AI-900: Microsoft Azure AI Fundamentals - May 2025
12 days ago
IT & Software
[100% OFF] AI-900: Microsoft Azure AI Fundamentals - May 2025

Crack the AI-900: 370+ Practice Questions with Explanations to Secure Your Microsoft Azure AI Fundamentals Certification

5.0
2,358 students
Certificate
English
$0$54.99
100% OFF

Course Description

Skills at a glance

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

  • Describe fundamental principles of machine learning on Azure (20–25%)

  • 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 (15–20%)

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

Describe fundamental principles of machine learning on Azure (20–25%)

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 (15–20%)

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

Identify features of common AI workloads

  • Identify features of content moderation and personalization workloads

  • Identify computer vision workloads

  • Identify natural language processing workloads

  • Identify knowledge mining workloads

  • Identify document intelligence workloads

  • Identify features of generative AI workloads

Identify features of content moderation and personalization workloads

Identify computer vision workloads

Identify natural language processing workloads

Identify knowledge mining workloads

Identify document intelligence 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 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 (20–25%)

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 regression machine learning scenarios

Identify classification machine learning scenarios

Identify clustering machine learning scenarios

Identify features of deep learning techniques

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

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 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 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 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 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 capabilities of the Azure AI Language service

Describe capabilities of the Azure AI Speech service

Describe features of generative AI workloads on Azure (15–20%)

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 features of generative AI models

Identify common scenarios for generative AI

Identify responsible AI considerations for generative AI

Identify capabilities of Azure OpenAI Service

  • Describe natural language generation capabilities of Azure OpenAI Service

  • Describe code generation capabilities of Azure OpenAI Service

  • Describe image generation capabilities of Azure OpenAI Service

Describe natural language generation capabilities of Azure OpenAI Service

Describe code generation capabilities of Azure OpenAI Service

Describe image generation capabilities of Azure OpenAI Service

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