Classification problems : Accuracy, Precision, Recall, F1 Score, AUC Refere nce Link: https://docs.microsoft.com/en-us/learn/modules/crea te-classification-model-azure-machine-learning-desi gner/ evaluate- model",
"references": ""
},
{
"question": ": Why do we split our data into training and validati on sets?",
"options": [
"A. Data is split into two sets in order to create tw o models, one model using the training set and a",
"B. Splitting data into two sets enables you to compa re the labels that the model predicts with the",
"C. We only need to split our data when we use the Az ure Machine Learning Designer, not in other",
"D. None of the above"
],
"correct": "B. Splitting data into two sets enables you to compa re the labels that the model predicts with the",
"explanation": "Explanation We want to test the model created with training data on validation data to see how well th e model performs with data it was not trained on. Reference Link: https:/ /docs.microsoft.com/en-us/learn/modules/create-regr ession- model-azure- machine-learning-designer/inference-pipeline",
"references": ""
},
{
"question": ": The ratio of correct predictions (true positives + true negatives) to the total number of predictions. Choose the correct option.",
"options": [
"A. F1 Score",
"B. Precision",
"C. Accuracy",
"D. Recall"
],
"correct": "C. Accuracy",
"explanation": "Explanation Accuracy: The ratio of correct predicti ons (true positives + true negatives) to the total number of predictions. In other words, what proportion of diabetes prediction s did the model get right? Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-classification-model-azure- machine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": The fraction of positive cases correctly identified (the number of true positives divided by the numbe r of true positives plus false positives). Choose the correct option. A. Precision",
"options": [
"B. Recall",
"C. F1 Score",
"D. Accuracy"
],
"correct": "",
"explanation": "Explanation Precision: The fraction of positive cas es correctly identified (the number of true positiv es divided by the number of true positives plus false positives). In other words, out of all the patients that the model predicted as having diabetes, how many are actually diabetic? Reference Link: https://docs.microsoft.com/en-us/learn/modul es/ create- classification-model-azure-machine-learning-designe r/evaluate-model",
"references": ""
},
{
"question": ": An overall metric that essentially combines _______ _ and _______ in classification problems.",
"options": [
"A. Precision",
"B. F1 Score",
"C. Accuracy",
"D. Recall"
],
"correct": "",
"explanation": "Explanation F1 Score: An overall metric that essent ially combines precision and recall. Reference Link : https://docs.microsoft.com/en-us/learn/modules/crea te-classification-model-azure-machine-learning-desi gner/ evaluate- model",
"references": ""
},
{
"question": ": A health clinic use the characteristics of a patien t such as age, weight, blood pressure to predict wh ether the patient is at risk of diabetes. Choose the correct option.",
"options": [
"A. Regression",
"B. Clustering",
"C. Classification",
"D. Time series forecasting"
],
"correct": "C. Classification",
"explanation": "Explanation Explanation Classification is a form of machine lea rning that is used to predict which category, or cl ass, an item belongs to. For example, a health clinic might use the characte ristics of a patient (such as age, weight, blood pr essure, and so on) to predict whether the patient is at risk of diabetes. In this case, the characteristics of the patient a re the features, and the label is a classification of either 0 or 1, representing non -diabetic or diabetic. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-classification-model-azure- machine-learning-designer/introduction",
"references": ""
},
{
"question": ": Average Precision (AP) is an overall metric that ta kes into account both precision and recall.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Average Precision (AP): An overall metr ic that takes into account both precision and recal l. Reference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/2-azure-image-classificat ion",
"references": ""
},
{
"question": ": What percentage of the class predictions made by th e model were correct? Choose the correct evaluation metrics for given example.",
"options": [
"A. Recall",
"B. Precision",
"C. Mean Absolute Error(MAE)",
"D. Average Precision (AP)"
],
"correct": "B. Precision",
"explanation": "Explanation Precision identifies What percentage of the class predictions made by the model were corre ct. Reference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/2-azure-image-classificat ion",
"references": ""
},
{
"question": ": To use your model, client application developers ne ed the following information in custom vision model . Choose the appropriate options.",
"options": [
"A. Project ID",
"B. Project Name",
"C. Model name D. Prediction endpoint"
],
"correct": "",
"explanation": "Explanation To use your model, client application d evelopers need the following information: Project I D, Prediction endpoint, Prediction key, Model name Reference Link : https://docs.microsoft.com/en-us/learn/modules/cl assify- images- custom-vision/2-azure-image-classification",
"references": ""
},
{
"question": ": Which workload is used for performing visual search es for specific products in online searches or even , in-store using a mobile device?",
"options": [
"A. Image analysis",
"B. Image processing",
"C. Image classification",
"D. Image manipulation"
],
"correct": "C. Image classification",
"explanation": "Explanation Product identification: performing visu al searches for specific products in online searche s or even, in-store using a mobile device. Reference Link: https://docs .microsoft.com/en-us/learn/modules/classify-images- custom-vision/1- introduction",
"references": ""
},
{
"question": ": Your organization has an existing frequently asked questions (FAQ) document. You need to create a QnA Maker knowledge base that includes the questions and answ ers from the FAQ with the least possible effort. Wh at should you do?",
"options": [
"A. Create an empty knowledge base, and then manually copy and paste the FAQ entries into it.",
"B. Import a pre-defined chit-chat data source.",
"C. Import the existing FAQ document into a new knowl edge base.",
"D. None",
"A. 1",
"B. 0.5",
"C. 0",
"D. None"
],
"correct": "B. 0.5",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Read API works best synchronously.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Classification is an example of __ machine learning .",
"options": [
"A. Supervised",
"B. Unsupervised",
"C. Linear",
"D. Regression"
],
"correct": "A. Supervised",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": An automobile dealership wants to use historic car sales data to train a machine learning model. The m odel should predict the price of a pre-owned car based on chara cteristics like its age, engine size, and mileage. What kind of machine learning model does the dealership need to create?",
"options": [
"A. Supervised",
"B. Regression C. Unsupervised",
"D. Linear"
],
"correct": "B. Regression C. Unsupervised",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You wish to upload your custom images for an image classification machine learning service you are cre ating. What options are available to you?",
"options": [
"A. Azure machine learning",
"B. Azure portal",
"C. Computer Vision",
"D. Custom Vision Portal"
],
"correct": "D. Custom Vision Portal",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": A model is developed to take medical images as inpu t and decide on whether tumor is benign or malignan t. This is an example of-",
"options": [
"A. Regression",
"B. Linear",
"C. Classification",
"D. Supervised"
],
"correct": "C. Classification",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": OCR API works best asynchronously.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Explanation/Reference:",
"references": ""
},
{
"question": ": Questions in the knowledge base can be assigned ___ _______ to help consolidate questions with the same meaning.",
"options": [
"A. None of the above",
"B. Prepositional phrasing",
"C. Alternative phrasing",
"D. Infinitive phrasing"
],
"correct": "C. Alternative phrasing",
"explanation": "Explanation Questions in the knowledge base can be assigned alternative phrasing to help consolidate questions with the same meaning. Reference Link: https://docs.microsof t.com/en-in/learn/modules/build-faq-chatbot-qna-mak er- azure-bot- service/2-get-started-qna-bot",
"references": ""
},
{
"question": ": User can use OCR to read text in __________ or to e xtract information from scanned documents such as _________, invoices, or forms.",
"options": [
"A. Files",
"B. Videos",
"C. Photographs",
"D. Letters"
],
"correct": "",
"explanation": "Explanation You can use OCR to read text in photogr aphs (for example, road signs or store fronts) or t o extract information from scanned documents such as letters, invoices, o r forms. Reference Link: https://docs.microsoft.com /en- us/learn/modules/get-started-ai-fundamentals/4-unde rstand-computer-vision",
"references": ""
},
{
"question": ": A sentiment score may be 0 is in the case where the wrong language code was used.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation A score may be 0.5 is in the case where the wrong language code was used. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": The square root of the mean squared difference betw een predicted and true values. Choose the correct o ption.",
"options": [
"A. Relative Mean Squared Error (RMSE)",
"B. Root Mean Squared Error (RMSE)",
"C. Root Mean Relative Error (RMRE)",
"D. Root Mean Absolute Error (RMAE)"
],
"correct": "B. Root Mean Squared Error (RMSE)",
"explanation": "Explanation Root Mean Squared Error (RMSE): The squ are root of the mean squared difference between predicted and true values. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/create-regression-model-azure- machine-learning- designer/evaluate-model",
"references": ""
},
{
"question": ": To train a regression model, you need a dataset tha t includes historical _________ and known _____ val ues.",
"options": [
"A. Objects",
"B. Label",
"C. Features",
"D. Numeric"
],
"correct": "",
"explanation": "Explanation To train a regression model, you need a dataset that includes historical features (charact eristics of the entity for which you want to make a prediction) and known labe l values (the numeric value that you want to train a model to predict). Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-regression-model-azure-machine- learning- designer/explore-data",
"references": ""
},
{
"question": ": In which machine learning technique the object bein g classified is an image, such as a photograph?",
"options": [
"A. Image Segmentation",
"B. Image Classification C. Object Detection",
"D. None of the above"
],
"correct": "B. Image Classification C. Object Detection",
"explanation": "Explanation Image classification is a machine learn ing technique in which the object being classified is an image, such as a photograph. Reference Link: https://docs.microsoft. com/en-us/learn/modules/classify-images-custom-visi on/1a- overview- classification",
"references": ""
},
{
"question": ": Microsoft Azure offers both __________ and ________ capabilities through the Speech cognitive service.",
"options": [
"A. Speech analytics",
"B. Speech recognition",
"C. Speech translation",
"D. Speech synthesis"
],
"correct": "",
"explanation": "Explanation Microsoft Azure offers both speech reco gnition and speech synthesis capabilities through t he Speech cognitive service. Reference Link: https://docs.microsoft.com /en-in/learn/modules/recognize-synthesize-speech/2- get- started-azure",
"references": ""
},
{
"question": ": A machine learning model could be trained by applyi ng an algorithm to these measurements that calculat es the most likely species of the flower. Choose the correct op tion for given example.",
"options": [
"A. Regression",
"B. None of the above",
"C. Classification",
"D. Clustering"
],
"correct": "C. Classification",
"explanation": "Explanation You can use a machine learning classifi cation technique to predict which category, or clas s, something belongs to. For example, the features of a flower might inc lude the measurements of its petals, stem, sepals, and other quantifiable characteristics. A machine learning model could be trained by applying an algorithm to these measureme nts that calculates the most likely species of the flower - its class. Reference Link: https://docs.microsoft.com/en-us/le arn/ modules/classify- images-custom-vision/1a-overview-classification",
"references": ""
},
{
"question": ": Paid subscription version of the Form Recognizer su pports up to _ pages and a maximum of _ lines per p age.",
"options": [
"A. 400 Pages",
"B. 100 Pages",
"C. 200 Pages",
"D. 300 Pages"
],
"correct": "A. 400 Pages",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": What type of compute resource do you need to deploy AKS in Azure Machine Learning?",
"options": [
"A. Inference Cluster",
"B. Compute Node",
"C. Compute Custer",
"D. Attachment Compute"
],
"correct": "B. Compute Node",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Which service is used to extract information from s canned forms and invoices?",
"options": [
"A. None of the above",
"B. Custom Vision",
"C. Form Recognizer",
"D. Optical character recognition ( OCR )",
"A. Custom Vision",
"B. Face",
"C. Face API",
"D. Computer Vision"
],
"correct": "B. Face",
"explanation": "Explanation The Face service enables you to build f ace detection and facial recognition solutions. Ref erence Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": The pipeline starts with the _______ from which you want to train the model.",
"options": [
"A. Entities",
