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首页AI-900认证考试:提升效率与自动化应对策略
"AI-900认证考试指南提供了深入理解人工智能基础知识的重要资源。本考试旨在评估考生对人工智能(AI)及其应用的理解,特别是针对客户服务领域的自动化解决方案。以下是两个典型考题涉及的知识点: 1. 题目:公司通过电话和电子邮件支持团队处理客户服务,为解决常见问题开发了网页聊天机器人。创建这个解决方案带来的商业利益是B.减少了客户服务代理的工作负担。由于机器人可以自动回答常见问题,员工不再需要花费大量时间在重复性任务上,从而提高了工作效率,使得客服团队能专注于更复杂的问题。 2. 题目:在机器学习项目中,数据分割对于训练和评估模型至关重要。正确的方法是B.随机将数据分为训练集和测试集。这样可以确保数据的代表性,避免模型过度拟合或欠拟合,有助于评估模型在未见过的数据上的性能。 SplitData模块在这个过程中扮演着关键角色,它允许用户根据需要将数据随机划分为训练和测试两部分,确保模型在实际应用中的稳定性和有效性。正确划分数据集有助于提高机器学习项目的成功率。 总结起来,AI-900认证考试考察了考生对人工智能技术的基础概念、客户服务自动化工具的应用以及数据预处理和模型验证的最佳实践。准备此类考试时,不仅需要掌握理论知识,还要熟悉实际操作中的应用场景,以便在考试中展现全面的技能和理解。"
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Topic 1
Question #20
DRAG DROP -
Match the principles of responsible AI to appropriate requirements.
To answer, drag the appropriate principles from the column on the left to its requirement on the right. Each principle may be used once, more than
once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:
Correct Answer:
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai https://docs.microsoft.com/en-
us/learn/modules/responsible-ai-principles/4-guiding-principles
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Topic 1
Question #21
DRAG DROP -
You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.
Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of
processes to the answer area and arrange them in the correct order.
Select and Place:
Correct Answer:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines
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Topic 1
Question #22
You are building an AI-based app.
You need to ensure that the app uses the principles for responsible AI.
Which two principles should you follow? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Implement an Agile software development methodology
B. Implement a process of AI model validation as part of the software review process
C. Establish a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy
ocer
D. Prevent the disclosure of the use of AI-based algorithms for automated decision making
Correct Answer:
BC
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai https://docs.microsoft.com/en-
us/learn/modules/responsible-ai-principles/3-implications-responsible-ai-practical
Community vote distribution
BC (100%)
Topic 1
Question #23
HOTSPOT -
To complete the sentence, select the appropriate option in the answer area.
Hot Area:
Correct Answer:
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
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Topic 1
Question #24
HOTSPOT -
Select the answer that correctly completes the sentence.
Hot Area:
Correct Answer:
Fairness is a core ethical principle that all humans aim to understand and apply. This principle is even more important when AI systems are
being developed. Key checks and balances need to make sure that the system's decisions don't discriminate or run a gender, race, sexual
orientation, or religion bias toward a group or individual.
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
![](https://csdnimg.cn/release/download_crawler_static/88895351/bg14.jpg)
Topic 1
Question #25
DRAG DROP -
Match the types of AI workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once,
more than once, or not at all.
NOTE: Each correct selection is worth one point.
Select and Place:
Correct Answer:
Box 1: Knowledge mining -
You can use Azure Cognitive Search's knowledge mining results and populate your knowledge base of your chatbot.
Box 2: Computer vision -
Box 3: Natural language processing
Natural language processing (NLP) is used for tasks such as sentiment analysis.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing
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