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High level of difficulty and many challenging questions. Identify the different types of AI models. AI design choosing tools. Who should take the exam? Artificial intelligence. Describe the strengths and weaknesses for artificial intelligence.
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Microsoft AI-900 or Microsoft Azure AI Fundamentals Exam is a certification exam that focuses on the fundamentals of Artificial Intelligence (AI) and its applications in Microsoft Azure. AI-900-KR exam is designed for individuals who want to explore the basics of AI and understand how it can be integrated into various applications. AI-900-KR exam covers topics such as machine learning, cognitive services, natural language processing, and computer vision.
| Sample Questions | Microsoft Azure AI Fundamentals Sample Questions |
| Books / Training | Course AI-900T00: Microsoft Azure AI Fundamentals |
| Schedule Exam | Pearson VUE |
| Exam Name | Microsoft Certified - Azure AI Fundamentals |
| Number of Questions | 40-60 |
| Exam Code | AI-900 |
| Passing Score | 700 / 1000 |
| Duration | 60 mins |
| Exam Price | $99 (USD) |
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Artificial Intelligence workloads and considerations | 15–20% | - Describe considerations for developing AI solutions - Identify types of AI workloads - Describe responsible AI principles |
| Topic 2: Fundamental principles of machine learning on Azure | 15–20% | - Describe automated machine learning - Describe core concepts of machine learning - Describe machine learning pipelines - Describe capabilities of Azure Machine Learning |
| Topic 3: Features of generative AI workloads on Azure | 20–25% | - Describe generative AI concepts - Describe use cases for generative AI - Describe capabilities of Azure OpenAI Service - Describe responsible AI practices for generative AI |
| Topic 4: Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Face - Identify types of computer vision solutions |
| Topic 5: Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Language - Describe capabilities of Azure Translator - Identify types of NLP solutions - Describe capabilities of Azure Speech |
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