"B. Features",
"C. Objects",
"D. Dataset"
],
"correct": "D. Dataset",
"explanation": "Explanation The pipeline starts with the dataset fr om which you want to train the model. Reference Lin k: https://docs.microsoft.com/en-us/learn/modules/crea te-regression-model-azure-machine-learning-designer / explore-data",
"references": ""
},
{
"question": ": The concept of evaluating the text of a document, o r documents, and then identifying the main talking points of the document(s). Choose the correct term.",
"options": [
"A. Key extraction",
"B. Phrase extraction",
"C. Text extraction",
"D. Key phrase extraction"
],
"correct": "D. Key phrase extraction",
"explanation": "Explanation Key phrase extraction is the concept of evaluating the text of a document, or documents, a nd then identifying the main talking points of the document(s). Referen ce Link: https://docs.microsoft.com/en-in/learn/mod ules/ analyze-text- with-text-analytics-service/2-get-started-azure",
"references": ""
},
{
"question": ": Machine learning models must be trained with existi ng data.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation Machine learning models must be trained with existing data. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/use-automated-machine-learning/dat a",
"references": ""
},
{
"question": ": Which targets are cloud-based resources on which yo u can run model training and data exploration proce sses?",
"options": [
"A. None of the above",
"B. Compute",
"C. Inference",
"D. Attached"
],
"correct": "B. Compute",
"explanation": "Explanation Compute targets are cloud-based resourc es on which you can run model training and data exploration processes. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-regression-model-azure-machine- learning- designer/create-compute",
"references": ""
},
{
"question": ": A specialized form of object detection that locates human faces in an image. Choose the correct option .",
"options": [
"A. Image analysis",
"B. Image classification",
"C. Semantic segmentation",
"D. Face detection"
],
"correct": "D. Face detection",
"explanation": "Explanation Face detection is a specialized form of object detection that locates human faces in an im age. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": A bank wants to use historic loan repayment records to categorize loan applications as low-risk or hig h-risk based on characteristics like the loan amount, the income of the borrower, and the loan period. What kind of ma chine learning model should the bank use automated machine learnin g to create?",
"options": [
"A. Classification",
"B. Time series forecasting",
"C. None of the above",
"D. Regression"
],
"correct": "A. Classification",
"explanation": "Explanation To predict a category, or class, use a classification model. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/use-automated-machine-learning/dat a",
"references": ""
},
{
"question": ": The ________________ will be the value returned, al ong with the language code. Choose the correct opti on.",
"options": [
"A. Predominant language",
"B. Expressive language",
"C. All of the above",
"D. Dominant language"
],
"correct": "A. Predominant language",
"explanation": "Explanation The predominant language will be the va lue returned, along with the language code. Referen ce Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": A score of 0.5 might indicate that the sentiment of the text is _________, and could result from text that does not have sufficient context to discern a sentiment or insuff icient phrasing.",
"options": [
"A. Neutral",
"B. Indeterminate",
"C. Positive D. Determinate"
],
"correct": "B. Indeterminate",
"explanation": "Explanation A score of 0.5 might indicate that the sentiment of the text is indeterminate, and could r esult from text that does not have sufficient context to discern a sentiment or insufficient phrasing. Reference Link: https:// docs.microsoft.com/en- in/learn/modules/analyze-text-with-text-analytics-s ervice/2-get-started-azure",
"references": ""
},
{
"question": ": A relative metric between 0 and 1 based on the squa re of the differences between predicted and true va lues. Choose the correct option.",
"options": [
"A. Root Mean Squared Error (RMSE)",
"B. Relative Absolute Error (RAE)",
"C. Mean Absolute Error (MAE)",
"D. Relative Squared Error (RSE)"
],
"correct": "D. Relative Squared Error (RSE)",
"explanation": "Explanation Relative Squared Error (RSE): A relativ e metric between 0 and 1 based on the square of the differences between predicted and true values. Reference Link: https://docs.microsoft.com/en-us/learn/modules/crea te- regression- model-azure-machine-learning-designer/evaluate-mode l",
"references": ""
},
{
"question": ": To use the Azure Machine Learning designer, you cre ate a ___________ that you will use to train a mach ine learning model.",
"options": [
"A. chain",
"B. pipeline",
"C. Roles",
"D. Experiments"
],
"correct": "B. pipeline",
"explanation": "Explanation To use the Azure Machine Learning desig ner, you create a pipeline that you will use to tra in a machine learning model. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/create-regression-model-azure- machine-learning- designer/explore-data",
"references": ""
},
{
"question": ": You wish to develop an application which can take v erbal commands. What Azure service should you provision?",
"options": [
"A. Azure Text Analytics",
"B. Speech",
"C. None of the above",
"D. LUIS"
],
"correct": "B. Speech",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": For each document submitted to it, the language ser vice will detect the below tasks. Choose the correc t options.",
"options": [
"A. The ISO 6391 language code (for example, \"en\")",
"B. The language name (for example \"English\")",
"C. A score indicating a level of confidence in the l anguage detection",
"D. Sentiments like positive or negative"
],
"correct": "",
"explanation": "Explanation For each document submitted to it, the language service will detect the following: The lan guage name (for example \"English\"). The ISO 6391 language code (for example, \"en\"). A score indicating a level of conf idence in the language detection. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/analyze-text-with-t ext- analytics- service/2-get-started-azure",
"references": ""
},
{
"question": ": User can create solutions that combine machine lear ning models to extract information from images, inc luding \"tags\" that could help catalog the image or even de scriptive captions that summarize the scene shown i n the image. Choose the correct option.",
"options": [
"A. Image classification",
"B. Image analysis",
"C. Semantic segmentation",
"D. Object detection Correct Answer: B"
],
"correct": "",
"explanation": "Explanation You can create solutions that combine m achine learning models with advanced image analysis techniques to extract information from images, including \"tags\" t hat could help catalog the image or even descriptiv e captions that summarize the scene shown in the image. Reference L ink: https://docs.microsoft.com/en-us/learn/modules /get- started-ai- fundamentals/4-understand-computer-vision",
"references": ""
},
{
"question": ": Given example, the following restaurant review coul d be analyzed for sentiment. \"We had dinner at this restaurant last night and the first thing I noticed was how co urteous the staff was. We were greeted in a friendl y manner and taken to our table right away. The table was clean, the chairs were comfortable, and the food was amaz ing.\"",
"options": [
"A. 0.9",
"B. 1",
"C. 0.5",
"D. 0"
],
"correct": "A. 0.9",
"explanation": "Explanation The sentiment score for the review migh t be around 0.9, indicating a positive sentiment. R eference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": A user support bot solution on Microsoft Azure is c reated using a combination of below two core techno logies?",
"options": [
"A. QnA Maker",
"B. Azure Bot Service",
"C. All of the above",
"D. Azure QnA Bot Service",
"A. Algorithm works better when we use data unchanged",
"B. It makes no difference. No risk involved",
"C. Smaller values in data may lead to higher bias",
"D. Larger values in data may lead to higher bias"
],
"correct": "D. Larger values in data may lead to higher bias",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": The language detection service will focus on the do minant language in the text.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation The language detection service will foc us on the predominant language in the text. Referen ce Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": If you consider the concept of `Describing an Image ' of Computer Vision, which of the following are co rrect:",
"options": [
"A. Ascending Order",
"B. Descending Order"
],
"correct": "B. Descending Order",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": The Face service enables you to build _________ and __________ solutions.",
"options": [
"A. None of the above",
"B. Face recognition",
"C. Face detection",
"D. Object detection Correct Answer: BC"
],
"correct": "",
"explanation": "Explanation The Face service enables you to build f ace detection and facial recognition solutions. Ref erence Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": Some potential uses for image classification includ e following things. Choose the correct options.",
"options": [
"A. Medical diagnosis",
"B. Disaster investigation",
"C. Face detection",
"D. Product identification"
],
"correct": "",
"explanation": "Explanation Some potential uses for image classific ation include: Product identification, Disaster inv estigation, Medical diagnosis Reference Link: https://docs.microsoft.co m/en-us/learn/modules/classify-images-custom-vision /1- introduction",
"references": ""
},
{
"question": ": Users can submit questions to the bot through any o f its channels, but can not receive an appropriate answer from the knowledge base on which the bot is based.",
"options": [
"A. FALSE",
"B. TRUE"
],
"correct": "A. FALSE",
"explanation": "Explanation Users can submit questions to the bot t hrough any of its channels, and receive an appropri ate answer from the knowledge base on which the bot is based. Reference Link: https://docs.microsoft.com/en-in/learn/modul es/ build-faq- chatbot-qna-maker-azure-bot-service/2-get-started-q na-bot",
"references": ""
},
{
"question": ": An item to which an utterance refers. For example, fan and light in the utterances. Choose the correct option.",
"options": [
"A. Intents B. Utterances",
"C. Entities",
"D. Objects"
],
"correct": "C. Entities",
"explanation": "Explanation An entity is an item to which an uttera nce refers. You can think of the fan and light enti ties as being specific instances of a general device entity. For example, fan and light in the following utterances: \"Switch the fan on.\" \"Turn on the light.\" Reference Link: https://docs.microsoft.com/ en-in/learn/modules/recognize-synthesize-speech/2-g et- started-azure",
"references": ""
},
{
"question": ": To create a knowledge base, you must first provisio n a _________ resource in your Azure subscription.",
"options": [
"A. QnA Maker",
"B. All of the above",
"C. Azure Bot Service",
"D. Azure QnA Bot Service"
],
"correct": "A. QnA Maker",
"explanation": "Explanation To create a knowledge base, you must fi rst provision a QnA Maker resource in your Azure subscription. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/build-faq-chatbot-qna-maker-azure-bot- service/2-get- started-qna-bot",
"references": ""
},
{
"question": ": A traffic monitoring solution might overlay traffic images with \"mask\" layers to highlight different v ehicles using specific colors. Choose the correct option.",
"options": [
"A. Object detection",
"B. Image classification",
"C. Image analysis",
"D. Semantic segmentation"
],
"correct": "D. Semantic segmentation",
"explanation": "Explanation Semantic segmentation is an advanced ma chine learning technique in which individual pixels in the image are classified according to the object to which they be long. For example, a traffic monitoring solution mi ght overlay traffic images with \"mask\" layers to highlight different ve hicles using specific colors. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": Choose the correct regression performance metrics f rom the following.",
"options": [
"A. Root Mean Squared Error (RMSE)",
"B. Mean Relative Error (MRE)",
"C. Mean Absolute Error (MAE)",
"D. Relative Squared Error (RSE)"
],
"correct": "",
"explanation": "Explanation Mean Absolute Error (MAE), Root Mean Sq uared Error (RMSE), Relative Absolute Error (RAE) a re the following regression performance metrics. Reference Link: https://docs.microsoft.com/en-us/learn/modul es/ create- regression-model-azure-machine-learning-designer/ev aluate-model",
"references": ""
},
{
"question": ": A common workload in (AI) applications which harnes ses the predictive power of machine learning to ena ble AI systems to identify real-world items based on image s. Choose the correct option.",
"options": [
"A. Image manipulation",
"B. Image classification",
"C. Image processing",
"D. Image analysis"
],
"correct": "B. Image classification",
"explanation": "Explanation Image classification is a common worklo ad in artificial intelligence (AI) applications. It harnesses the predictive power of machine learning to enable AI systems to i dentify real-world items based on images. Reference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/1-introduction",
"references": ""
},
{
"question": ": Which service is used to train custom image classif ication and object detection models using your own images?",
"options": [
"A. Computer Vision",
"B. None of the above",
"C. Face API",
"D. Custom Vision Correct Answer: D"
],
"correct": "",
"explanation": "Explanation Custom Vision is the service used to tr ain custom image classification and object detectio n models using your own images. Reference Link: https://docs.microsoft. com/en-us/learn/modules/get-started-ai-fundamentals /4- understand- computer-vision",
"references": ""
},
{
"question": ": Face detection can be combined with __________ and ___________ techniques to infer details such as age and emotional state; and even recognize individuals bas ed on their facial features. Choose the correct opt ion.",
"options": [
"A. Facial geometry analysis",
"B. Appearance geometry analysis",
"C. Classification",
"D. Regression"
],
"correct": "",
"explanation": "Explanation Face detection can be combined with cla ssification and facial geometry analysis techniques to infer details such as age and emotional state; and even recognize indi viduals based on their facial features. Reference L ink: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": Computer vision is the best Azure resource for dete cting, analyzing and working with Faces.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Once you provision a QnA Maker resource, you can us e the QnA Maker portal to create a ________ that consists of question-and-answer pairs.",
"options": [
"A. Dataset",
"B. Historical data",
"C. Database D. Knowledge base"
],
"correct": "",
"explanation": "Explanation After provisioning a QnA Maker resource , you can use the QnA Maker portal to create a know ledge base that consists of question-and-answer pairs. Reference Li nk: https://docs.microsoft.com/en-in/learn/modules/ build- faq-chatbot- qna-maker-azure-bot-service/2-get-started-qna-bot",
"references": ""
},
{
"question": ": In many cases, a knowledge base is created using a combination of all of these techniques; starting wi th a base dataset of questions and answers from an existing F AQ document, adding common conversational exchanges from a chit-chat source, and extending the knowledge base with additional manual entries.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation In many cases, a knowledge base is crea ted using a combination of all of these techniques; starting with a base dataset of questions and answers from an existing F AQ document, adding common conversational exchanges from a chit- chat source, and extending the knowledge base with additional manual entries. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/2-get-sta rted- qna-bot",
"references": ""
},
{
"question": ": Most modern image classification solutions are base d on ______ techniques that make use of __________ to uncover patterns in the pixels that correspond to particula r classes.",
"options": [
"A. Recurrent neural network (RNN)",
"B. Deep Learning",
"C. Convolutional neural networks (CNNs)",
"D. Machine Learning"
],
"correct": "",
"explanation": "Explanation Most modern image classification soluti ons are based on deep learning techniques that make use of convolutional neural networks (CNNs) to uncover pat terns in the pixels that correspond to particular c lasses. Training an effective CNN is a complex task that requires consi derable expertise in data science and machine learn ing. Reference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/1a-overview-classificatio n",
"references": ""
},
{
"question": ": A technique used to detect and read text in images. Choose the correct option.",
"options": [
"A. Intelligent Character Recognition ( ICR )",
"B. None of the above",
"C. Optical mark recognition ( OMR )",
"D. Optical character recognition ( OCR )"
],
"correct": "D. Optical character recognition ( OCR )",
"explanation": "Explanation Optical character recognition is a tech nique used to detect and read text in images. Refer ence Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": Image classification can be used for the following use cases",
"options": [
"A. Custom",
"B. Compute Node",
"C. Object Detection",
"D. Comupter Vision"
],
"correct": "C. Object Detection",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Performance metrics which calculates average differ ence between predicted values and true values. The lower this value is, the better the model is predicting. Choos e the correct option.",
"options": [
"A. Root Mean Squared Error (RMSE)",
"B. Mean Absolute Error (MAE)",
"C. Relative Squared Error (RSE)",
"D. Mean Relative Error (MRE)"
],
"correct": "B. Mean Absolute Error (MAE)",
"explanation": "Explanation The average difference between predicte d values and true values. This value is based on th e same units as the label. The lower this value is, the better the mode l is predicting. Reference Link: https://docs.micro soft.com/en- us/learn/modules/create-regression-model-azure-mach ine-learning-designer/evaluate-model",
"references": ""
},
{
"question": ": You want to train a model that classifies images of dogs and cats based on a collection of your own di gital photographs. Which Azure service should you use?",
"options": [
"A. Custom Vision",
"B. Computer Vision",
"C. Azure Machine Learning",
"D. Azure Bot Service"
],
"correct": "A. Custom Vision",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Common techniques used to train image classificatio n models have been encapsulated into the ________ cognitive service , making it easy to train a model and publi sh it as a software service with minimal knowledge of deep learning techniques.",
"options": [
"A. Image Segmentation",
"B. Custom Vision",
"C. Image classification",
"D. Object Detection"
],
"correct": "B. Custom Vision",
"explanation": "Explanation Common techniques used to train image c lassification models have been encapsulated into th e Custom Vision cognitive service in Microsoft Azure; making it eas y to train a model and publish it as a software ser vice with minimal knowledge of deep learning techniques. You can use the Custom Vision cognitive service to train image classification models and deploy them as services for applications to use.",
"references": ""
},
{
"question": ": You can use Microsoft Azure Machine Learning design er to create ___________ models by using a drag and drop visual interface, without needing to write any code .",
"options": [
"A. None of the above B. Regression",
"C. Classification",
"D. Time series forecasting"
],
"correct": "",
"explanation": "Explanation You can use Microsoft Azure Machine Lea rning designer to create regression models by using a drag and drop visual interface, without needing to write any code . Reference Link: https://docs.microsoft.com/en-us/ learn/ modules/create- regression-model-azure-machine-learning-designer/in troduction",
"references": ""
},
{
"question": ": The Computer Vision service can not detect image ty pes.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation The Computer Vision service can detect image types, for example, identifying clip art imag es or line drawings. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/analyze-images-computer-vision/2-image- analysis-azure",
"references": ""
},
{
"question": ": When RMSE compared to the MAE, a larger difference indicates greater variance in the individual errors .",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation When RMSE compared to the MAE, a larger difference indicates greater variance in the indiv idual errors. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-regression-model-azure-machine- learning- designer/evaluate-model",
"references": ""
},
{
"question": ": What is used to inform the service which language t he text is in? A. Language name",
"options": [
"B. Language code",
"C. All of the above",
"D. Language ID"
],
"correct": "B. Language code",
"explanation": "Explanation A language code (such as \"en\" for Engli sh, or \"fr\" for French) is used to inform the servi ce which language the text is in. Reference Link: https://docs.microsoft. com/en-in/learn/modules/analyze-text-with-text-anal ytics- service/2-get- started-azure",
"references": ""
},
{
"question": ": A list of words in a sentence that has no structure , could result in an _________ score.",
"options": [
"A. 0.1",
"B. Indeterminate",
"C. 0",
"D. 0.9"
],
"correct": "B. Indeterminate",
"explanation": "Explanation A list of words in a sentence that has no structure, could result in an indeterminate scor e. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": OCR API works best synchronously.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": It's common practice to train the model using a ___ ______, while holding back some data with which to test the trained model.",
"options": [
"A. Whole data B. Multiple datasets",
"C. All of the above",
"D. Subset of the data"
],
"correct": "D. Subset of the data",
"explanation": "Explanation It's common practice to train the model using a subset of the data, while holding back som e data with which to test the trained model. Reference Link: https://doc s.microsoft.com/en-us/learn/modules/create-regressi on- model-azure- machine-learning-designer/create-training-pipeline",
"references": ""
},
{
"question": ": You want to use the Text Analytics service to deter mine the key talking points in a text document. Whi ch feature of the service should you use?",
"options": [
"A. Key phrase extraction",
"B. Entity detection",
"C. None",
"D. Sentiment analysis"
],
"correct": "A. Key phrase extraction",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": An automobile dealership wants to use historic car sales data to train a machine learning model. The m odel should predict the price of a pre-owned car based on its m ake, model, engine size, and mileage. What kind of machine learning model should the dealership use automated machine learning to create?",
"options": [
"A. None of the above",
"B. Classification",
"C. Time series forecasting",
"D. Regression",
"A. Length of entities",
"B. Total amount of text for the language compared to other languages in the text",
"C. Length of phrases",
"D. Length of objects"
],
"correct": "D. Regression",
"explanation": "Explanation The language service uses an algorithm to determine the predominant language, such as leng th of phrases or total amount of text for the language compared to o ther languages in the text. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": If you pass text in French but tell the service the language code is en for English, the service will return a score of precisely _________.",
"options": [
"A. 0.1",
"B. 0.5",
"C. 0.9",
"D. Indeterminate"
],
"correct": "B. 0.5",
"explanation": "Explanation If you pass text in French but tell the service the language code is en for English, the s ervice will return a score of precisely 0.5. Reference Link: https://docs.micr osoft.com/en-in/learn/modules/analyze-text-with-tex t- analytics-service/2- get-started-azure",
"references": ""
},
{
"question": ": You want to use automated machine learning to train a regression model with the best possible R2 score . How should you configure the automated machine learning experi ment?",
"options": [
"A. Disable featurization",
"B. Enable featurization",
"C. Set the Primary metric to R2 score",
"D. Block all algorithms other than GradientBoosting"
],
"correct": "",
"explanation": "Explanation The primary metric determines the metri c used to evaluate the best performing model. Refer ence Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
"references": ""
},
{
"question": ": The simplest approach is to use a general Cognitive Services resource for both ______ and _________.",
"options": [
"A. Deployment",
"B. Training",
"C. Prediction",
"D. Processing"
],
"correct": "",
"explanation": "Explanation The simplest approach is to use a gener al Cognitive Services resource for both training an d prediction. This means you only need to concern yourself with one en dpoint (the HTTP address at which your service is h osted) and key (a secret value used by client applications to authent icate themselves). Reference Link: https:// docs.microsoft.com/en- us/learn/modules/classify-images-custom-vision/1a-o verview-classification",
"references": ""
},
{
"question": ": You are developing an application that must take En glish input from a microphone and generate a real-t ime text- based transcription in Hindi. Which service should you use?",
"options": [
"A. Text Analytics",
"B. Translator Text",
"C. QnA Maker",
"D. Speech"
],
"correct": "B. Translator Text",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Regression is an example of a ____________ machine learning technique in which you train a model using data that includes both the ____________ and known values for the label, so that the model learns to fit the fea ture combinations to the label. A. Features",
"options": [
"B. Supervised",
"C. Unsupervised",
"D. Entities"
],
"correct": "",
"explanation": "Explanation Regression is an example of a supervise d machine learning technique in which you train a m odel using data that includes both the features and known values for the label, so that the model learns to fit the feature combinations to the label. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-regression-model-azure-machine- learning- designer/introduction",
"references": ""
},
{
"question": ": What is the typical minimum number of Compute Clust er nodes recommended for training in a Production environment?",
"options": [
"A. 1",
"B. 2",
"C. 0",
"D. 3"
],
"correct": "B. 2",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": A process where you evaluate different aspects of a document or phrase, in order to gain insights into the content of that text.",
"options": [
"A. Analyzing objects",
"B. Analyzing Text",
"C. Analyzing entities",
"D. Synthesizing text",
"A. Azure Machine Learning",
"B. QnA Maker",
"C. Text Analytics",
"D. None of the above"
],
"correct": "A. Azure Machine Learning",
"explanation": "Explanation Azure Machine Learning enables you to t rain a predictive model from the existing data. Ref erence Link: https://docs.microsoft.com/en-us/learn/module s/get-started-ai-fundamentals/2-understand-machine- learn",
"references": ""
},
{
