P.S. Fast2test在Google Drive上分享了免費的、最新的AB-731考試題庫：https://drive.google.com/open?id=1s8Lzo6lQ5iLnsu49l_zVxbKOUGe6vHwj
Fast2test提供的AB-731考古題是最全面的學習資料，這是一個可以讓您高效高速的掌握知識的題庫寶典。我們提供的Microsoft AB-731模擬測試題及答案和真實考試的題目及答案有95%的相似性，能保證您100%通過AB-731認證考試，滿足廣大考生需求。當您真的了解我們產品的可靠性之后，您會毫不猶豫的購買它，因為Microsoft AB-731是您最好的選擇，甚至是您未來職業生涯成功不可缺少的。
| 主題 | 簡介 |
|---|---|
| 主題 1 |
|
| 主題 2 |
|
| 主題 3 |
|
如果你選擇了Fast2test，Fast2test可以確保你100%通過Microsoft AB-731 認證考試，如果考試失敗，Fast2test將全額退款給你。
問題 #58
Hotspot Question
Select the answer that correctly completes the sentence.
答案：
解題說明：
問題 #59
Your company has an AI solution that uses a prebuilt Azure OpenAI model to generate content.
You need to reduce the cost of solution while minimizing the impact on the quality of the generated output.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
答案：C,D
解題說明：
To reduce costs for a prebuilt Azure OpenAI model while maintaining high output quality, you should implement a combination of prompt optimization, caching, and model selection strategies.
[C]
1. Optimize Prompt Engineering
Reducing the number of tokens processed is the most direct way to lower costs.
Prompt Compression: Use tools like LLMLingua to remove redundant text from prompts without losing semantic meaning.
Task Decomposition: Break complex tasks into smaller, focused prompts to improve clarity and reduce expensive retries.
Shorten Context: Summarize long conversation histories or external RAG (Retrieval-Augmented Generation) documents before sending them to the model.
2. Implement Caching Mechanisms
[A]
3. Use Model Routing and Tiering
Matching request complexity to model capability can reduce costs by 30-60%.
*-> Model Cascading: Use a small, cheap model (e.g., GPT-4o-mini) for simple tasks like classification or basic formatting. Route only complex reasoning tasks to high-end models like GPT-4o.
Reasoning Effort Control: For newer models like GPT-5, adjust the reasoning_effort parameter to
"minimal" for straightforward tasks to save on compute.
Reference:
https://ekaivakriti.com/blog/how-to-reduce-openai-costs-by-60-percent/
問題 #60
HOTSPOT - Select the answer that correctly completes the sentence.
You use __________ to train a model that will forecast product demand based on historical sales data.
答案：
解題說明：
Explanation:
Azure Machine Learning
Forecasting product demand from historical sales data is a predictive analytics / machine learning use case.
It typically requires selecting an appropriate forecasting approach (for example, regression, tree-based methods, or time-series models), preparing and splitting historical data, training and validating the model, tuning hyperparameters, and then deploying the model for ongoing inference. The Microsoft service designed to support that end-to-end ML lifecycle is Azure Machine Learning , which is why it correctly completes the sentence.
Azure Machine Learning provides the tooling and infrastructure to: manage datasets, run training jobs on scalable compute, track experiments, compare model performance, register models, and operationalize them through managed endpoints and pipelines. This makes it well-suited for iterative forecasting work, where you may retrain on new data regularly, monitor drift, and update models as product lines, promotions, or seasonality patterns change.
The other options do not directly fit "train a model" for forecasting. Azure AI Search is an indexing/retrieval service used to search and ground generative AI responses, not for training predictive models. Azure OpenAI provides access to large language and multimodal models for generative tasks (drafting, summarizing, Q & A) and is not the primary platform for building classical forecasting models. Microsoft Foundry is a broader platform experience for building and governing AI apps and agents, but the specific service for training a forecasting model on historical sales data is Azure Machine Learning.
問題 #61
HOTSPOT - For each of the following statements, select Yes if the statement is true. Otherwise, select No .
NOTE: Each correct selection is worth one point.
答案：
解題說明：
Explanation:
The answer Area
* You can use Azure Language in Foundry Tools to analyze the sentiment of customer reviews. Answer:
Yes
* You can use Azure Language in Foundry Tools to translate internal reports into multiple languages.
