Microsoft AI-900 Online Practice Questions and Exam Preparation

Microsoft AI-900 Online Questions & Answers

• Question 341:

  You are developing a system to predict the prices of insurance for drivers in the United Kingdom.

  You need to minimize bias in the system.

  What should you do?

  A. Remove information about protected characteristics from the data before sampling.
  B. Take a training sample that is representative of the population in the United Kingdom.
  C. Create a training dataset that uses data from global insurers.
  D. Take a completely random training sample.
  C. Create a training dataset that uses data from global insurers.

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  Explanation

  Best practices you implement

  Use more data

  Using more data is the simplest and best possible way to prevent overfitting, and as an added bonus typically increases accuracy. When you use more data, it becomes harder for the model to memorize exact patterns, and it is forced to reach solutions that are more flexible to accommodate more conditions. It's also important to recognize statistical bias, to ensure your training data doesn't include isolated patterns that won't exist in live-prediction data. This scenario can be difficult to solve, because there may not be overfitting between your train and test sets, but there may be overfitting present when compared to live test data.

  Note: Prevent overfitting and imbalanced data with automated machine learning

  The best way to prevent overfitting is to follow ML best-practices including:

  -> Using more training data, and eliminating statistical bias

  Preventing target leakage

  Using fewer features

  Regularization and hyperparameter optimization Model complexity limitations Cross-validation

  References:

  https://learn.microsoft.com/en-us/azure/machine-learning/concept-manage-ml-pitfalls

• Question 342:

  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. Custom Vision
  B. QnA Maker
  C. Translator Text
  D. Face
  B. QnA Maker

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  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 semi-structured 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.

  Incorrect Answers:

  A: Azure Custom Vision is a cognitive service that lets you build, deploy, and improve your own image classifiers. An image classifier is an AI service that applies labels (which represent classes) to images, according to their visual characteristics. Unlike the Computer Vision service, Custom Vision allows you to specify the labels to apply.

  D:

  Azure Cognitive Services Face Detection API: At a minimum, each detected face corresponds to a faceRectangle field in the response. This set of pixel coordinates for the left, top, width, and height mark the located face. Using these coordinates, you can get the location of the face and its size. In the API response, faces are listed in size order from largest to smallest.

  References:

  https://azure.microsoft.com/en-us/services/cognitive-services/qna-maker/

• Question 343:

  HOTSPOT

  To complete the sentence, select the appropriate option in the answer area.

  

  

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  References:

  https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai

• Question 344:

  You deploy the Azure OpenAI service to generate images.

  You need to ensure that the service provides the highest level of protection against harmful content.

  What should you do?

  A. Configure the Content filters settings.
  B. Customize a large language model (LLM).
  C. Configure the system prompt
  D. Change the model used by the Azure OpenAI service.
  A. Configure the Content filters settings.

• Question 345:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

• Question 346:

  You have an Azure Machine Learning model that uses clinical data to predict whether a patient has a disease.

  You clean and transform the clinical data.

  You need to ensure that the accuracy of the model can be proven.

  What should you do next?

  A. Train the model by using the clinical data.
  B. Split the clinical data into Two datasets.
  C. Train the model by using automated machine learning (automated ML).
  D. Validate the model by using the clinical data.
  D. Validate the model by using the clinical data.

• Question 347:

  Which OpenAI model does GitHub Copilot use to make suggestions for client-side JavaScript?

  A. GPT-4
  B. Codex
  C. DALL-E
  D. GPT-3
  B. Codex

• Question 348:

  HOTSPOT

  To complete the sentence, select the appropriate option in the answer area.

  

  

• Question 349:

  What are two tasks that can be performed by using the Computer Vision service? Each correct answer presents a complete solution.

  NOTE: Each correct selection is worth one point.

  A. Train a custom image classification model.
  B. Detect faces in an image.
  C. Recognize handwritten text.
  D. Translate the text in an image between languages.
  B. Detect faces in an image.
  C. Recognize handwritten text.

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  Explanation

  B: Azure's Computer Vision service provides developers with 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.

  C: 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.

  References:

  https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/homeDetectfacesinanimage-FaceAPIMicrosoftAzureprovidesmultiplecognitiveservicesthatyoucanusetodetectandanalyzefaces,including:ComputerVision,whichoffersfacedetectionandsomebasicfaceanalysis,suchasdeterminingage.VideoIndexer,whichyoucanusetodetectandidentifyfacesinavideo.Face,whichofferspre-builtalgorithmsthatcandetect,recognize,andanalyzefaces.Recognizehandwrittentext-ReadAPITheReadAPIisabetteroptionforscanneddocumentsthathavealotoftext.TheReadAPIalsohastheabilitytoautomaticallydeterminetheproperrecognitionmodel

• Question 350:

  Stating the source of the data used to train a model is an example of which responsible Al principle?

  A. fairness
  B. transparency
  C. reliability and safety
  D. privacy and security
  B. transparency

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  Explanation

  According to Microsoft's Responsible AI Principles, Transparency means that AI systems should clearly communicate how they operate, including data sources, limitations, and decision-making processes.

  Stating the source of data used to train a model helps users understand where the model's knowledge comes from, enabling informed trust and accountability. Transparency ensures that organizations disclose relevant details about data collection and model design, especially for compliance, fairness, and reproducibility.

  Other options are incorrect:

  A. Fairness: Focuses on avoiding bias and ensuring equitable outcomes.

  C. Reliability and safety: Ensures AI performs consistently and safely.

  D. Privacy and security: Protects user data and maintains confidentiality. Thus, the principle illustrated by disclosing training data sources is Transparency.