"question": ": Anomaly detector is stateful.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You need to deliver a support bot for internal use in your organization. Some users want to be able to submit questions to the bot using Microsoft Teams, others want to use a web chat interface on an internal web site. What should you do?",
"options": [
"A. None of the above",
"B. Create a knowledge base. Then create two bots tha t use the same knowledge base - one bot",
"C. Create a knowledge base. Then create a bot for th e knowledge base and connect the Web Chat and",
"D. Create two knowledge bases with the same question and answer pairs. Then create a bot for each"
],
"correct": "C. Create a knowledge base. Then create a bot for th e knowledge base and connect the Web Chat and",
"explanation": "Explanation The Microsoft Teams channel enables you r bot to receive and respond to messages in Microso ft Teams, and the Web Chat channel enables interaction s through a web chat interface. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/1-introdu ction/",
"references": ""
},
{
"question": ": To use the Computer Vision service, you need to cre ate a resource for it in your Azure subscription. C hoose the appropriate resource types from the following.",
"options": [
"A. Computer Vision",
"B. Advance Computer Vision",
"C. Custom Vision",
"D. Cognitive Services"
],
"correct": "",
"explanation": "Explanation To use the Computer Vision service, you need to create a resource for it in your Azure subscription. You can use either of the following resource types: Computer Vision, Cognitive Services Reference Link : https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/2-image-analysis-azure",
"references": ""
},
{
"question": ": A racing car telemetry system that uses sensors to proactively warn engineers about potential mechanic al failures before they happen. Choose the correct opt ion.",
"options": [
"A. Clustering",
"B. Regression",
"C. Classification",
"D. Anomaly detection"
],
"correct": "D. Anomaly detection",
"explanation": "Explanation By using anomaly detection - a machine learning based technique that analyzes data over ti me and identifies unusual changes.",
"references": ""
},
{
"question": ": Choose this resource type if you only plan to use N LP services, or want to manage access and billing f or the resource separately from other services.",
"options": [
"A. Language resource",
"B. Text analytics service",
"C. Language cognitive service",
"D. Text Language service"
],
"correct": "A. Language resource",
"explanation": "Explanation A Language resource - choose this resou rce type if you only plan to use natural language processing services, or if you want to manage access and billi ng for the resource separately from other services. Reference Link: https://docs.microsoft.com/en-in/learn/module s/analyze-text-with-text-analytics-service/2-get-st arted- azure",
"references": ""
},
{
"question": ": Conversations typically take the form of messages e xchanged in turns; and one of the most common kinds of _______ is a question followed by an answer.",
"options": [
"A. Transactional exchange",
"B. Conversational exchange",
"C. None of the above",
"D. Natural language exchange"
],
"correct": "B. Conversational exchange",
"explanation": "Explanation Conversations typically take the form o f messages exchanged in turns; and one of the most common kinds of conversational exchange is a questi on followed by an answer. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/1-introdu ction/",
"references": ""
},
{
"question": ": Define the sequence of steps performed by Azure Mac hine Learning. Choose the correct options from following.",
"options": [
"A. Prepare the data",
"B. Deploy a predictive service",
"C. None of the above",
"D. Train a model"
],
"correct": "",
"explanation": "Explanation Azure Machine Learning is a cloud-based service that helps simplify some of the tasks and reduce the time it takes to prepare data, train a model, a nd deploy a predictive service. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/what-is-ml",
"references": ""
},
{
"question": ": A cognitive service in Microsoft Azure that provide s pre-built computer vision capabilities. Choose th e correct option.",
"options": [
"A. Computer Vision service",
"B. Custom vision",
"C. All of the above D. Advance Computer Vision"
],
"correct": "A. Computer Vision service",
"explanation": "Explanation The Computer Vision service is a cognit ive service in Microsoft Azure that provides pre-bu ilt computer vision capabilities. The service can analy ze images, and return detailed information about an image and the objects it depicts. Reference Link: https:/ /docs.microsoft.com/en-us/learn/modules/analyze-ima ges- computer-vision/2-image-analysis-azure",
"references": ""
},
{
"question": ": Which algorithms can be used to normalize words bef ore counting them?",
"options": [
"A. Lemmatization",
"B. N-Grams",
"C. M-Grams",
"D. Stemming"
],
"correct": "",
"explanation": "Explanation Applying stemming or lemmatization algo rithms to normalize words before counting them - fo r example, so that words like \"power\", \"powered\", and \"powerful\" are interpreted as being the same word. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/analyze-text-with-text-analytics-servic e/1- introduction",
"references": ""
},
{
"question": ": Which compute resources are scalable clusters of vi rtual machines for on-demand processing of experime nt code?",
"options": [
"A. Kubernetes Clusters",
"B. Inference Clusters",
"C. Managed Cluster",
"D. Compute Clusters"
],
"correct": "D. Compute Clusters",
"explanation": "Explanation Compute Clusters: Scalable clusters of virtual machines for on-demand processing of experi ment code. Reference Link: https://docs.microsoft.com/en -us/learn/modules/use-automated-machine- learning/create-compute",
"references": ""
},
{
"question": ": In Microsoft Azure, the ________ service can help s implify application development by using pre-traine d models that can determine the language of a document or te xt",
"options": [
"A. Text Language service",
"B. Language API service",
"C. Language cognitive service",
"D. Text analytics service"
],
"correct": "C. Language cognitive service",
"explanation": "Explanation In Microsoft Azure, the Language cognit ive service can help simplify application developme nt by using pre-trained models that can determine the lan guage of a document or text. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
"references": ""
},
{
"question": ": Organizations are turning to artificial intelligenc e (AI) solutions that make use of AI agents, common ly known as _______ to provide a first-line of automated sup port through the full range of channels that we use to communicate.",
"options": [
"A. QnA section",
"B. Feedback section",
"C. About us",
"D. Bots"
],
"correct": "D. Bots",
"explanation": "Explanation Organizations are turning to artificial intelligence (AI) solutions that make use of AI ag ents, commonly known as bots to provide a first-line of a utomated support through the full range of channels that we use to communicate. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/build-faq-chatbot-q na- maker-azure-bot-service/1-introduction/",
"references": ""
},
{
"question": ": __ can be used for medical imaging diagnosis.",
"options": [
"A. Image Classification",
"B. Custom Vision",
"C. Cognitive Services",
"D. Computer Vision"
],
"correct": "A. Image Classification",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": "You can use the ___________ capabilities in the Lan guage service to detect the language for each of th e reviews from various applications.",
"options": [
"A. Language detection",
"B. Text Language",
"C. Language API",
"D. Text analytics"
],
"correct": "D. Text analytics",
"explanation": "Explanation You can use the text analytics capabili ties in the Language service to detect the language for each of these reviews; and it might respond with the follow ing results. Document Language ISO 6391 Code Score Review 1 English en 1.0 Review 2 Spanish es 1.0 Review 3 E nglish en 0.9 Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": Extending frequency analysis to multi-term phrases, commonly known as M-grams.",
"options": [
"A. FALSE",
"B. TRUE"
],
"correct": "A. FALSE",
"explanation": "Explanation Extending frequency analysis to multi-t erm phrases, commonly known as N-grams (a two-word phrase is a bi-gram, a three-word phrase is a tri-g ram, and so on). Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
"references": ""
},
{
"question": ": What Is the typical minimum number of Compute Clust er nodes recommended for training in a Production environment?",
"options": [
"A. 1",
"B. 3",
"C. 2",
"D. 0",
"A. None of the above",
"B. Azure Bot Service",
"C. Custom Vision",
"D. Computer Vision"
],
"correct": "C. Custom Vision",
"explanation": "Explanation Custom Vision enables you to train an i mage classification model based on your own images. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/4-understan d- computer-vision",
"references": ""
},
{
"question": ": You want to use the Text Analytics service to deter mine the key talking points in a text document. Whi ch feature of the service should you use?",
"options": [
"A. Key phrase extraction",
"B. Sentiment analysis",
"C. None",
"D. Entity detection"
],
"correct": "A. Key phrase extraction",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": This service can return what is known as bounding b ox coordinates in computer vision. Choose the corre ct option.",
"options": [
"A. Tagging visual features",
"B. Describing an image",
"C. Detecting brands",
"D. Object detection"
],
"correct": "D. Object detection",
"explanation": "Explanation The object detection capability is simi lar to tagging, in that the service can identify co mmon objects; but rather than tagging, or providing tags for the recognized objects only, this service can also retu rn what is known as bounding box coordinates. Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze- images-computer-vision/2-image-analysis-azure",
"references": ""
},
{
"question": ": A cloud service that you can use to train and manag e machine learning models. Choose the correct optio n.",
"options": [
"A. Azure Machine Learning",
"B. Azure Automated Learning",
"C. Azure AI Learning",
"D. Azure Deep Learning"
],
"correct": "A. Azure Machine Learning",
"explanation": "Explanation Azure Machine Learning is a cloud servi ce that you can use to train and manage machine lea rning models. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/use-automated-machine- learning/introduction",
"references": ""
},
{
"question": ": Which service is used to suggest class and bounding boxes you add to training set after an initial dat aset:",
"options": [
"A. Smart tagging",
"B. None",
"C. Auto-tagging",
"D. tag smart"
],
"correct": "D. tag smart",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Where do you manage the compute targets? Choose the correct option.",
"options": [
"A. Azure Machine Learning Designer",
"B. Azure Machine Learning Dashboard",
"C. Azure Machine Learning service",
"D. Azure Machine Learning studio",
"A. None of the above",
"B. Statistical analysis of terms used in the text.",
"C. Extending frequency analysis to multi-term phrase s, commonly known as N-grams",
"D. Applying stemming or lemmatization algorithms to normalize words before counting them"
],
"correct": "D. Azure Machine Learning studio",
"explanation": "Explanation There are some commonly used techniques that can be used to build software to analyze text , including: Statistical analysis of terms used in th e text. Extending frequency analysis to multi-term phrases, commonly known as N-grams. Applying stemming or lem matization algorithms to normalize words before counting them. Applying linguistic structure rules to analyze sentences. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
"references": ""
},
{
"question": ": Microsoft Azure provides the _______ service - a cl oud-based platform for creating, managing, and publ ishing machine learning models.",
"options": [
"A. Azure Machine Learning",
"B. Azure Deep Learning",
"C. Azure AI Learning",
"D. Azure Cognitive Learning"
],
"correct": "A. Azure Machine Learning",
"explanation": "Explanation Microsoft Azure provides the Azure Mach ine Learning service - a cloud-based platform for c reating, managing, and publishing machine learning models.",
"references": ""
},
{
"question": ": A technique that uses mathematics and statistics to create a model that can predict unknown values. Ch oose the correct option.",
"options": [
"A. Hadoop services",
"B. Deep learning",
"C. Machine learning",
"D. Congitive Learning"
],
"correct": "C. Machine learning",
"explanation": "Explanation Machine learning is a technique that us es mathematics and statistics to create a model tha t can predict unknown values. Reference Link: https://doc s.microsoft.com/en-us/learn/modules/use-automated- machine-learning/what-is-ml",
"references": ""
},
{
"question": ": You want to use the Speech service to build an appl ication that reads incoming email message subjects aloud. Which API should you use?",
"options": [
"A. Language detection",
"B. Language API",
"C. Text Language",
"D. Text-to-Speech"
],
"correct": "D. Text-to-Speech",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": To use the Speech service in an application, you mu st provision an appropriate resource. Choose the co rrect options.",
"options": [
"A. Speech recognition resource",
"B. A Cognitive Services resource",
"C. Speech synthesis resource",
"D. A Speech resource"
],
"correct": "",
"explanation": "Explanation To use the Speech service in an applica tion, you must provision an appropriate resource su ch as A Speech resource, A Cognitive Services resource. Ref erence Link: https://docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/2-get- started-azure",
"references": ""
},
{
