New 2023 Realistic Free Microsoft AI-900 Exam Dump Questions and Answer
AI-900 Practice Test Engine: Try These 165 Exam Questions
Career Prospects
Although the Microsoft AI-900 exam is associated with the foundational-level certification, all the successful candidates can pursue various lucrative career paths in the field of IT. Some of the job roles that these professionals can work in include a Data Scientist, a Software Developer, and an Azure AI Engineer, among others. They can also proceed to get some other role-based certificates to boost their potential in the world of Information Technology. With the Microsoft Certified: Azure AI Fundamentals certification, you can earn an average of $48,000 per annum as an entry-level specialist. Those with some work experience can get an average of $74,000 per year.
Exam Overview
This certification test is available in English, Spanish, Simplified Chinese, Japanese, French, Korean, and German. You will find different formats of questions while dealing with this Microsoft exam. These include multiple choice, drag and drop, build list, active screen, short answer, and best answer. The test costs $99 and the learners can register for it through Pearson VUE or Certiport.
The Importance of Microsoft AI-900 Exam
Microsoft AI-900 exam is an associate level certification which is a three to five-hour exam that covers the technologies necessary for building intelligent applications for cloud computing. Students should have a solid knowledge of Microsoft Azure IaaS, services, APIs, SQL Server 2017. Role of Azure Intelligent Solutions. Windows 2012, Windows 2016, and SQL Server 2017. .NET Framework 4.6.1 (or 4.7), or higher. Resident Deployment of the Solutions. Classify application workloads. Apply Azure monitoring and analytics, Operations Management Suite (OMS) logs, and Event Hubs. Manage the master database. Implement master database failover. Microsoft AI-900 exam dumps aligns with the objectives listed below. Classify application workloads. Deploy, configure, set up, activate, maintain, troubleshoot and support all necessary Azure services. Manage the master database.
Informationidentify the load of a given server. Forums and blogs about Azure and use of its products. Long term planning and development of future plans. Categoriesidentify the Azure deployment models. Forums and blogs about Azure and use of its products. Easy management of the Azure resources. Responsible for managing the database when the system doesn't work normally. Array of Solutionstests the knowledge of the candidate. Backgrounds of the candidate before they start their work. Push when you are in the process of testing.
NEW QUESTION 90
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Yes
Automated machine learning, also referred to as automated ML or AutoML, is the process of automating the time consuming, iterative tasks of machine learning model development. It allows data scientists, analysts, and developers to build ML models with high scale, efficiency, and productivity all while sustaining model quality.
Box 2: No
Box 3: Yes
During training, Azure Machine Learning creates a number of pipelines in parallel that try different algorithms and parameters for you. The service iterates through ML algorithms paired with feature selections, where each iteration produces a model with a training score. The higher the score, the better the model is considered to
"fit" your data. It will stop once it hits the exit criteria defined in the experiment.
Box 4: No
Apply automated ML when you want Azure Machine Learning to train and tune a model for you using the target metric you specify.
The label is the column you want to predict.
Reference:
https://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features
NEW QUESTION 91
Match the types of machine learning to the appropriate scenarios.
To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right.
Each machine learning type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Graphical user interface, text, application Description automatically generated
Box 1: Image classification
Image classification is a supervised learning problem: define a set of target classes (objects to identify in images), and train a model to recognize them using labeled example photos.
Box 2: Object detection
Object detection is a computer vision problem. While closely related to image classification, object detection performs image classification at a more granular scale. Object detection both locates and categorizes entities within images.
Box 3: Semantic Segmentation
Semantic segmentation achieves fine-grained inference by making dense predictions inferring labels for every pixel, so that each pixel is labeled with the class of its enclosing object ore region.
Reference:
https://developers.google.com/machine-learning/practica/image-classification
https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/object-detection-model-builder
https://nanonets.com/blog/how-to-do-semantic-segmentation-using-deep-learning/
NEW QUESTION 92
You have an Azure Machine Learning model that predicts product quality. The model has a training dataset that contains 50,000 records. A sample of the data is shown in the following table.
For each of the following Statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION 93
Match the Azure Cognitive Services service to the appropriate actions.
To answer, drag the appropriate service from the column on the left to its action on the right. Each service may he used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION 94
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation:
Reliability and safety: To build trust, it's critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions. These systems should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation.
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles
NEW QUESTION 95
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation
Privacy and security.
As AI becomes more prevalent, protecting privacy and securing important personal and business information is becoming more critical and complex. With AI, privacy and data security issues require especially close attention because access to data is essential for AI systems to make accurate and informed predictions and decisions about people. AI systems must comply with privacy laws that require transparency about the collection, use, and storage of data and mandate that consumers have appropriate controls to choose how their data is used. At Microsoft, we are continuing to research privacy and security breakthroughs (see next unit) and invest in robust compliance processes to ensure that data collected and used by our AI systems is handled responsibly.
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles
NEW QUESTION 96
What are two tasks that can be performed by using computer vision? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. Detect the color scheme in an image
- B. Detect brands in an image.
- C. Predict stock prices.
- D. Translate text between languages.
- E. Extract key phrases.
Answer: B,E
Explanation:
B: Azure's Computer Vision service gives you access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an image contains adult content, find specific brands or objects, or find human faces.
E: Computer Vision includes Optical Character Recognition (OCR) capabilities. You can use the new Read API to extract printed and handwritten text from images and documents. It uses the latest models and works with text on a variety of surfaces and backgrounds. These include receipts, posters, business cards, letters, and whiteboards. The two OCR APIs support extracting printed text in several languages.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview
NEW QUESTION 97
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://www.cloudfactory.com/data-labeling-guide
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
NEW QUESTION 98
You need to track multiple versions of a model that was trained by using Azure Machine Learning. What should you do?
- A. Register the training data.
- B. Explain the model.
- C. Register the model.
- D. Provision an inference duster.
Answer: C
NEW QUESTION 99
You need to develop a web-based AI solution for a customer support system. Users must be able to interact with a web app that will guide them to the best resource or answer.
Which service should you use?
- A. QnA Maker
- B. Custom Vision
- C. Face
- D. Translator Text
Answer: A
Explanation:
Explanation
QnA Maker is a cloud-based API service that lets you create a conversational question-and-answer layer over your existing data. Use it to build a knowledge base by extracting questions and answers from your semistructured content, including FAQs, manuals, and documents. Answer users' questions with the best answers from the QnAs in your knowledge base-automatically. Your knowledge base gets smarter, too, as it continually learns from user behavior.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/qna-maker/
NEW QUESTION 100
Which type of machine learning should you use to identify groups of people who have similar purchasing habits?
- A. regression
- B. classification
- C. clustering
Answer: C
Explanation:
Explanation
Clustering is a machine learning task that is used to group instances of data into clusters that contain similar characteristics. Clustering can also be used to identify relationships in a dataset Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks
NEW QUESTION 101
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection
NEW QUESTION 102
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Graphical user interface, text, application, email Description automatically generated
NEW QUESTION 103
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-gb/azure/cognitive-services/qnamaker/concepts/data-sources-and-content
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/choose-natural-language-processing-service QnA maker conversational AI service and has nothing to do with SQL database You can easily create a user support bot solution on Microsoft Azure using a combination of two core technologies:
- QnA Maker. This cognitive service enables you to create and publish a knowledge base with built-in natural language processing capabilities.
- Azure Bot Service. This service provides a framework for developing, publishing, and managing bots on Azure.
https://docs.microsoft.com/en-us/learn/modules/build-faq-chatbot-qna-maker-azure-bot-service/2-get-started-qna-bot LUIS is used to understand user intent from utterances.
Creating a language understanding application with Language Understanding consists of two main tasks. First you must define entities, intents, and utterances with which to train the language model - referred to as authoring the model. Then you must publish the model so that client applications can use it for intent and entity prediction based on user input.
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/choose-natural-language-processing-service
NEW QUESTION 104
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Reference:
https://docs.microsoft.com/en-gb/azure/cognitive-services/text-analytics/overview
https://azure.microsoft.com/en-gb/services/cognitive-services/speech-services/ You can use the Speech service to transcribe a call to text - Yes we can use Speech to Text API to achieve this
https://docs.microsoft.com/en-us/learn/modules/recognize-synthesize-speech/1-introduction You can use a speech service to translate the audio of a call to a different language - Yes we can use Speech translation service to achieve this The Speech service includes the following application programming interfaces (APIs):
Speech-to-text - used to transcribe speech from an audio source to text format.
Text-to-speech - used to generate spoken audio from a text source.
Speech Translation - used to translate speech in one language to text or speech in another.
https://docs.microsoft.com/en-us/learn/modules/translate-text-with-translation-service/2-get-started-azure You can use text analytics service to extract key entities from a call transcript -Yes Text Analytics API helps to achieve this
https://docs.microsoft.com/en-us/learn/modules/analyze-text-with-text-analytics-service/2-get-started-azure
NEW QUESTION 105
You use Azure Machine Learning designer to publish an inference pipeline.
Which two parameters should you use to consume the pipeline? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. the authentication key
- B. the training endpoint
- C. the REST endpoint
- D. the model name
Answer: A,C
Explanation:
Explanation
https://docs.microsoft.com/en-in/learn/modules/create-regression-model-azure-machine-learning-designer/deploy
NEW QUESTION 106
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features
NEW QUESTION 107
What is a use case for classification?
- A. analyzing the contents of images and grouping images that have similar colors
- B. predicting whether someone uses a bicycle to travel to work based on the distance from home to work
- C. predicting how many cups of coffee a person will drink based on how many hours the person slept the previous night.
- D. predicting how many minutes it will take someone to run a race based on past race times
Answer: A
Explanation:
Section: Describe features of computer vision workloads on Azure
Explanation:
Classification is a machine learning method that uses data to determine the category, type, or class of an item or row of data.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/linear-regression
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/machine-learning-initialize- model-clustering
NEW QUESTION 108
Match the tool to the Azure Machine Learning task.
To answer, drag the appropriate tool from the column on the left to its tasks on the right. Each tool may be used once, more than once, or not at all NOTE: Each correct match is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION 109
A medical research project uses a large anonymized dataset of brain scan images that are categorized into predefined brain haemorrhage types.
You need to use machine learning to support early detection of the different brain haemorrhage types in the images before the images are reviewed by a person.
This is an example of which type of machine learning?
- A. regression
- B. clustering
- C. classification
Answer: C
Explanation:
Reference:
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/introduction
NEW QUESTION 110
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