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You can read the Best Solution to prepare AI-900: Microsoft Azure AI Fundamentals Exam

You can read the Best Solution to prepare AI-900: Microsoft Azure AI Fundamentals Exam. It has become an essential trend for the candidates who are preparing for the exam. There are several methods in this field. Familiarity with the necessary resources is essential for this purpose. Translator is comes with the certification. Solutiondescribe is required for this purpose. Forecasting is used for the AI. The exam AI-900 Microsoft Azure AI Fundamentals Exam is useful to work on several systems. Feature engineering is a very important method of the AI. Evaluation and testing of the accuracy and correctness is the best practice for this purpose. Regression analysis is used to achieve this. Data validation is used for this purpose. The data collection process is easy with the Microsoft AI-900 exam. Microsoft AI-900 exam dumps are used for this purpose. Data validation is easy with the Microsoft AI-900 exam. Regression analysis is important for this purpose. Create a cluster for this purpose. Content migration is required for this purpose. Digital image is used for this purpose. Images are used for this purpose. The data is used for this purpose.

Exam Details

The Microsoft AI-900 exam is the only qualifying test that leads to the Microsoft Certified: Azure AI Fundamentals certification. It measures one’s knowledge of AI considerations & workloads, features of NLP workloads on Azure, and basic principles of ML on Azure. The candidates can choose to take this exam in English, French, Simplified Chinese, Japanese, German, Spanish, or Korean. It contains 40-60 questions covering different types, including case studies, drag and drop, active screen, build list, and multiple choice. You can schedule your test with Certiport or Pearson VUE. However, it is required to pay the fee of $99 before scheduling it.

Microsoft AI-900 Exam Syllabus Topics:

Topic Details
Topic 1
  • Identify clustering machine learning scenarios
  • Automated Machine Learning UI tool
  • azure Machine Learning designer

Topic 2
  • describe how training and validation datasets are used in machine learning
  • Identify features of anomaly detection workloads

Topic 3
  • Identify features of image classification solutions
  • Identify features of common AI workloads

Topic 4
  • Describe fundamental principles of machine learning on Azure
  • Identify core tasks in creating a machine learning solution

Topic 5
  • Describe features of computer vision workloads on Azure
  • Describe considerations for privacy and security in an AI solution

Topic 6
  • Identify features of object detection solutions
  • identify features and labels in a data set for machine learning

Topic 7
  • Identify conversational AI workloads Identify guiding principles for responsible AI
  • Identify prediction
  • forecasting workloads

Topic 8
  • Identify features of semantic segmentation solutions
  • Identify natural language processing or knowledge mining workloads

Topic 9
  • Describe how machine learning algorithms are used for model training
  • Identify common machine learning types


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Microsoft Azure AI Fundamentals Sample Questions (Q86-Q91):

NEW QUESTION # 86
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.
Answer: ** Explanation:
Explanation
Graphical user interface, text, application, chat or text message Description automatically generated

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines
NEW QUESTION # 87**
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 # 88**
To complete the sentence, select the appropriate option in the answer area.
Answer: ** Explanation:

Explanation

With Microsoft's Conversational AI tools developers can build, connect, deploy, and manage intelligent bots that naturally interact with their users on a website, app, Cortana, Microsoft Teams, Skype, Facebook Messenger, Slack, and more.
Reference:
https://azure.microsoft.com/en-in/blog/microsoft-conversational-ai-tools-enable-developers-to-build-connect-and
NEW QUESTION # 89**
What is a use case for classification?

  • A. predicting how many cups of coffee a person will drink based on how many hours the person slept the previous night.
  • B. predicting whether someone uses a bicycle to travel to work based on the distance from home to work
  • C. predicting how many minutes it will take someone to run a race based on past race times
  • D. analyzing the contents of images and grouping images that have similar colors

Answer: D Explanation:
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-m
NEW QUESTION # 90
To complete the sentence, select the appropriate option in the answer area.
Answer: ** Explanation:

Explanation

With Microsoft's Conversational AI tools developers can build, connect, deploy, and manage intelligent bots that naturally interact with their users on a website, app, Cortana, Microsoft Teams, Skype, Facebook Messenger, Slack, and more.
Reference:
https://azure.microsoft.com/en-in/blog/microsoft-conversational-ai-tools-enable-developers-to-build-connect-and
NEW QUESTION # 91
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