Exam AI-900: Microsoft Azure AI Fundamentals
| Exam Number: AI-900 | Length of test: 120 mins |
| Exam Name: Microsoft Azure AI Fundamentals | Number of questions in the actual exam: 40-60 |
| Format: PDF, VPLUS | Passing Score: 700/1000 |
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Total Questions: 275 $30 Premium PDF file 2 months updates Last updated: March-2025 |
Total Questions: 275 FREE Premium VPLUS file Last updated: March-2025 |
Download practice test questions
| Title | Size | Hits | Download |
|---|---|---|---|
| Microsoft.AI-900.vSep-2024.by.Ando.98q | 2.51 MB | 262 | Download |
| Microsoft.AI-900.vSep-2024.by.Ando.98q | 3.38 MB | 107 | Download |
| Microsoft.AI-900.vFeb-2024.by.VCEplus.110q | 4.61 MB | 253 | Download |
| Microsoft.AI-900.vJul-2024.by.Pandoie.178q | 5.92 MB | 226 | Download |
| Microsoft.AI-900.vApr-2024.by.ToanNguyen.116q | 4.47 MB | 261 | Download |
Study guide for Exam AI-900: Microsoft Azure AI Fundamentals
Audience profile
This exam is an opportunity for you to demonstrate knowledge of machine learning and AI concepts and related Microsoft Azure services. As a candidate for this exam, you should have familiarity with Exam AI-900’s self-paced or instructor-led learning material.
This exam is intended for you if you have both technical and non-technical backgrounds. Data science and software engineering experience are not required. However, you would benefit from having awareness of:
- Basic cloud concepts
- Client-server applications
You can use Azure AI Fundamentals to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.
Skills at a glance
- Describe Artificial Intelligence workloads and considerations (15–20%)
- Describe fundamental principles of machine learning on Azure (20–25%)
- Describe features of computer vision workloads on Azure (15–20%)
- Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)
- Describe features of generative AI workloads on Azure (15–20%)
Describe Artificial Intelligence workloads and considerations (15–20%)
- Identify features of common AI workloads
- Identify guiding principles for responsible AI
Describe fundamental principles of machine learning on Azure (20–25%)
- Identify common machine learning techniques
- Describe core machine learning concepts
- Describe Azure Machine Learning capabilities
Describe features of computer vision workloads on Azure (15–20%)
- Identify common types of computer vision solution
- Identify Azure tools and services for computer vision tasks
Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)
- Identify features of common NLP Workload Scenarios
- Identify Azure tools and services for NLP workloads
Describe features of generative AI workloads on Azure (15–20%)
- Identify features of generative AI solutions
- Identify capabilities of Azure OpenAI Service
AI 900 valid?
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Exam AI-900 is valid now.
You should learn it.
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