Microsoft Fundamentals AI-900 Questions & Answers

• Question 1:

  DRAG DROP

  You plan to deploy an Azure Machine Learning model by using the Machine Learning designer.

  Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

  Select and Place:

  

  Correct Answer:

  

• Question 2:

  DRAG DROP

  Match the Azure Cognitive Services to the appropriate AI workloads.

  To answer, drag the appropriate service from the column on the left to its workload on the right. Each service may be used once, more than once, or not at all.

  NOTE: Each correct match is worth one point.

  Select and Place:

  

  Correct Answer:

  

  Box 1: Custom Vision

  The Custom Vision service uses a machine learning algorithm to analyze images. You submit sets of images that have and don't have the visual characteristics you're looking for. Then you label the images with your own custom labels (tags)

  at the time of submission. The algorithm trains to this data and calculates its own accuracy by testing itself on the same images. Once you've trained your model, you can test, retrain, and eventually use it in your image recognition app to

  classify images or detect objects.

  Box 2: Form Recognized

  Box 3: Face

  The Azure Face service provides AI algorithms that detect, recognize, and analyze human faces in images. Facial recognition software is important in many different scenarios, such as identity verification, touchless access control, and face

  blurring for privacy.

  Reference:

  https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/overview

  https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-identity

• Question 3:

  DRAG DROP

  Match the Azure Cognitive Services 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 be used once, more than once, or not at all.

  NOTE: Each correct selection is worth one point.

  Select and Place:

  

  Correct Answer:

  

  Box 1: Custom Vision Azure Custom Vision is an image recognition service that lets you build, deploy, and improve your own image identifier models. An image identifier applies labels to images, according to their visual characteristics. Each label represents a classification or object.

  Box 2: Form Recognizer Box 3: Face Reference: https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/overview

• Question 4:

  DRAG DROP

  Match the types of natural language processing workloads to the appropriate scenarios.

  To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.

  NOTE: Each correct match is worth one point.

  Select and Place:

  

  Correct Answer:

  

• Question 5:

  DRAG DROP

  You plan to use Azure Cognitive Services to develop a voice controlled personal assistant app.

  Match the Azure Cognitive Services to the appropriate tasks.

  To answer, drag the appropriate service from the column on the left to its description on the right. Each service may be used once, more than once, or not at all.

  NOTE: Each correct selection is worth one point.

  Select and Place:

  

  Correct Answer:

  

  Box 1: Speech

  The Speech service provides speech-to-text and text-to-speech capabilities with an Azure Speech resource. You can transcribe speech to text with high accuracy, produce natural-sounding text-to-speech voices, translate spoken audio, and

  use speaker recognition during conversations.

  Box 2: Language service

  Build applications with conversational language understanding, a Cognitive Service for Language feature that understands natural language to interpret user goals and extracts key information from conversational phrases. Create multilingual,

  customizable intent classification and entity extraction models for your domain-specific keywords or phrases across 96 languages.

  Box 3: Speech

  Incorrect:

  Not Translator text: Text translation is a cloud-based REST API feature of the Translator service that uses neural machine translation technology to enable quick and accurate source-to-target text translation in real time across all supported

  languages.

  Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/overview

  https://azure.microsoft.com/en-us/services/cognitive-services/conversational-language-understanding/

  https://docs.microsoft.com/en-us/azure/cognitive-services/translator/text-translation-overview

• Question 6:

  DRAG DROP

  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.

  Select and Place:

  

  Correct Answer:

  

  Box 1: The Azure portal Box 2: Machine Learning designer Box 3: Automated machine learning (automated ML)

  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. Reference: https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml

• Question 7:

  DRAG DROP Match the services to the appropriate descriptions. To answer, drag the appropriate service from the column on the left to its description on the right. Each service may be used once, more than once, or not at all. NOTE: Each correct match is worth one point

  Select and Place:

  

  Correct Answer:

  

• Question 8:

  DRAG DROP

  Match the principles of responsible AI to the appropriate descriptions.

  To answer, drag the appropriate principle from the column on the left to its description on the right. Each principle may be used once, more than once, or not at all.

  NOTE: Each correct match is worth one point.

  Select and Place:

  

  Correct Answer:

  

  Box 1: Reliability and safety

  Reliability and safety: AI systems should perform reliably and safely.

  Box 2: Privacy and security

  Privacy and security: AI systems should be secure and respect privacy.

  Incorrect:

  Inclusiveness: AI systems should empower everyone and engage people.

  Fairness: AI systems should treat all people fairly.

  Reference: https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai

• Question 9:

  DRAG DROP

  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.

  Select and Place:

  

  Correct Answer:

  

  Box 1: Speech

  Custom Speech: Code-free automated machine learning for speech recognition

  Speech to text is a Speech service feature that accurately transcribes spoken audio to text.

  Make spoken audio actionable

  Quickly and accurately transcribe audio to text in more than 100 languages and variants. Customize models to enhance accuracy for domain-specific terminology. Get more value from spoken audio by enabling search or analytics on

  transcribed text or facilitating action—all in your preferred programming language.

  Box 2: Language service

  Add intents to your LUIS app to identify groups of questions or commands that have the same intention.

  Note: Language understanding (LU) is a very centric component to enable conversational services such as bots, IoT experiences, analytics, and others. In a spoken dialog system, LU converts from the words in a sentence into a machine-

  readable meaning representation, typically indicating the intent of the sentence and any present entities. For example, consider a physical fitness domain, with a dialog system embedded in a wearable device like a watch. This dialog system

  could recognize intents like StartActivity and StopActivity, and could recognize entities like ActivityType. In the user input “begin a jog”, the goal of LU is to identify the intent as StartActivity, and identify the entity ActivityType= ’’jog’’.

  Box 3: Language service

  Intent compared to entity

  The intent represents the action the application should take for the user, based on the entire utterance. An utterance can have only one top-scoring intent, but it can have many entities.

  Create an intent when the user's intention would trigger an action in your client application, like a call to the checkweather() function from the table above. Then create entities to represent parameters required to execute the action.

  Reference: https://azure.microsoft.com/en-us/services/cognitive-services/speech-to-text

  https://azure.microsoft.com/en-us/blog/luis-ai-automated-machine-learning-for-custom-language-understanding/

  https://docs.microsoft.com/en-us/azure/cognitive-services/luis/concepts/intents

• Question 10:

  DRAG DROP

  You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.

  Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of processes to the answer area and arrange them in the correct order.

  Select and Place:

  

  Correct Answer:

  

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines