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How to book the AI-900: Microsoft Azure AI Fundamentals Exam

• Step 1: Visit to Microsoft Learning and search for AI-900: Microsoft Azure AI Fundamentals Exam Outlook and Modules.
• Step 2: Sign up/Login to Pearson VUE account.
• Step 3: Select local centre based on your country, date, time and confirm with a payment method.

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Introducing Updated Microsoft Certified: Azure AI Fundamentals Designation

This certificate is an opportunity for candidates to showcase their mastery of the Machine Learning (ML) and Artificial Intelligence (AI) workloads and their implementation of Azure services. For that reason, AI-900 exam can be taken by all candidates from technical and non-technical fields. While software engineering and data science skills may not be required for such an evaluation, it is important to have general programming knowledge to stand a chance of cracking this test right away. By and large, the updated Microsoft Certified: Azure AI Fundamentals designation can help you advance your career growth by preparing you for advanced Azure role-based certifications including the Microsoft Certified: Azure AI Engineer Associate and the Microsoft Certified: Azure Data Scientist Associate certificates.

Exam Topics

The potential candidates for this certification test must develop their skills in its topics before attempting it. It is recommended to go through the official webpage to review the detailed objectives. Microsoft updates the topics of its exams regularly, so studying the latest domains is very important to your success in the test. Thus, Microsoft AI-900 covers the following sections:

Describe AI Considerations and Workloads (15-20%)

The first topic evaluates the following skills:

• Identify the guiding principles associated with responsible Artificial Intelligence – This one will evaluate the candidates’ ability to explain some concepts. These include considerations of safety and reliability in AI solutions and considerations for fairness in AI solutions. It also covers considerations for security and privacy, transparency, inclusiveness, and accountability within an AI solution.
• Identify the common AI Workloads features – You should be able to identify a variety of workloads, such as forecasting/prediction, computer vision, and conversational AI. The subsection also covers the characteristics of anomaly detection workloads, knowledge mining, and natural language processing workloads.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

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Microsoft AI-900 Exam Syllabus Topics: