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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
| Exam Number: | AI-900 |
| Available Languages: | French, Chinese (Simplified), Chinese (Traditional), Portuguese (Brazil), English, Japanese, Korean, German, Spanish |
| Passing Score: | 700 (out of 1000) |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Exam Format: | Multiple response, Drag and drop, Multiple choice, Case study (limited) |
| Exam Price: | Approx. 99 USD (varies by region) |
| Real Exam Qty: | 40-60 |
| Exam Duration: | 60 minutes |
| 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: | Microsoft AI-901 Sample Questions |
| 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/ |
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NEW QUESTION # 80
Based on the image provided, here is the transcribed text:
You need to build an AI solution that produces new product images based on written descriptions provided by users.
Which AI workload should you use?
Answer: D
Explanation:
The requirement is to produce new product images based on written descriptions. This is an image generation workload, because the AI system is creating entirely new images from natural language prompts.
NEW QUESTION # 81
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: Generating a response to a user prompt occurs during the inference stage. = Yes When a deployed generative AI model receives a user prompt and generates an output, that process is called inference . The model is being used to produce a response, not being trained.
Statement 2: A generative AI model generates responses by copying stored documents directly from the model's training data. = No Generative AI models do not normally respond by simply copying stored documents from training data. They generate outputs based on learned statistical patterns. In some cases, models may reproduce memorized content, but that is not the normal or intended generation mechanism.
Statement 3: A generative AI model produces output by predicting the next token based on patterns learned from the model's training data. = Yes This is correct. Large language models generate text by predicting likely next tokens based on the prompt and learned patterns from training.
NEW QUESTION # 82
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Evaluating model outcomes across demographic groups to reduce bias is an example of the Microsoft responsible AI principle of fairness .
The Microsoft responsible AI principle of fairness means AI systems should treat all people fairly and avoid unfair bias or discrimination across groups.
The other options are incorrect:
accountability means people and organizations remain responsible for AI systems and their effects.
privacy and security focuses on protecting data and controlling access.
transparency means users should understand when and how AI is being used, including system capabilities and limitations.
NEW QUESTION # 83
For each of the following statements, select if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 84
You are developing a system to predict the prices of insurance for drivers in the United Kingdom. You need to minimize unintended bias in the system. What should you do?
Answer: B
Explanation:
To minimize unintended bias, the training data should be representative of the population for which the model will be used. Microsoft responsible AI guidance identifies fairness as a key principle and notes that discrepancies can occur when systems underperform for specific demographic groups or rarely observed input conditions in training data.
A global insurance dataset may not represent UK drivers. A completely random sample may still underrepresent important groups. Removing protected characteristics alone does not guarantee fairness, because other fields can act as proxies. The best answer is to use a training sample representative of the target UK population.
NEW QUESTION # 85
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