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| Section | Weight | Objectives |
|---|---|---|
| Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
| Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|
| Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|
| Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
>> AI-900 Exam Lab Questions <<
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NEW QUESTION # 302
Your company is exploring the use of voice recognition technologies in its smart home devices. The company wants to identify any barriers that might unintentionally leave out specific user groups.
This an example of which Microsoft guiding principle for responsible AI?
Answer: A
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Responsible AI Framework, Inclusiveness is one of the six guiding principles for responsible AI. The principle of inclusiveness ensures that AI systems are designed to empower everyone and engage people of all abilities. Microsoft emphasizes that inclusive AI systems must be developed with awareness of potential barriers that could unintentionally exclude certain user groups. This directly aligns with the scenario described-where the company is examining voice recognition technologies in smart home devices to identify barriers that might leave out users, such as those with speech impairments, accents, or language differences.
The official Microsoft Learn module "Identify guiding principles for responsible AI" explains that inclusiveness focuses on creating systems that can understand and serve users with diverse needs. For example, voice recognition models should account for variations in dialect, tone, accent, and speech patterns to ensure equitable access for all. A lack of inclusiveness could cause bias or misrecognition for underrepresented groups, leading to unintentional exclusion.
Microsoft's guidance further stresses that designing for inclusiveness involves involving diverse users in the data collection and testing phases, conducting accessibility assessments, and continuously improving model performance across different demographic groups. In this way, inclusiveness promotes fairness, accessibility, and usability across cultural and physical differences.
In contrast:
* A. Accountability is about ensuring humans are responsible for AI outcomes.
* B. Fairness focuses on preventing bias and discrimination in data or algorithms.
* D. Privacy and security ensure protection of personal data and secure handling of information.
Thus, evaluating potential barriers that could exclude specific user groups exemplifies Inclusiveness, as it demonstrates a proactive approach to making AI accessible and beneficial for all users.
NEW QUESTION # 303
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
NEW QUESTION # 304
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer#deploy
NEW QUESTION # 305
Which two tools can you use to call the Azure OpenAI service? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.
Answer: C,D
Explanation:
The correct answers are B. Azure REST API and C. Azure SDK for Python.
The Azure OpenAI Service can be accessed using multiple development interfaces. According to Microsoft Learn documentation, developers can call the service via the Azure REST API, which provides direct HTTPS- based access to the model endpoints for tasks like completions, chat, embeddings, and image generation. This interface is platform-independent and supports integration with any system capable of making HTTP requests.
Additionally, Azure SDKs offer higher-level libraries for convenient integration into applications. The Azure SDK for Python and Azure SDK for JavaScript are both supported for Azure OpenAI interaction, allowing developers to authenticate with Azure credentials, send prompts, and receive model responses programmatically.
However, among the listed options, the REST API (B) and SDK for Python (C) are most explicitly referenced in the AI-900 learning modules and Microsoft documentation as standard tools to call Azure OpenAI services.
Option A (Azure CLI) is incorrect because the CLI is used primarily for provisioning and managing Azure resources, not for directly calling OpenAI model endpoints.
Therefore, based on the Azure AI-900 and OpenAI integration guidance, the correct answers are B. Azure REST API and C. Azure SDK for Python.
NEW QUESTION # 306
Match the services to the appropriate descriptions.
To answer, drag the appropriate service from the column on the left to its description on the right. Each service may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point
Answer:
Explanation:
Explanation
Graphical user interface, application Description automatically generated.
NEW QUESTION # 307
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