"question": ": The Language service is a part of the Azure Cogniti ve Services offerings that can perform advanced ____________ over raw text.",
"options": [
"A. Language identification",
"B. Text Extraction",
"C. Computer Vision service",
"D. Natural language processing"
],
"correct": "D. Natural language processing",
"explanation": "Explanation The Language service is a part of the A zure Cognitive Services offerings that can perform advanced natural language processing over raw text. Referenc e Link: https://docs.microsoft.com/en- in/learn/modules/analyze-text-with-text-analytics-s ervice/2-get-started-azure",
"references": ""
},
{
"question": ": What are the compute resource you can create in Azu re ML Studio? Choose the correct options.",
"options": [
"A. Interface Clusters",
"B. Compute Clusters",
"C. Attached Cluster",
"D. Compute Instances"
],
"correct": "",
"explanation": "Explanation There are four kinds of compute resourc e you can create: Compute Instances, Attached Compu te, Compute Clusters, Inference Clusters Reference Link : https://docs.microsoft.com/en-us/learn/modules/us e- automated-machine-learning/create-compute",
"references": ""
},
{
"question": ": Whether a person is suffering from a particular dis ease or not can be termed as a ______________.",
"options": [
"A. clustering",
"B. classification",
"C. regression",
"D. All of the above"
],
"correct": "B. classification",
"explanation": "Explanation Whether a person is suffering from a di sease or Not can be termed as a classification prob lem.",
"references": ""
},
{
"question": ": What all details are required for creating a new Ma chine Learning resource? Choose the correct options .",
"options": [
"A. Resource group",
"B. Password vault",
"C. Subscription",
"D. Key vault"
],
"correct": "",
"explanation": "Explanation Subscription, Resource group, Key vault are required for creating a new Machine Learning resource. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/use-automated-machine-learning/create- workspace",
"references": ""
},
{
"question": ": What is the foundation for most AI solutions?",
"options": [
"A. Deep Learning",
"B. All of the above",
"C. Data Analysis",
"D. Machine Learning"
],
"correct": "D. Machine Learning",
"explanation": "Explanation Machine Learning is the foundation for most AI solutions",
"references": ""
},
{
"question": ": Your Azure subscription will never be charged any a mount for data storage as long as the Azure Machine Learning workspace exists in your subscription",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation Your Azure subscription will be charged a small amount for data storage as long as the Azu re Machine Learning workspace exists in your subscript ion. Reference Link: https://docs.microsoft.com/en- us/learn/modules/use-automated-machine-learning/cre ate-workspace",
"references": ""
},
{
"question": ": The free tier edition of Read API allows for _ page s, versus __ for the paid version",
"options": [
"A. 21000",
"B. 20000",
"C. 22,000",
"D. 23000",
"A. This application detects damage in your windshiel d. If the application detects a defect, have the",
"B. This application detects damage in any glass surf ace, but you must accept responsibility for using i t",
"C. When used in good lighting conditions, this appli cation can be used to identify potentially dangerou s",
"D. All of the above"
],
"correct": "C. When used in good lighting conditions, this appli cation can be used to identify potentially dangerou s",
"explanation": "Explanation You should be transparent about the lim itations of the application. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": Which programming languages are supported in Azure machine learning Designer?",
"options": [
"A. C#",
"B. R",
"C. Scala",
"D. Python"
],
"correct": "D. Python",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": A graphical interface enabling no-code development of machine learning solutions. Choose the correct o ption.",
"options": [
"A. Azure Machine Learning designer",
"B. Automated machine learning",
"C. ML Studio",
"D. Machine Learning Dashboard"
],
"correct": "A. Azure Machine Learning designer",
"explanation": "Explanation Azure Machine Learning designer is a gr aphical interface enabling no-code development of machine learning solutions.",
"references": ""
},
{
"question": ": Which Azure service is best for detecting popular b rand logos?",
"options": [
"A. Computer Vision",
"B. Object Detection",
"C. Azure Portal",
"D. Custom Vision"
],
"correct": "A. Computer Vision",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Identify people or objects, such as cars, in a spac e and map their movement within that space. Choose the correct option.",
"options": [
"A. Non-Spatial Analysis",
"B. None of the above",
"C. Temporal Analysis",
"D. Spatial Analysis"
],
"correct": "D. Spatial Analysis",
"explanation": "Explanation Spatial Analysis: Identify people or ob jects, such as cars, in a space and map their movem ent within that space. Reference Link: https://docs.microsoft. com/en-us/learn/modules/analyze-images-computer- vision/1-introduction",
"references": ""
},
{
"question": ": An image is an array of pixel values which can be u sed as _________ to train machine learning models t hat make predictions about the image and its contents.",
"options": [
"A. Entities",
"B. Objects",
"C. Hyperparameters",
"D. Features"
],
"correct": "D. Features",
"explanation": "Explanation An image is just an array of pixel valu es. These numeric values can be used as features to train machine learning models that make predictions about the image and its contents. Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/1-introduction",
"references": ""
},
{
"question": ": Bots typically manage conversation flows using a co mbination of _________ and ____________ responses that guide the user to a resolution.",
"options": [
"A. Restricted option",
"B. English language",
"C. Constrained option",
"D. Natural language"
],
"correct": "",
"explanation": "Explanation Regardless of the channel used, bots ty pically manage conversation flows using a combinati on of natural language and constrained option responses t hat guide the user to a resolution. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/1-introdu ction/",
"references": ""
},
{
"question": ": The free tier edition of Read API allows for____ pa ges, versus ____for the paid version",
"options": [
"A. 2-2,000",
"B. 2-10,000",
"C. 20 -Unlimited",
"D. 20-30,000"
],
"correct": "A. 2-2,000",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": If you create a Cognitive Services resource, client applications need different keys and endpoint for different service they use.",
"options": [
"A. FALSE",
"B. TRUE",
"A. Casual",
"B. Conversational",
"C. Transactional",
"D. Chatty"
],
"correct": "B. Conversational",
"explanation": "Explanation Bots are designed to interact with user s in a conversational manner. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/1-introdu ction/",
"references": ""
},
{
"question": ": You can submit only single document at a time for a nalysis.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation You can submit multiple documents at a time for analysis. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": Some potential uses for computer vision include fol lowing aspects. Choose the correct option.",
"options": [
"A. Spatial Analysis",
"B. Text Extraction",
"C. Content creation",
"D. Content Organization"
],
"correct": "",
"explanation": "Explanation Some potential uses for computer vision include: Content Organization, Text Extraction, Sp atial Analysis. Reference Link: https://docs.microsoft.co m/en-us/learn/modules/analyze-images-computer-visio n/1- introduction",
"references": ""
},
{
"question": ":Which feature enables non-experts to quickly create an effective machine learning model from data?",
"options": [
"A. ML Studio",
"B. Automated machine learning",
"C. Machine Learning Dashboard",
"D. Azure Machine Learning designer"
],
"correct": "B. Automated machine learning",
"explanation": "Explanation Automated machine learning feature enab les non-experts to quickly create an effective mach ine learning model from data.",
"references": ""
},
{
"question": ": AI algorithms that detect, recognize, and analyze h uman faces in images. Choose the correct option.",
"options": [
"A. Image analysis",
"B. Object Detection",
"C. All of the above",
"D. Face service"
],
"correct": "D. Face service",
"explanation": "Explanation The Azure Face service provides AI algo rithms that detect, recognize, and analyze human fa ces in images. Reference Link: https://docs.microsoft.com/ en-us/azure/cognitive-services/face/overview",
"references": ""
},
{
"question": ": Azure Machine Learning provides the following featu res. Choose the correct option.",
"options": [
"A. Automated machine learning",
"B. Azure Machine Learning designer",
"C. Analytical Machine Learning",
"D. Data and compute management"
],
"correct": "",
"explanation": "Explanation Azure Machine Learning provides the fol lowing features and capabilities:Automated machine learning, Azure Machine Learning designer, Data and compute management, Pipelines",
"references": ""
},
{
"question": ": Which compute resources are deployment targets for predictive services that use your trained model? A. Compute Instances",
"options": [
"B. Inference Clusters",
"C. Compute Clusters",
"D. Attached Compute"
],
"correct": "B. Inference Clusters",
"explanation": "Explanation Inference Clusters: Deployment targets for predictive services that use your trained model s. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/use-automated-machine-learning/create- compute",
"references": ""
},
{
"question": ": Which intent is a required intent and can't be dele ted or renamed?",
"options": [
"A. None intent",
"B. TurnOff intent",
"C. TurnOn intent",
"D. Greeting intent"
],
"correct": "A. None intent",
"explanation": "Explanation In a Language Understanding application , the None intent is created but left empty on purp ose. The None intent is a required intent and can't be delet ed or renamed. Fill it with utterances that are out side of your domain. Reference Link: https://docs.microsoft.com/ en-in/learn/modules/recognize-synthesize-speech/2-g et- started-azure",
"references": ""
},
{
"question": ": To use Azure Machine Learning, you create _________ __ in your Azure subscription. Choose the correct option.",
"options": [
"A. a workarea",
"B. a workground",
"C. a playground",
"D. a workspace",
"A. Create an empty knowledge base, and then manually copy and paste the FAQ entries into it.",
"B. Import a pre-defined chit-chat data source.",
"C. Import the existing FAQ document into a new knowl edge base.",
"D. None of the above"
],
"correct": "C. Import the existing FAQ document into a new knowl edge base.",
"explanation": "Explanation You can import question and answer pair s from an existing FAQ document into a QnA Maker knowledge base. Reference Link: https://docs.micros oft.com/en-in/learn/modules/build-faq-chatbot-qna-m aker- azure-bot-service/1-introduction/",
"references": ""
},
{
"question": ": What is used to to orchestrate model training, depl oyment, and management tasks?",
"options": [
"A. Python script",
"B. Pipelines",
"C. Notebooks",
"D. Bash Script"
],
"correct": "B. Pipelines",
"explanation": "Explanation Data scientists, software engineers, an d IT operations professionals can define pipelines to orchestrate model training, deployment, and managem ent tasks.",
"references": ""
},
{
"question": ": User can use the workspace to manage data, ________ _, code, __________, and other artifacts related to your machine learning workloads. Choose the correct opti on.",
"options": [
"A. generic resources",
"B. logs",
"C. models",
"D. compute resources"
],
"correct": "",
"explanation": "Explanation Explanation User can use this workspace to manage d ata, compute resources, code, models, and other artifacts related to your machine learning workloads. Referen ce Link: https://docs.microsoft.com/en- us/learn/modules/use-automated-machine-learning/cre ate-workspace",
"references": ""
},
{
"question": ": An area of artificial intelligence (AI) in which so ftware systems are designed to perceive the world v isually, though cameras, images, and video. Choose the corre ct option.",
"options": [
"A. NLP",
"B. Computer Vision",
"C. Machine vision",
"D. Image processing"
],
"correct": "B. Computer Vision",
"explanation": "Explanation Computer vision is an area of artificia l intelligence (AI) in which software systems are d esigned to perceive the world visually, though cameras, images , and video. Reference Link: https://docs.microsoft .com/en- us/learn/paths/explore-computer-vision-microsoft-az ure/",
"references": ""
},
{
"question": ": Which service can help to Identify and categorize e ntities in the text?",
"options": [
"A. Language API service",
"B. Text Language service",
"C. Language cognitive service",
"D. Text analytics service"
],
"correct": "C. Language cognitive service",
"explanation": "Explanation Language cognitive service can help ide ntify and categorize entities in the text. Referenc e Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
"references": ""
},
{
"question": ": Which compute resources are development workstation s that data scientists can use to work with data an d models?",
"options": [
"A. Attached Compute",
"B. Compute Instances",
"C. Inference Clusters",
"D. Compute Clusters"
],
"correct": "B. Compute Instances",
"explanation": "Explanation Compute Instances: Development workstat ions that data scientists can use to work with data and models. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/use-automated-machine- learning/create-compute",
"references": ""
},
{
"question": ": How does the translation engine know when an uttera nce has finished?",
"options": [
"A. After a pause in the audio",
"B. User presses the spacebar",
"C. User needs to speak the word `Stop'.",
"D. After 10 words have been spoken."
