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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Exam Price: | USD 99 |
| Exam Duration: | 45-60 |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700 / 1000 |
| Exam Format: | Multiple choice, Multiple select, Scenario-based, Match the service to use case, Drag and drop |
| Certificate Validity Period: | 1 year (renewable via free online assessment on Microsoft Learn) |
| Available Languages: | Korean, Spanish, Russian, French, Italian, Portuguese (Brazil), Japanese, Arabic (Saudi Arabia), Indonesian (Indonesia), English, Chinese (Simplified), Chinese (Traditional), German |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online (remote proctored via Pearson VUE) or at a Pearson VUE test center |
| Pre Condition: | No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900 |
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NEW QUESTION # 107
You need to build an AI solution that responds to user queries with detailed written explanations.
Which type of AI model should you use?
Answer: A
Explanation:
A text generation model is the correct tool when you want an AI solution that responds to user queries with detailed written explanations.
Natural Language: They write clear sentences and paragraphs.
Complex Ideas: They break down hard topics into simple words.
Flexible Format: They can make lists, summaries, or long guides.
NEW QUESTION # 108
You have a Microsoft Foundry project that contains a deployed generative Al model You need to develop an application by using the Microsoft Foundry SDK to send chat prompts to the deployed model Which information must the application include?
Answer: A
Explanation:
To send chat prompts to a deployed model, the application needs authentication credentials, the endpoint URL, and the model deployment name . Microsoft's Foundry SDK guidance shows authentication with credentials, an endpoint, and the model= " model_deployment_name " value when calling a deployed model.
NEW QUESTION # 109
You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You use the Azure OpenAI Responses API to send a prompt to the model.
You need to provide an image for analysis.
Which content item should you include in the request?
Answer: B
Explanation:
When using the Azure OpenAI Responses API with a vision-enabled model, the image must be included as an input image content item. The correct content item type is:
{"type": "input_image", "image_url": image_url}
Microsoft's Azure OpenAI Responses API documentation states that the Responses API supports image inputs, and multimodal requests use structured input content items for the request.
Why the other options are incorrect:
A . image_base64 = Incorrect. Base64 data can be used as the image data format, but the content item type is still input_image.
B . image_generation = Incorrect. This is related to generating images, not providing an image for analysis.
C . output_image = Incorrect. This would refer to generated output, not image input.
D . input_image = Correct.
NEW QUESTION # 110
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement 1: In the new Microsoft Foundry portal, you must fine-tune a model before you can deploy the model. = No Fine-tuning is optional. Microsoft's Foundry model deployment documentation describes deploying Foundry Models directly from the model catalog for inference. It does not require fine-tuning first.
Statement 2: In the new Microsoft Foundry portal, you can test a model from the model catalog only after you deploy the model. = No Microsoft documentation states that some Foundry Tools are available to try via the model catalog without a project , and Foundry playgrounds are used for prototyping and validation before production.
Therefore, the statement using "only after you deploy" is too restrictive.
Statement 3: In the new Microsoft Foundry portal, you can deploy a model from the model catalog only after retraining the model. = No Retraining/fine-tuning is not required before deployment. Microsoft states that after you deploy a Foundry Model, you can interact with it in the Foundry Playground and use it from code, and the deployment workflow starts by selecting a model from the model catalog and choosing Deploy .
NEW QUESTION # 111
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement 1: An AI generative model is retrained before performing each user request. = No A generative AI model is not retrained for every user request. During normal use, the model performs inference: it receives input, processes the prompt, and generates a response based on the deployed model.
Statement 2: An AI agent responds by copying and pasting answers stored in a database. = No An AI agent does not simply copy and paste stored answers. Agents use generative AI models, instructions, context, and optionally tools or connected data sources to reason over user input and produce responses or actions.
Statement 3: An AI agent uses a generative AI model to establish actions based on user input. = Yes This is correct. An AI agent uses a generative AI model together with instructions and available tools to interpret user input, determine the next action, and generate a response.
NEW QUESTION # 112
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