100% OFF Microsoft Azure AI (AI-900) Exam Questions May - 2025 Coupon Code
100% OFF Microsoft Azure AI (AI-900) Exam Questions May - 2025 Coupon Code
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  • Platform: Udemy
  • Category: IT Certifications
  • Language: English
  • Instructor: Z Ahmadi
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Prepare for Success: 420+ Updated AI-900 Practice Tests with Explanations to Achieve Microsoft Azure AI Fundamentals

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Skills at a glance

  • Describe Artificial Intelligence workloads and considerations (15–20%)

  • Describe fundamental principles of machine learning on Azure (15–20%)

  • Describe features of computer vision workloads on Azure (15–20%)

  • Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)

  • Describe features of generative AI workloads on Azure (20–25%)

Describe Artificial Intelligence workloads and considerations (15–20%)

Identify features of common AI workloads

  • Identify computer vision workloads

  • Identify natural language processing workloads

  • Identify document processing workloads

  • Identify features of generative AI workloads

Identify guiding principles for responsible AI

  • Describe considerations for fairness in an AI solution

  • Describe considerations for reliability and safety in an AI solution

  • Describe considerations for privacy and security in an AI solution

  • Describe considerations for inclusiveness in an AI solution

  • Describe considerations for transparency in an AI solution

  • Describe considerations for accountability in an AI solution

Describe fundamental principles of machine learning on Azure (15-20%)

Identify common machine learning techniques

  • Identify regression machine learning scenarios

  • Identify classification machine learning scenarios

  • Identify clustering machine learning scenarios

  • Identify features of deep learning techniques

  • Identify features of the Transformer architecture

Describe core machine learning concepts

  • Identify features and labels in a dataset for machine learning

  • Describe how training and validation datasets are used in machine learning

Describe Azure Machine Learning capabilities

  • Describe capabilities of automated machine learning

  • Describe data and compute services for data science and machine learning

  • Describe model management and deployment capabilities in Azure Machine Learning

Describe features of computer vision workloads on Azure (15–20%)

Identify common types of computer vision solution

  • Identify features of image classification solutions

  • Identify features of object detection solutions

  • Identify features of optical character recognition solutions

  • Identify features of facial detection and facial analysis solutions

Identify Azure tools and services for computer vision tasks

  • Describe capabilities of the Azure AI Vision service

  • Describe capabilities of the Azure AI Face detection service

Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)

Identify features of common NLP Workload Scenarios

  • Identify features and uses for key phrase extraction

  • Identify features and uses for entity recognition

  • Identify features and uses for sentiment analysis

  • Identify features and uses for language modeling

  • Identify features and uses for speech recognition and synthesis

  • Identify features and uses for translation

Identify Azure tools and services for NLP workloads

  • Describe capabilities of the Azure AI Language service

  • Describe capabilities of the Azure AI Speech service

Describe features of generative AI workloads on Azure (20–25%)

Identify features of generative AI solutions

  • Identify features of generative AI models

  • Identify common scenarios for generative AI

  • Identify responsible AI considerations for generative AI

Identify generative AI services and capabilities in Microsoft Azure

  • Describe features and capabilities of Azure AI Foundry

  • Describe features and capabilities of Azure OpenAI service

  • Describe features and capabilities of Azure AI Foundry model catalog