],
"correct": "A. After a pause in the audio",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": What is AI?",
"options": [
"A. All of the above",
"B. It is used to automatically detect errors or unus ual activity in a system",
"C. Software that imitates human behaviors and capabi lities",
"D. It has machine learning technology to make predic tion and draw conclusions from data."
],
"correct": "A. All of the above",
"explanation": "Explanation AI is the creation of software that imi tates human behaviors and capabilities. Key element s include: Machine learning - This is often the foundation for an AI system, and is the way we \"teach\" a computer model to make prediction and draw conclusions from data. Ano maly detection - The capability to automatically de tect errors or unusual activity in a system. Computer vi sion - The capability of software to interpret the world visually through cameras, video, and images. Natural languag e processing - The capability for a computer to int erpret written or spoken language, and respond in kind. Co nversational AI - The capability of a software \"age nt\" to participate in a conversation.",
"references": ""
},
{
"question": ": Which service provides an application programming i nterface (API) that developers can use to create an omaly detection solutions?",
"options": [
"A. Binary classification",
"B. Regression",
"C. None of the above",
"D. Anomaly Detector Correct Answer: D"
],
"correct": "",
"explanation": "Explanation In Microsoft Azure, the Anomaly Detecto r service provides an application programming inter face (API) that developers can use to create anomaly det ection solutions.",
"references": ""
},
{
"question": ": Cloud-based resources on which you can run model tr aining and data exploration processes. Choose the correct option.",
"options": [
"A. Resource targets",
"B. Artifacts",
"C. Storage targets",
"D. Compute targets"
],
"correct": "D. Compute targets",
"explanation": "Explanation Compute targets are cloud-based resourc es on which you can run model training and data exploration processes. Reference Link: https://docs .microsoft.com/en-us/learn/modules/use-automated- machine-learning/create-compute",
"references": ""
},
{
"question": ": Encoding words or terms as numeric features that ca n be used to train a machine learning model.",
"options": [
"A. FALSE",
"B. TRUE"
],
"correct": "B. TRUE",
"explanation": "Explanation Encoding words or terms as numeric feat ures that can be used to train a machine learning m odel. For example, to classify a text document based on t he terms it contains. This technique is often used to perform sentiment analysis, in which a document is classifi ed as positive or negative. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
"references": ""
},
{
"question": ": What information is required to connect to your dep loyed service from a client application? Choose the correct option.",
"options": [
"A. Access Key for your service",
"B. REST endpoint for your service",
"C. Primary Key for your service",
"D. Endpoint URL Correct Answer: BC"
],
"correct": "",
"explanation": "Explanation You need below information to connect t o your deployed service from a client application. The REST endpoint for your service the Primary Key for your service Reference Link: https://docs.microsoft.com/ en- us/learn/modules/use-automated-machine-learning/dep loy-model",
"references": ""
},
{
"question": ": What compute resources are based on standard Azure virtual machine images?Choose the correct option.",
"options": [
"A. Interface Clusters",
"B. Attached Cluster",
"C. Compute Clusters",
"D. Compute Instances"
],
"correct": "",
"explanation": "Explanation Compute instances and clusters are base d on standard Azure virtual machine images. Referen ce Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/create-compute",
"references": ""
},
{
"question": ": Which service provides an interface to the knowledg e base through one or more channels?",
"options": [
"A. A bot resource",
"B. A historical data",
"C. A knowledge base",
"D. A bot service"
],
"correct": "D. A bot service",
"explanation": "Explanation A bot service that provides an interfac e to the knowledge base through one or more channel s. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/build-faq-chatbot-qna-maker-azure-bot- service/1-introduction/",
"references": ""
},
{
"question": ": In Azure Machine Learning, data for model training and other operations is usually encapsulated in an object called a __________.",
"options": [
"A. All of the above",
"B. dataset C. file",
"D. Database"
],
"correct": "B. dataset C. file",
"explanation": "Explanation In Azure Machine Learning, data for mod el training and other operations is usually encapsu lated in an object called a dataset. Reference Link: https:/ /docs.microsoft.com/en-us/learn/modules/use-automat ed- machine-learning/data",
"references": ""
},
{
"question": ": The Computer Vision service can use _______________ capabilities to detect printed and handwritten tex t in images.",
"options": [
"A. Intelligent character recognition (ICR)",
"B. Optical character recognition (OCR)",
"C. Optical mark recognition (OMR)",
"D. None of the above"
],
"correct": "B. Optical character recognition (OCR)",
"explanation": "Explanation The Computer Vision service can use opt ical character recognition (OCR) capabilities to de tect printed and handwritten text in images. Reference L ink: https://docs.microsoft.com/en- us/learn/modules/analyze-images-computer-vision/2-i mage-analysis-azure",
"references": ""
},
{
"question": ": Which classification involves training a machine le arning model to classify images based on their contents?",
"options": [
"A. Semantic segmentation",
"B. Image classification",
"C. Image analysis",
"D. Object detection"
],
"correct": "B. Image classification",
"explanation": "Explanation Image classification involves training a machine learning model to classify images based o n their contents. Reference Link: https://docs.microsoft.co m/en-us/learn/modules/get-started-ai-fundamentals/4 - understand-computer-vision",
"references": ""
},
{
"question": ": In automated ML, which vitual machine image is reco mmended to achieve the optimal balance of cost and performance? A. Standard_DS11_v2",
"options": [
"B. None of the above",
"C. Standard_D15_v2",
"D. Standard_DS13_v2"
],
"correct": "",
"explanation": "Explanation In automated ML, the Standard_DS11_v2 i mage is recommended to achieve the optimal balance of cost and performance. Reference Link: https://docs. microsoft.com/en-us/learn/modules/use-automated- machine-learning/create-compute",
"references": ""
},
{
"question": ": To implement the Bot solution, you need the followi ng components. Choose the correct answer.",
"options": [
"A. A bot service",
"B. A knowledge base",
"C. A historical data",
"D. A bot resource"
],
"correct": "",
"explanation": "Explanation To implement BOT solution, you need: A knowledge base of question and answer pairs - usual ly with some built-in natural language processing model to enable questions that can be phrased in multiple wa ys to be understood with the same semantic meaning. A bot se rvice that provides an interface to the knowledge b ase through one or more channels. Reference Link: https ://docs.microsoft.com/en-in/learn/modules/build-faq - chatbot-qna-maker-azure-bot-service/1-introduction/",
"references": ""
},
{
"question": ": You plan to build an application that uses the Spee ch service to transcribe audio recordings of phone calls into text, and then submits the transcribed text to the Text Analytics service to extract key phrases. You want to manage access and billing for the applicati on services in a single Azure resource. Which type of Azure resource should you create?",
"options": [
"A. Cognitive Services",
"B. Computer Vision",
"C. None of the above",
"D. Custom Vision",
"A. Seeing Vision",
"B. Seeing ML",
"C. Seeing Algo",
"D. Seeing AI"
],
"correct": "D. Seeing AI",
"explanation": "Explanation The Seeing AI app is a great example of the power of computer vision. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": When categorizing an image, the Computer Vision ser vice supports two specialized domain models. Choose the correct option.",
"options": [
"A. People",
"B. Celebrities",
"C. Areas",
"D. Landmarks"
],
"correct": "",
"explanation": "Explanation When categorizing an image, the Compute r Vision service supports two specialized domain models: Celebrities, Landmarks Reference Link: https://docs .microsoft.com/en-us/learn/modules/analyze-images- computer-vision/2-image-analysis-azure",
"references": ""
},
{
"question": ": Translator text supports languages.",
"options": [
"A. more than 60",
"B. up to 10",
"C. up to 50",
"D. up to 30",
"A. Gearnal Data",
"B. Advance Data",
"C. Complex Data",
"D. Normalize Data"
],
"correct": "D. Normalize Data",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You are developing an application or tourists to us e as a text-based or audio-based translator. Which Azure services can help?",
"options": [
"A. Text Analytics",
"B. Text Translate",
"C. Translator Text",
"D. Azure Speech"
],
"correct": "C. Translator Text",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": To use the Language service in an application, you can choose to provision either of the following typ es of resource. Choose the correct options.",
"options": [
"A. A Cognitive Services API calls",
"B. A Cognitive Services resource",
"C. A Language resource",
"D. A Language Identifier API service"
],
"correct": "",
"explanation": "Explanation To use the Language service in an appli cation, you must provision an appropriate resource in your Azure subscription. You can choose to provision eit her of the following types of resource: A Language resource, ACognitive Services resource Reference Link: https:/ /docs.microsoft.com/en-in/learn/modules/analyze-tex t-with- text-analytics-service/2-get-started-azure",
"references": ""
},
{
"question": ": Which compute resources links to existing Azure com pute resources, such as Virtual Machines or Azure Databricks clusters?",
"options": [
"A. Attached Compute",
"B. Kubernetes Clusters",
"C. Compute Clusters",
"D. Inference Clusters"
],
"correct": "A. Attached Compute",
"explanation": "Explanation Attached Compute: Links to existing Azu re compute resources, such as Virtual Machines or A zure Databricks clusters. Reference Link: https://docs.m icrosoft.com/en-us/learn/modules/use-automated-mach ine- learning/create-compute",
"references": ""
},
{
"question": ": Which service help to perform sentiment analysis on text to determine a positive or negative sentiment ?",
"options": [
"A. Language cognitive service",
"B. Language API service",
"C. Text analytics service",
"D. Text Language service"
],
"correct": "A. Language cognitive service",
"explanation": "Explanation Language cognitive service can help to perform sentiment analysis on text to determine a p ositive or negative sentiment. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/analyze-text-with-t ext- analytics-service/1-introduction",
"references": ""
},
{
"question": ": What provides first-line of automated support throu gh the full range of channels that we use to communicate?",
"options": [
"A. Robots service",
"B. Bots service",
"C. LUIS service",
"D. QnA Maker"
],
"correct": "B. Bots service",
"explanation": "Explanation Bots are used to provide a first-line o f automated support through the full range of chann els that we use to communicate.",
"references": ""
},
{
"question": ": Using the pre-built machine learning classification model, the service evaluates the text and returns a sentiment score in the range of _________.",
"options": [
"A. 0 to 1",
"B. 0 to 100",
"C. 0 to 1.5",
"D. 0 to 10"
],
"correct": "A. 0 to 1",
"explanation": "Explanation Using the pre-built machine learning cl assification model, the service evaluates the text and returns a sentiment score in the range of 0 to 1. Reference L ink: https://docs.microsoft.com/en-in/learn/modules /analyze- text-with-text-analytics-service/2-get-started-azur e",
"references": ""
},
{
"question": ": In Azure Machine Learning, operations that you run are called ___________.",
"options": [
"A. experiments",
"B. jobs",
"C. runs",
"D. None of the above"
],
"correct": "A. experiments",
"explanation": "Explanation In Azure Machine Learning, operations t hat you run are called experiments. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
"references": ""
},
{
"question": ": You are using the Form Recognizer service to analyz e receipts that you have scanned into JPG format images. What is the maximum file size of JPG file y ou can submit to the pre-built receipt model?",
"options": [
"A. 100MB",
"B. 10MB",
"C. 20MB",
"D. 50MB"
],
"correct": "",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": The confidence score may be greater than 1 as a res ult of the mixed language text.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "B. FALSE",
"explanation": "Explanation The confidence score may be less than 1 as a result of the mixed language text. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": Which service provides a dedicated QnA Maker portal web-based interface that you can use to create, train, publish, and manage knowledge bases?",
"options": [
"A. Bots service",
"B. LUIS service",
"C. Robots service",
"D. QnA Maker"
],
"correct": "D. QnA Maker",
"explanation": "Explanation The QnA Maker service provides a dedica ted QnA Maker portal web-based interface that you c an use to create, train, publish, and manage knowledge bas es. Reference Link: https://docs.microsoft.com/en- in/learn/modules/build-faq-chatbot-qna-maker-azure- bot-service/2-get-started-qna-bot",
"references": ""
},
{
"question": ": An advanced machine learning technique in which ind ividual pixels in the image are classified accordin g to the object to which they belong.",
"options": [
"A. Image classification",
"B. Object detection",
"C. Image analysis",
"D. Semantic segmentation"
],
"correct": "D. Semantic segmentation",
"explanation": "Explanation Semantic segmentation is an advanced ma chine learning technique in which individual pixels in the image are classified according to the object to whi ch they belong. Reference Link: https://docs.micros oft.com/ en- us/learn/modules/get-started-ai-fundamentals/4-unde rstand-computer-vision",
"references": ""
},
{
"question": ": Language cognitive service can help simplify applic ation development by using pre-trained models that can do the following, choose the correct options.",
"options": [
"A. Perform sentiment analysis on text",
"B. None of the above",
"C. Identify and categorize entities in the text.",
"D. Determine the language of a document or text"
],
"correct": "",
"explanation": "Explanation In Microsoft Azure, the Language cognit ive service can help simplify application developme nt by using pre-trained models that can: Determine the la nguage of a document or text (for example, French o r English). Perform sentiment analysis on text to det ermine a positive or negative sentiment. Extract ke y phrases from text that might indicate its main talking poin ts. Identify and categorize entities in the text. E ntities can be people, places, organizations, or even everyday ite ms such as dates, times, quantities, and so on. Ref erence Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
"references": ""
},
{
"question": ": A machine learning based technique that analyzes da ta over time and identifies unusual changes. Choose the correct option.",
"options": [
"A. Outlier detection",
"B. Intrusion detection",
"C. Anomaly detection",
"D. Novelty detection"
],
"correct": "C. Anomaly detection",
"explanation": "Explanation By using anomaly detection - a machine learning based technique that analyzes data over ti me and identifies unusual changes. Reference Link: https:/ /docs.microsoft.com/en-us/learn/modules/get-started -ai- fundamentals/3-understand-anomaly-detection",
"references": ""
},
{
"question": ": What is one aspect that may impair facial detection ?",
"options": [
"A. Medium angles",
"B. Small angles C. Angles",
"D. Extreme angles"
],
"correct": "D. Extreme angles",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": The Text-to-Speech Neural voices leverage Neural ne tworks resulting in a more robotic-sounding voice.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": A sentiment score with values closer to 1 being a _ _________ sentiment.",
"options": [
"A. Positive",
"B. All of the above",
"C. Negative",
"D. Neutral"
],
"correct": "A. Positive",
"explanation": "Explanation Language service evaluates the text and returns a sentiment score in the range of 0 to 1, with values closer to 1 being a positive sentiment. Reference L ink: https://docs.microsoft.com/en-in/learn/modules /analyze- text-with-text-analytics-service/2-get-started-azur e",
"references": ""
},
{
"question": ": Most computer vision solutions are based on machine learning models that can be applied to _______ fro m cameras, videos, or images.",
"options": [
"A. Raw input",
"B. Visual input",
"C. Text input",
"D. Object input"
],
"correct": "B. Visual input",
"explanation": "Explanation Most computer vision solutions are base d on machine learning models that can be applied to visual input from cameras, videos, or images. Reference Li nk: https://docs.microsoft.com/en-us/learn/modules/ get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": Sensors in the car collect _________, such as engin e revolutions, brake temperature, and so on.",
"options": [
"A. Telemetry",
"B. Logs",
"C. Objects",
"D. Metrics"
],
"correct": "A. Telemetry",
"explanation": "Explanation Sensors in the car collect telemetry, s uch as engine revolutions, brake temperature, and s o on. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/3-understan d- anomaly-detection",
"references": ""
},
{
"question": ": The language detection service will focus on the __ __________ in the text.",
"options": [
"A. Expressive language",
"B. Dominant language",
"C. Predominant language",
"D. All of the above"
],
"correct": "C. Predominant language",
"explanation": "Explanation The language detection service will foc us on the predominant language in the text. Referen ce Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
"references": ""
},
{
"question": ": This causes Azure Machine Learning to automatically preprocess the features before training in Automated ML. Choose the correct option.",
"options": [
"A. Enable Primary metric",
"B. All of the above",
"C. Activate featurization",
"D. Enable featurization"
],
"correct": "",
"explanation": "Explanation In Featurization settings. Enable featu rization must be Selected which causes Azure Machin e Learning to automatically preprocess the features before tra ining. Reference Link: https://docs.microsoft.com/e n- us/learn/modules/use-automated-machine-learning/dat a",
"references": ""
},
{
"question": ": You are using Azure Machine Learning designer to cr eate a training pipeline for a binary classificatio n model. You have added a dataset containing features and labels, a Two-Class Decision Forest module, an d a Train Model module. You plan to use Score Model a nd Evaluate Model modules to test the trained model with a subset of the dataset that was not use d for training. Which additional kind of module sho uld you add?",
"options": [
"A. Update Data",
"B. Split Data",
"C. Add Data",
"D. Remove Data"
],
"correct": "B. Split Data",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": Speech cognitive service, which includes the follow ing application programming interfaces (APIs). Choo se the correct options.",
"options": [
"A. The Text-to-Text API",
"B. The Text-to-Speech API",
"C. All of the above",
"D. The Speech-to-Text API"
],
"correct": "",
"explanation": "Explanation The Speech cognitive service, which inc ludes the following application programming interfa ces (APIs): The Speech-to-Text API The Text-to-Speech A PI Reference Link: https://docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/2-get- started-azure",
"references": ""
},
{
"question": ": You want to use the Computer Vision service to anal yze images of locations and identify well-known buildings. What should you do?",
"options": [
"A. Retrieve the objects in the image.",
"B. Retrieve the categories for the image, specifying t he landmarks domain C. None of the above",
"D. Retrieve the categories for the image, specifying the celebrities domain"
],
"correct": "B. Retrieve the categories for the image, specifying t he landmarks domain C. None of the above",
"explanation": "Explanation The landmarks domain includes many well -known buildings around the world. Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/2-image-analysis-azure",
"references": ""
},
{
"question": ": The text analytics capability is useful for detecti ng positive and negative sentiment in below areas. Choose the correct options",
"options": [
"A. Customer reviews",
"B. Social media",
"C. Discussion forums",
"D. All of the above"
],
"correct": "D. All of the above",
"explanation": "Explanation The text analytics capabilities in the Language service can evaluate text and return senti ment scores and labels for each sentence. This capability is us eful for detecting positive and negative sentiment in social media, customer reviews, discussion forums and more . Reference Link: https://docs.microsoft.com/en- in/learn/modules/analyze-text-with-text-analytics-s ervice/2-get-started-azure",
"references": ""
},
{
"question": ": Seeing AI app harnesses the power of AI to open up the visual world and describe nearby _______, ___________and __________.",
"options": [
"A. Text",
"B. People",
"C. None of the above",
"D. Object"
],
"correct": "",
"explanation": "Explanation The Seeing AI app is a great example of the power of computer vision. Designed for the bli nd and low vision community, the Seeing AI app harnesses t he power of AI to open up the visual world and desc ribe nearby people, text and objects. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/get-st arted-ai- fundamentals/4-understand-computer-vision",
"references": ""
},
{
"question": ":Which machine learning model is suitable for predic ting categories or classes?",
"options": [
"A. Regression",
"B. Clustering",
"C. Time series forecasting",
"D. Classification"
],
"correct": "D. Classification",
"explanation": "Explanation Classification is used for predicting c ategories or classes. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
"references": ""
},
{
"question": ": Machine learning models must be trained with live d ata.",
"options": [
"A. FALSE",
"B. TRUE"
],
"correct": "A. FALSE",
"explanation": "Explanation Machine learning models must be trained with existing data. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
"references": ""
},
{
"question": ": Which of the following tasks would be a good fit fo r the Speech-to-Text?",
"options": [
"A. Real-time voice-chat transcription from a microph one",
"B. Creating an audio file from a famous quote",
"C. None of the above",
"D. Translating a document written in English into Ge rman."
],
"correct": "A. Real-time voice-chat transcription from a microph one",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": In Azure Machine Learning, you can deploy a service as an __________ or to an __________________ cluster.",
"options": [
"A. Azure Inference Service (AIS) cluster.",
"B. Azure Container Instances (ACI)",
"C. Azure Compute Instances (ACI) D. Azure Kubernetes Service (AKS) cluster."
],
"correct": "",
"explanation": "Explanation In Azure Machine Learning, you can depl oy a service as an Azure Container Instances (ACI) or to an Azure Kubernetes Service (AKS) cluster. Reference L ink: https://docs.microsoft.com/en-us/learn/modules /use- automated-machine-learning/data",
"references": ""
},
{
"question": ": Which option in Automated ML can calculate feature importance for the best model? Choose the correct option.",
"options": [
"A. Primary metric",
"B. Explain best model",
"C. Blocked algorithms",
"D. Get best model"
],
"correct": "B. Explain best model",
"explanation": "Explanation Explain best model: Selected - this opt ion causes automated machine learning to calculate feature importance for the best model; making it possible t o determine the influence of each feature on the pr edicted label. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/use-automated-machine-learning/d ata",
"references": ""
},
{
"question": ": Image is an array of pixel values which can be used as _________ to train machine learning models that make predictions about the image and its contents.",
"options": [
"A. Objects",
"B. Entities",
"C. Hyperparameters",
"D. Features"
],
"correct": "D. Features",
"explanation": "Explanation An image is just an array of pixel valu es. These numeric values can be used as features to train machine learning models that make predictions about the image and its contents. Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/1-introduction",
"references": ""
},
{
"question": ": The Computer vision service includes a model that h as been trained to identify thousands of well-known celebrities from the worlds of sports, entertainmen t, and business. A. FALSE",
"options": [
"B. TRUE"
],
"correct": "B. TRUE",
"explanation": "Explanation Celebrities - The service includes a mo del that has been trained to identify thousands of well- known celebrities from the worlds of sports, entertainmen t, and business. Reference Link: https://docs.micro soft.com/ en- us/learn/modules/analyze-images-computer-vision/2-i mage-analysis-azure",
"references": ""
},
{
"question": ": How do you access the QnAmaker portal?",
"options": [
"A. qnamaker.ai",
"B. portal.azure.com",
"C. cognitive service",
"D. None of the above"
],
"correct": "A. qnamaker.ai",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You can use the __________ capability of the Langua ge service to identify the language in which text i s written.",
"options": [
"A. Language Identification",
"B. None of the above",
"C. Language detection",
"D. Language analyzer"
],
"correct": "C. Language detection",
"explanation": "Explanation You can use the language detection capa bility of the Language service to identify the lang uage in which text is written. Reference Link: https://docs .microsoft.com/en-in/learn/modules/analyze-text-wit h-text- analytics-service/2-get-started-azure",
"references": ""
},
{
"question": ": What represents the purpose, or goal, expressed in a user's utterance? A. Entities",
"options": [
"B. Objects",
"C. Utterances",
"D. Intents"
],
"correct": "D. Intents",
"explanation": "Explanation An intent represents the purpose, or go al, expressed in a user's utterance. Reference Link : https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/2-get-started-azure",
"references": ""
},
{
"question": ": How does the translation engine know when an uttera nce has finished?",
"options": [
"A. User needs to speak the word `Stop'.",
"B. After 10 words have been spoken.",
"C. After a pause in the audio",
"D. User presses the spacebar"
],
"correct": "C. After a pause in the audio",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": You want to use the Computer Vision service to anal yze images. You also want to use the Text Analytics service to analyze text. You want developers to req uire only one key and endpoint to access all of you r services. What kind of resource should you create i n your Azure subscription?",
"options": [
"A. None of the above",
"B. Custom Vision",
"C. Computer Vision",
"D. Cognitive Services"
],
"correct": "D. Cognitive Services",
"explanation": "Explanation A Cognitive Services resource support b oth Computer Vision and Text Analytics. Reference L ink: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/2-image-analysis-azure",
"references": ""
},
{
"question": ": To classify images based on the type of vehicle the y contain, such as taxis, buses, cyclists, and so o n is an example of __________________.",
"options": [
"A. Semantic segmentation B. Image classification",
"C. Image analysis",
"D. Object detection"
],
"correct": "",
"explanation": "Explanation In a traffic monitoring solution you mi ght use an image classification model to classify i mages based on the type of vehicle they contain, such as taxis, buses, cyclists, and so on. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
"references": ""
},
{
"question": ": You use the Text Analytics service to perform senti ment analysis on a document, and a score of 0.99 is returned. What does this score indicate about the d ocument sentiment?",
"options": [
"A. The document is positive.",
"B. None of the above",
"C. The document is negative.",
"D. All of the above"
],
"correct": "A. The document is positive.",
"explanation": "Explanation/Reference:",
"references": ""
},
{
"question": ": To indentify best model, the training process used some of the data to train the model, and applied a technique called __________ to iteratively test the trained model with data it wasn't trained with and compare the predicted value with the actual known v alue.",
"options": [
"A. None of the above",
"B. inversion",
"C. cross-validation",
"D. Validation"
],
"correct": "C. cross-validation",
"explanation": "Explanation The best model is identified based on t he evaluation metric you specified (Normalized root mean squared error). To calculate this metric, the train ing process used some of the data to train the mode l, and applied a technique called cross-validation to iter atively test the trained model with data it wasn't trained with and compare the predicted value with the actual kno wn value. Reference Link: https://docs.microsoft.co m/en- us/learn/modules/use-automated-machine-learning/dat a",
"references": ""
},
{
"question": "Which solution will be used to identify the locatio n of different classes of vehicle in a traffic moni toring?",
"options": [
"A. Semantic segmentation",
"B. Image analysis",
"C. Image classification",
"D. Object detection"
],
"correct": "D. Object detection",
"explanation": "Explanation A traffic monitoring solution might use object detection to identify the location of diffe rent classes of vehicle. Reference Link: https://docs.microsoft.com /en-us/learn/modules/get-started-ai-fundamentals/4- understand-computer-vision",
"references": ""
},
{
"question": ": The first challenge in creating a user support bot is to use the ___________ to create a knowledge bas e.",
"options": [
"A. A bot service",
"B. A knowledge base service",
"C. QnA Maker service",
"D. A historical data service"
],
"correct": "C. QnA Maker service",
"explanation": "Explanation The first challenge in creating a user support bot is to use the QnA Maker service to crea te a knowledge base. Reference Link: https://docs.micros oft.com/en-in/learn/modules/build-faq-chatbot-qna-m aker- azure-bot-service/2-get-started-qna-bot",
"references": ""
},
{
"question": ": Machine learning models are trained to classify ind ividual objects within an image, and identify their location with a bounding box. Choose the correct op tion.",
"options": [
"A. Object detection",
"B. Image analysis",
"C. Image classification",
"D. Semantic segmentation",
"A. Language cognitive resource",
"B. Language resource",
"C. Cognitive Services resource",
"D. Text analytics resource"
],
"correct": "C. Cognitive Services resource",
"explanation": "Explanation A Cognitive Services resource - choose this resource type if you plan to use the Language service in combination with other cognitive services, and you want to manage access and billing for these service s together. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/analyze-text-with-text-analytics-servic e/2-get- started-azure",
"references": ""
},
{
"question": ": A sentiment score with values closer to 0 being a _ _________ sentiment.",
"options": [
"A. Neutral",
"B. Indeterminant",
"C. Negative",
"D. Positive"
],
"correct": "C. Negative",
"explanation": "Explanation Language service evaluates the text and returns a sentiment score in the range of 0 to 1, with values closer to 0 being a negative sentiment. Reference L ink: https://docs.microsoft.com/en-in/learn/modules / analyze- text-with-text-analytics-service/2-get-started-azur e",
"references": ""
},
{
"question": ": Normalized root mean squared error metric is a part of _______________.",
"options": [
"A. Time series forecasting",
"B. Regression",
"C. Clustering",
"D. Classification"
],
"correct": "B. Regression",
"explanation": "Explanation Normalized root mean squared error metr ic is a part of Regression.",
"references": ""
},
{
"question": ": Some built-in natural language processing model to enable questions that can be phrased in multiple ways to be understood with the same semantic meanin g. Choose the correct term.",
"options": [
"A. A bot resource",
"B. A bot service",
"C. A historical data",
"D. A knowledge base"
],
"correct": "D. A knowledge base",
"explanation": "Explanation A knowledge base of question and answer pairs - usually with some built-in natural languag e processing model to enable questions that can be ph rased in multiple ways to be understood with the sa me semantic meaning. Reference Link: https://docs.micr osoft.com/en-in/learn/modules/build-faq-chatbot-qna - maker-azure-bot-service/1-introduction/",
"references": ""
},
{
"question": ": The difference between the predicted and actual val ue known as __________ in the model.",
"options": [
"A. prediction",
"B. Precision",
"C. error",
"D. Accuracy"
],
"correct": "C. error",
"explanation": "Explanation The difference between the predicted an d actual value (known as the residuals) indicates t he amount of error in the model. Reference Link: https://docs .microsoft.com/en-us/learn/modules/use-automated-ma chine- learning/data",
"references": ""
},
{
"question": ": The Computer Vision service can identify famous lan dmarks, such as the Taj Mahal and the Statue of Liberty.",
"options": [
"A. TRUE",
"B. FALSE"
],
"correct": "A. TRUE",
"explanation": "Explanation Landmarks - The Computer Vision service can identify famous landmarks, such as the Taj Mah al and the Statue of Liberty. Reference Link: https://docs .microsoft.com/en-us/learn/modules/analyze-images- computer-vision/2-image-analysis-azure",
"references": ""
},
{
"question": ": Which machine learning model is suitable for predic ting numeric values?",
"options": [
"A. Classification",
"B. Regression",
"C. Time series forecasting",
"D. Clustering"
],
"correct": "B. Regression",
"explanation": "Explanation Regression is used for predicting numer ic values. Reference Link: https://docs.microsoft.c om/en- us/learn/modules/use-automated-machine-learning/dat a",
"references": ""
},
{
"question": ": User can use automated machine learning to train mo dels for below problems. Choose the correct option.",
"options": [
"A. Regression",
"B. Classification",
"C. Time series forecasting",
"D. Clustering"
],
"correct": "",
"explanation": "Explanation User can use automated machine learning to train models for: Classification (predicting ca tegories or classes) Regression (predicting numeric values) Tim e series forecasting (regression with a time-series element, enabling you to predict numeric values at a future point in time) Reference Link: https://docs.microso ft.com/en- us/learn/modules/use-automated-machine-learning/dat a",
"references": ""
},
{
"question": ": You want to use the Computer Vision service to iden tify the location of individual items in an image. Which of the following features should you retrieve ?",
"options": [
"A. All of the above",
"B. Categories",
"C. Objects D. Tags"
],
"correct": "C. Objects D. Tags",
"explanation": "Explanation Computer Vision returns objects with a bounding box to indicate their location in the imag e. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/analyze-images-computer-vision/2-image- analysis-azure",
"references": ""
}
]