Exam Name: Microsoft Azure AI Fundamentals
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Azure AI Fundamentals
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Microsoft AI-901 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
| Exam Number: | AI-900 |
| Real Exam Qty: | 40-60 |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Exam Duration: | 60 minutes |
| Available Languages: | French, English, German, Korean, Chinese (Traditional), Spanish, Japanese, Portuguese (Brazil), Chinese (Simplified) |
| Passing Score: | 700 (out of 1000) |
| Exam Price: | Approx. 99 USD (varies by region) |
| Exam Format: | Case study (limited), Multiple response, Multiple choice, Drag and drop |
| Related Certifications: | Microsoft Azure Fundamentals (AZ-900) Microsoft Azure Data Fundamentals (DP-900) |
| Recommended Training: | Azure AI Fundamentals Course Microsoft Learn - AI-900 Learning Path |
| Exam Registration: | Schedule exam via Pearson VUE Microsoft Certification Portal |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored exam or in-person test center |
| Pre Condition: | No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/ |
Microsoft AI-901 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Describe features of computer vision workloads on Azure | 15-20% | - Azure AI Vision services
|
| Describe features of generative AI workloads on Azure | 10-15% | - Azure OpenAI and generative services
|
| Describe fundamental principles of machine learning on Azure | 25-30% | - Machine learning concepts
|
| Describe Artificial Intelligence workloads and considerations | 20-25% | - Identify features of common AI workloads
|
| Describe features of natural language processing (NLP) workloads on Azure | 15-20% | - Text analysis
|
Microsoft Azure AI Fundamentals Exam FAQ — Smart Answers
Yes:
Courses build the foundation; then practice smartly with the 132 practice questions for the Microsoft Azure AI Fundamentals — every answer expert-verified.
The Microsoft Azure AI Fundamentals is Microsoft's certification exam for Microsoft Azure AI Fundamentals, at the Fundamentals level. It validates skills employers hire for, which is why it can affect your career and future. Related credentials include Microsoft Azure Data Fundamentals (DP-900), Microsoft Azure Fundamentals (AZ-900).
Files arrive by automatic email within a minute of payment — unlimited installations, and 24/7 customer assisting for any login or downloading issues if nothing shows up within 2 hours. If you fail the corresponding AI-901 exam within 60 days of purchase, you have options: a full refund (send a scanned enrollment slip plus the official Score Report PDF within 2 days of the exam; processed within 7 days), waiting for the next updated version free, or changing to two other equal-value dumps free. Excluded: exams within 3 days of purchase, candidate names that don't match the payer, and free or expired products.
No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended. Vendors revise eligibility rules from time to time, so verify the current requirements on the official page (official AI-901 exam page) before booking.
The Microsoft Azure AI Fundamentals blueprint covers 5 domains — including Describe features of computer vision workloads on Azure (15-20%), Describe fundamental principles of machine learning on Azure (25-30%), Describe Artificial Intelligence workloads and considerations (20-25%). The weightings tell you where to spend your hours; the complete outline above lists every subtopic.
Through the vendor's official registration channels:
The Microsoft Azure AI Fundamentals is delivered Online proctored exam or in-person test center — choose the arrangement that fits you when booking.
Approx. 99 USD (varies by region) per attempt, 700 (out of 1000) to pass. A retake bills the full fee again, so prepare smartly: work through the 132 practice questions for the AI-901 exam at TestKingIT before you book.
60 minutes for 40-60 questions. Efficient preparation includes pacing: rehearse timed sets until the clock feels manageable, not menacing.
Yes — download the free Microsoft Azure AI Fundamentals demo and judge the quality before paying. Purchases include 365 days of free updates, with each latest version emailed to you immediately; renew afterward at 50% off.
Microsoft Azure AI Fundamentals Sample Questions:
For each of the following statements, Select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Statement 1: To process prompts that contain images, you must deploy a multimodal generative AI model. = Yes Image prompts require a vision-enabled or multimodal model. A text-only model cannot interpret image content.
Statement 2: In the Foundry playground, you can provide an image by uploading a local file or by specifying a publicly accessible URL. = Yes The Foundry playground for vision-capable models supports adding image input to a prompt, including local uploads and image URLs.
Statement 3: A multimodal model can interpret multiple images included in a single prompt. = Yes Vision-enabled multimodal models can accept image content items in a prompt, and multiple images can be included for the model to analyze together.
Select the answer that correctly completes the sentence.
Correct Answer:
Explanation:
When using the OpenAI Responses API and a vision-enabled model, you can include an image in a request by providing the image as a base64-encoded image data.
Azure OpenAI / Microsoft Foundry vision requests support image input as an input_image item. The image can be provided by URL or as base64-encoded image data in the request. Microsoft documentation for Azure OpenAI batch examples also lists Base64 encoded image and Image URL as supported input patterns for Responses API requests.
The other options are incorrect:
a CSV file attachment is not an image input format for vision analysis.
an MP4 video stream is video content, not an image format.
a shared access signature (SAS) token is only an access token for a protected resource; it is not the image data itself.
Select the answer that correctly completes the sentence.
Correct Answer:
Explanation:
The correct answer is endpoint of the model. After a vision-enabled GPT model is deployed in Microsoft Foundry, the deployment exposes an inference endpoint that applications can call programmatically. The application sends requests containing text and, when required, image content to the deployed model through the appropriate chat-completions API endpoint. Microsoft's documentation explicitly states that to use vision- enabled models, you call the Chat Completion API against a supported model that has been deployed.
The Foundry playground is primarily an interactive environment for testing prompts, model behavior, and multimodal inputs during development. It is not the production interface that an external application uses to submit inference requests. An evaluation pipeline is used to assess model or application quality against defined metrics and datasets, while a training dataset is associated with model training or fine-tuning rather than serving inference traffic.
Microsoft Foundry provides the endpoint and required authentication information after deployment.
Applications then invoke that endpoint using an SDK or REST API, passing text and image inputs as part of the request payload.
You have a Microsoft Foundry project that contains a vision-enabled model deployment. You need to create a prompt that ensures the model produces a relevant and useful response. What should you include in the prompt?
- A. a dataset ID for the image
- B. a description of the task
- C. the version number of the model
- D. the deployment name of the model
Correct Answer: B 🗳️
Explanation: Only visible for TestKingIT members. You can sign-up / login (it's free).
You are developing a simple application that uses the Microsoft Foundry SDK to send chat prompts to a model.
Which three elements should you provide in the code to run the application? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. the model deployment name
- B. the task type
- C. the endpoint URL
- D. the Foundry project display name
- E. credentials
Correct Answer: A,C,E 🗳️
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