The answer: No
* You can use Azure Language in Foundry Tools to extract text from scanned documents. Answer: No Azure Language is designed for natural language processing (NLP) over text that is already machine- readable. That includes capabilities like sentiment analysis , key phrase extraction, entity recognition, summarization, and classification. Therefore, statement 1 is Yes : sentiment analysis of customer reviews is a standard NLP workload where the service scores text as positive/negative/neutral (and often provides confidence scores), helping organizations quantify customer satisfaction and detect recurring issues.
Statement 2 is No because translation is typically handled by a dedicated translation capability (commonly delivered as a separate translator service) rather than the core "Language" NLP features. While translation is an AI language workload, it's not what the Azure Language service is primarily used for in this context; the expected Microsoft service choice for multi-language translation is the translator capability, not Azure Language.
Statement 3 is No because extracting text from scanned documents is OCR (optical character recognition), which is a computer vision/document processing function. OCR is delivered through Azure Vision and/or Azure Document Intelligence , which can read printed/handwritten text from images and PDFs and return structured output. Azure Language can analyze extracted text after OCR, but it does not perform the image-to- text extraction step itself.
問題 #62
Drag and Drop Question
Match the business scenario to the appropriate AI solution design approach.
To answer, drag the AI solution from the column on the left to its business scenario on the right.
Each solution may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
答案：
解題說明：
Explanation:
Box 1: Build with Microsoft Copilot Studio
The marketing department at your company wants AI to summarize emails and create presentations.
Building an AI solution to summarize emails and create presentations using Microsoft Copilot Studio involves creating custom AI agents that leverage your company's Microsoft 365 data (emails, documents) to automate these workflows. Copilot Studio allows you to create, test, and publish conversational agents that can be integrated into Microsoft Teams or directly into Office apps.
Box 2: Use Microsoft 365 Copilot
The HR department at your company wants a conversational agent for policy questions and leave request.
A company can use Microsoft 365 Copilot to create a conversational agent for policy questions and leave requests, primarily by leveraging Copilot Studio to customize agents with specific organizational data. These agents can function within Microsoft Teams, providing a self-service,
24/7 interface for employees.
Box 3: Build with Azure Machine Learning
The manufacturing department at your company wants AI to predict maintenance schedules.
Azure Machine Learning (Azure ML) is a powerful, cloud-based platform that helps companies shift from reactive or scheduled maintenance to predictive maintenance, which optimizes maintenance schedules based on actual equipment health.
By leveraging IoT sensors, historical data, and AI, Azure ML enables organizations to forecast equipment failures before they occur, reducing downtime and maintenance costs.
Box 4: Extend with Microsoft 365 Copilot connectors
The finance department at your company wants AI-powered access to enterprise resource planning (ERP) data by using familiar productivity tools You can extend Microsoft 365 Copilot with connectors to enable AI-powered access to enterprise resource planning (ERP) data directly within productivity tools like Outlook, Teams, and Excel.
This integration allows users to query, summarize, and act on data from systems such as SAP, Oracle, and Dynamics 365 without switching between applications.
Reference:
https://techcommunity.microsoft.com/blog/azurecommunicationservicesblog/build-your-ai-email- agent-with-microsoft-copilot-studio/4448724
https://adoption.microsoft.com/en-us/scenario-library/human-resources/leave-of-absence- compliance-agent
https://learn.microsoft.com/en-us/azure/documentdb/solutions-iot
https://www.mtlc.co/how-to-unlock-the-power-of-microsoft-365-copilot-connectors
問題 #63
......
面對職場的競爭和不景氣時期，提升您的專業能力是未來最好的投資，而獲得Microsoft AB-731認證對于考生而言有諸多好處。相對于考生尋找工作而言，一張AB-731認證可以倍受企業青睞，為您帶來更好的工作機會。但是如何輕松拿到AB-731認證哪？ Fast2test的AB-731考古題是通過考試最有效的方式之一，我們提供在線測試引擎的題庫，可以讓您模擬真實的考試情景，快速讓考生掌握知識點并應用。AB-731題庫資料包含真實的考題體型，100%幫助考生通過考試。
AB-731最新考古題: https://tw.fast2test.com/AB-731-premium-file.html
順便提一下，可以從雲存儲中下載Fast2test AB-731考試題庫的完整版：https://drive.google.com/open?id=1s8Lzo6lQ5iLnsu49l_zVxbKOUGe6vHwj