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Updated: Sep 05, 2026
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Microsoft AI-900 exam covers a wide range of topics related to AI and machine learning, including machine learning workloads, computer vision workloads, natural language processing workloads, and conversational AI workloads. Candidates will be tested on their understanding of the key concepts and terminology related to these topics, as well as their ability to use the Azure AI services to build intelligent solutions.
Microsoft AI-900 Certification Exam is an important credential for individuals who are looking to establish themselves as experts in the field of AI. It is recognized by a number of organizations and can be used to demonstrate an individual's knowledge and understanding of AI concepts and their applications. Additionally, individuals who hold this certification are more likely to be considered for career opportunities in the field of AI and data science.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
Microsoft AI-900 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Certificate Validity Period: | Valid indefinitely |
| Available Languages: | Chinese (Simplified), Italian, Japanese, English, Spanish, Arabic (Saudi Arabia), Korean, Portuguese (Brazil), French, German, Russian, Indonesian (Indonesia), Chinese (Traditional) |
| Related Certifications: | Microsoft Certified: Azure Data Fundamentals Microsoft Certified: Azure Fundamentals |
| Exam Duration: | 45 minutes |
| Exam Format: | Multiple choice, Scenario-based questions, Multiple select |
| Passing Score: | 700 (on a scale of 1–1000) |
| Exam Price: | $99 USD |
| Real Exam Qty: | 40–60 |
| Recommended Training: | Instructor-led Training: AI-900 Course Microsoft Learn: Azure AI Fundamentals Learning Path |
| Exam Registration: | Microsoft Certification Registration Pearson VUE Registration |
| Sample Questions: | Microsoft AI-900 Sample Questions |
| Exam Way: | Online proctored or onsite testing at Pearson VUE test centers |
| Pre Condition: | No required prerequisites; basic familiarity with cloud computing or AI concepts is recommended but not mandatory |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900/ |
Career Prospects
Although the Microsoft AI-900 exam is associated with the foundational-level certification, all the successful candidates can pursue various lucrative career paths in the field of IT. Some of the job roles that these professionals can work in include a Data Scientist, a Software Developer, and an Azure AI Engineer, among others. They can also proceed to get some other role-based certificates to boost their potential in the world of Information Technology. With the Microsoft Certified: Azure AI Fundamentals certification, you can earn an average of $48,000 per annum as an entry-level specialist. Those with some work experience can get an average of $74,000 per year.
Microsoft AI-900 exam is an excellent opportunity for individuals who want to learn about AI and its applications in Azure. Microsoft Azure AI Fundamentals certification validates their knowledge of AI concepts and Azure services that support AI. Passing AI-900 exam can also open doors to new career opportunities in the AI industry, as more and more companies are adopting AI technologies to improve their business processes.
Microsoft AI-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Computer Vision - Identify types of computer vision solutions - Describe capabilities of Azure Face - Describe capabilities of Azure Form Recognizer |
| 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 |
| 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 |
| Artificial Intelligence workloads and considerations | 15–20% | - Describe considerations for developing AI solutions - Describe responsible AI principles - Identify types of AI workloads |
| Features of generative AI workloads on Azure | 20–25% | - Describe use cases for generative AI - Describe capabilities of Azure OpenAI Service - Describe responsible AI practices for generative AI - Describe generative AI concepts |
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