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The Azure AI Fundamentals certification might not be a prerequisite for any other certification levels, however, it can still be used to prepare for multiple Azure-related qualifications including the Microsoft Certified: Azure Data Scientist Associate and the Microsoft Certified: Azure AI Engineer Associate.
In case you're eager to get to know more about artificial intelligence facets & machine learning functions that relate to Microsoft Azure, then you're recommended to opt for AI-900 test.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Features of generative AI workloads on Azure | 20–25% | - Describe use cases for generative AI - Describe responsible AI practices for generative AI - Describe capabilities of Azure OpenAI Service - Describe generative AI concepts |
| Topic 2: Fundamental principles of machine learning on Azure | 15–20% | - Describe capabilities of Azure Machine Learning - Describe automated machine learning - Describe core concepts of machine learning - Describe machine learning pipelines |
| Topic 3: Artificial Intelligence workloads and considerations | 15–20% | - Identify types of AI workloads - Describe considerations for developing AI solutions - Describe responsible AI principles |
| Topic 4: Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Identify types of NLP solutions - Describe capabilities of Azure Language - Describe capabilities of Azure Translator - Describe capabilities of Azure Speech |
| Topic 5: Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Face - Describe capabilities of Azure Form Recognizer - Identify types of computer vision solutions |
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