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AI-900 Practice Tests (latest) Microsoft Azure Fundamentals
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AI-900 Practice Tests (latest) Microsoft Azure Fundamentals

About this course

The AI-900 Microsoft Azure AI Fundamentals Practice Test Course is designed to help you prepare for the AI-900 certification exam by covering key topics and providing practice questions. Here's a concise summary of the course content:Introduction to AI Concepts: Understand the fundamental principles of artificial intelligence, including machine learning, deep learning, and neural networks.Azure AI Services Overview: Learn about the various AI services offered by Microsoft Azure, such as Azure Machine Learning, Cognitive Services, and Azure Bot Services.Machine Learning on Azure: Explore how to build, train, and deploy machine learning models using Azure Machine Learning Studio and other tools.Natural Language Processing (NLP): Delve into NLP concepts and how to implement them using Azure services like Text Analytics and Language Understanding (LUIS).Computer Vision: Study image and video analysis techniques, including object detection and facial recognition, utilizing Azure's Computer Vision services.Responsible AI: Learn about ethical considerations and best practices for developing and deploying AI solutions responsibly.Exam Preparation: Access practice exams and quizzes designed to mirror the AI-900 certification exam format, helping you assess your readiness and identify areas for improvement.This course provides a comprehensive foundation in AI and Azure services, equipping you with the knowledge and skills needed to succeed in the AI-900 certification exam.

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What you'll learn

  • Understand fundamental AI principles including machine learning and deep learning
  • Gain knowledge about Azure's AI services such as Cognitive Services and Azure Bot Services
  • Learn how to build and deploy machine learning models on Azure
  • Implement natural language processing techniques using Azure tools

Course objectives

  • Prepare effectively for the AI-900 certification exam
  • Identify knowledge gaps and focus on key areas for improvement
  • Familiarize yourself with ethical practices in AI development
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