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AI-900: Microsoft Azure AI Fundamentals.
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AI-900: Microsoft Azure AI Fundamentals.

About this course

Candidates for this exam should have foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.This exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial.Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.What is AI?Simply put, AI is the creation of software that imitates human behaviors and capabilities. Key elements include:Machine learning - This is often the foundation for an AI system, and is the way we "teach" a computer model to make prediction and draw conclusions from data.Anomaly detection - The capability to automatically detect errors or unusual activity in a system.Computer vision - The capability of software to interpret the world visually through cameras, video, and images.Natural language processing - The capability for a computer to interpret written or spoken language, and respond in kind.Conversational AI - The capability of a software "agent" to participate in a conversation.

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63/100

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39/45
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What you'll learn

  • understand basic concepts of AI and ML
  • identify common AI workloads
  • explain how Azure services support AI implementation
  • recognize the applications of anomaly detection and computer vision

Course objectives

  • demonstrate knowledge of AI and ML concepts
  • prepare for Azure role-based certifications
  • apply AI principles using Microsoft Azure services
Artificial Intelligence #azure #artificial intelligence #machine learning #computer vision #natural language processing #cloud ai #anomaly detection #conversational ai #azure services #ml workloads
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