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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-901 |
| Passing Score: | 700 |
| Certificate Validity Period: | Lifetime |
| Exam Price: | $99 USD |
| Exam Format: | Case studies, Multiple select, Multiple choice |
| Available Languages: | Chinese (Simplified), Korean, Portuguese (Brazil), Italian, French, Russian, Japanese, Arabic (Saudi Arabia), Indonesian (Indonesia), English, Chinese (Traditional), German, Spanish |
| Real Exam Qty: | 30-40 |
| Exam Duration: | 60 minutes |
| Recommended Training: | Microsoft Learn: Get started with Microsoft Foundry Microsoft Learn: AI concepts for developers and technology professionals |
| Exam Registration: | Pearson VUE Scheduling Microsoft Certification Exam Registration |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | No required prerequisites; basic understanding of cloud computing and familiarity with Python syntax recommended |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-901/ |
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| Topic | Details |
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NEW QUESTION # 50
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Box: natural language processing
The interactive answering of questions entered by a user as part of an application is a direct example of natural language processing (NLP).
How NLP Powers Interactive Q&A
Text interpretation: The system uses linguistic rules and machine learning models to read and interpret the user's typed input.
Intent recognition: It figures out what the user wants or needs by analyzing the meaning behind the words.
Response generation: It formulates and delivers a human-like reply back through the application interface.
Reference:
https://www.gauthmath.com/solution/1800845210023942/The-interactive-answering-of-questions-entered-by-a-user-as-part-of-an-applicati
NEW QUESTION # 51
Drag and Drop Question
You have a Microsoft Foundry project named project1 that contains an Azure OpenAI resource named Resource1.
To Resource1, you deploy a gpt-4.1-mini model by using a model deployment named my-mini- gpt.
You need to connect to my-mini-gpt from an application.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 52
Which type of compute resource should you use to attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning?
Answer: C
Explanation:
To attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning, you should use the "Attached Compute" or "Kubernetes Compute Target". This allows you to leverage your existing AKS cluster as a compute resource for your machine learning tasks within Azure Machine Learning. You can achieve this using the Azure CLI v2, Python SDK v2, or Machine Learning Studio UI.
1. Kubernetes Compute Target:
Azure Machine Learning treats your AKS cluster as a compute target, allowing you to specify it as the location for running your training jobs or deploying models.
2. Attached Compute:
This refers to the ability to connect existing compute resources, like your AKS cluster, to your Azure Machine Learning workspace.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-to-workspace
NEW QUESTION # 53
What should you use to compare benchmark metrics of different AI models?
Answer: C
Explanation:
To compare benchmark metrics across Azure AI models, navigate to the Azure AI Foundry portal, explore the model catalog, and use the benchmarking tools to assess model performance. You can then compare these metrics to choose the most suitable model for your needs.
Reference:
https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/benchmark-model-in-catalog
NEW QUESTION # 54
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Box: analyzes images to detect
A multimodal model analyzes images to detect, recognize, and reason about objects by combining computer vision with natural language processing.
Reference:
https://farukalamai.substack.com/p/object-detection-with-multimodal
NEW QUESTION # 55
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