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Testpdf 考題網覆蓋了真實的 AI-901 考試指南，並根據其編定適合全球考生都能通用的 AI-901 題庫，讓每一位考生都能順利通過 Microsoft AI-901 考試。我們承諾使用 AI-901 考題的考生可以一次通過相關認證考試，對于一次不過的全額退款，避免您的後顧之憂。你現在就可以去網上可以免費下載我們提供的部分關於 Microsoft AI-901 題庫的模擬測試題和答案作為嘗試。

Microsoft AI-901 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Describe Artificial Intelligence workloads and considerations	20-25%	- Identify features of common AI workloads 1. Computer vision use cases 2. Document processing and extraction 3. Natural language processing use cases 4. Conversational AI and chatbots - Responsible AI principles 1. Inclusiveness 2. Privacy and security 3. Fairness 4. Transparency and accountability 5. Reliability and safety
Topic 2: Describe features of computer vision workloads on Azure	15-20%	- Image analysis 1. Image classification 2. Optical character recognition (OCR) 3. Object detection - Azure AI Vision services 1. Azure AI Vision 2. Face detection and analysis (limited use cases)
Topic 3: Describe features of natural language processing (NLP) workloads on Azure	15-20%	- Azure NLP services 1. Azure AI Language 2. Speech services (speech-to-text, text-to-speech) - Text analysis 1. Sentiment analysis 2. Key phrase extraction 3. Language detection
Topic 4: Describe features of generative AI workloads on Azure	10-15%	- Generative AI concepts 1. Prompt engineering basics 2. Responsible use of generative AI 3. Large language models (LLMs) - Azure OpenAI and generative services 1. Azure OpenAI Service capabilities 2. Use cases: chatbots, content generation, summarization
Topic 5: Describe fundamental principles of machine learning on Azure	25-30%	- Azure Machine Learning basics 1. AutoML concepts 2. Azure ML workspace components - Machine learning concepts 1. Training and evaluation concepts 2. Supervised vs unsupervised learning 3. Regression and classification

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最新上傳的新版AI-901題庫上線 &AI-901：Microsoft Azure AI Fundamentals

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最新的 Microsoft Certified: Azure AI Fundamentals AI-901 免費考試真題 (Q33-Q38):

問題 #33
You are developing an application that processes voicemail recordings by using Azure Content Understanding in Foundry Tools. Which feature does Azure Content Understanding use to convert audio to text?

A. key phrase extraction
B. transcription
C. optical character recognition (OCR)
D. Voice Live

答案：B

解題說明：
Azure Content Understanding uses transcription to convert audio content, such as voicemail recordings, into text. Microsoft's Azure Content Understanding audio documentation states that transcription converts conversational audio into searchable and analyzable text-based transcripts.

問題 #34
Your company has thousands of recorded customer support calls in multiple languages stored as audio files in Azure Storage.
You need to generate text transcripts of all the recordings.
Which Azure Speech in Foundry Tools capability should you use?

A. speech to text batch transcription
B. text to speech
C. speech to text real-time transcription
D. speech translation

答案：A

解題說明：
For thousands of recorded support calls stored as audio files in Azure Storage, the correct capability is speech to text batch transcription.
Microsoft states that batch transcription is designed to transcribe a large amount of audio data in storage, including audio files in Azure Blob Storage, and that files can be processed concurrently to reduce turnaround time.
Real-time transcription is for live audio, not large stored batches. Text to speech converts text into audio. Speech translation translates speech between languages, but the requirement is to generate transcripts.

問題 #35
Your company processes customer support emails.
You need to implement an AI solution that automatically identifies mentions of people, organizations, and locations in the emails.
Which text analysis technique should you use?

A. key phrase extraction
B. summarization
C. sentiment analysis
D. Named Entity Recognition (NER)

答案：D

解題說明：
The correct text analysis technique is Named Entity Recognition (NER).
Microsoft defines NER as a feature that identifies and categorizes entities in unstructured text, including people, places, and organizations.
Sentiment analysis detects positive, negative, or neutral opinion. Summarization creates shorter versions of text. Key phrase extraction identifies important phrases, but it does not specifically classify mentions as people, organizations, or locations.

問題 #36
You are using the Azure Speech SDK to develop a Python application that supports real-time spoken conversations.
Which Azure speech class should you use to configure the connection to the Azure Speech service?

A. AuditOutputConfig
B. SpeechSynthesizer
C. AudioConfig

答案：A

問題 #37
You plan to develop an AI application that will read the license plates of motor vehicles by using Azure AI Foundry. What should you use to develop the application?

A. Azure AI Studio
B. Copilot for Microsoft 365
C. GitHub Actions
D. Microsoft Visual Studio Code

答案：A

解題說明：
Azure AI Studio (now Azure AI Foundry) is used to develop an AI application for reading license plates using its tools and models. The platform allows developers to build, customize, and deploy AI agents and applications, including those that process images to extract information like license plate numbers.
Key components of the process
Platform: Azure AI Foundry (formerly Azure AI Studio) is the central platform for building and managing AI applications.
Tools: You can use its integrated development environment (IDE), SDKs, and APIs to develop and customize models.
Models: The platform provides access to a wide range of AI models, including computer vision models capable of optical character recognition (OCR), which can be used to read text from images.
Workflow:
Create an Azure AI Foundry project in Azure.
Use the model catalog to find and deploy a suitable computer vision or OCR model.
Integrate the model into your application using the SDK or API.
For a license plate application, you would feed images to the model, and the model would output the recognized text from the license plate.
Reference:
https://azure.microsoft.com/en-us/products/ai-foundry

問題 #38
......

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[{:section_type=>"html", :content=>"新版AI-901題庫上線, AI-901認證題庫, AI-901題庫分享, AI-901考古題分享, AI-901認證考試\n<a href=\"https://www.testpdf.net/AI-901.html\"><img src=\"https://ts2.mm.bing.net/th?w=500&amp;q=Microsoft%20Azure%20AI%20Fundamentals\"></a>\nTestpdf 考題網覆蓋了真實的 AI-901 考試指南，並根據其編定適合全球考生都能通用的 AI-901 題庫，讓每一位考生都能順利通過 Microsoft AI-901 考試。我們承諾使用 <a href=\"https://www.newdumpspdf.com/AI-901-practice-test.html\">AI-901</a> 考題的考生可以一次通過相關認證考試，對于一次不過的全額退款，避免您的後顧之憂。你現在就可以去網上可以免費下載我們提供的部分關於 Microsoft AI-901 題庫的模擬測試題和答案作為嘗試。<h2>Microsoft AI-901 Exam Syllabus Topics:</h2><table class=\"mytable\" border=\"1\" cellpadding=\"1\" cellspacing=\"1\" style=\"width: 100%; border-color: #E0E0E0;\"><tbody>\n<tr>\n<th>Section</th>\n<th>Weight</th>\n<th>Objectives</th>\n</tr>\n<tr>\n<td>Topic 1: Describe Artificial Intelligence workloads and considerations</td>\n<td>20-25%</td>\n<td>- Identify features of common AI workloads <ul>\n<li>1. Computer vision use cases<ul></ul>\n</li>\n<li>2. Document processing and extraction<ul></ul>\n</li>\n<li>3. Natural language processing use cases<ul></ul>\n</li>\n<li>4. Conversational AI and chatbots<ul></ul>\n</li>\n</ul>- Responsible AI principles <ul>\n<li>1. Inclusiveness<ul></ul>\n</li>\n<li>2. Privacy and security<ul></ul>\n</li>\n<li>3. Fairness<ul></ul>\n</li>\n<li>4. Transparency and accountability<ul></ul>\n</li>\n<li>5. Reliability and safety<ul></ul>\n</li>\n</ul>\n</td>\n</tr>\n<tr>\n<td>Topic 2: Describe features of computer vision workloads on Azure</td>\n<td>15-20%</td>\n<td>- Image analysis <ul>\n<li>1. Image classification<ul></ul>\n</li>\n<li>2. Optical character recognition (OCR)<ul></ul>\n</li>\n<li>3. Object detection<ul></ul>\n</li>\n</ul>- Azure AI Vision services <ul>\n<li>1. Azure AI Vision<ul></ul>\n</li>\n<li>2. Face detection and analysis (limited use cases)<ul></ul>\n</li>\n</ul>\n</td>\n</tr>\n<tr>\n<td>Topic 3: Describe features of natural language processing (NLP) workloads on Azure</td>\n<td>15-20%</td>\n<td>- Azure NLP services <ul>\n<li>1. Azure AI Language<ul></ul>\n</li>\n<li>2. Speech services (speech-to-text, text-to-speech)<ul></ul>\n</li>\n</ul>- Text analysis <ul>\n<li>1. Sentiment analysis<ul></ul>\n</li>\n<li>2. Key phrase extraction<ul></ul>\n</li>\n<li>3. Language detection<ul></ul>\n</li>\n</ul>\n</td>\n</tr>\n<tr>\n<td>Topic 4: Describe features of generative AI workloads on Azure</td>\n<td>10-15%</td>\n<td>- Generative AI concepts <ul>\n<li>1. Prompt engineering basics<ul></ul>\n</li>\n<li>2. Responsible use of generative AI<ul></ul>\n</li>\n<li>3. Large language models (LLMs)<ul></ul>\n</li>\n</ul>- Azure OpenAI and generative services <ul>\n<li>1. Azure OpenAI Service capabilities<ul></ul>\n</li>\n<li>2. Use cases: chatbots, content generation, summarization<ul></ul>\n</li>\n</ul>\n</td>\n</tr>\n<tr>\n<td>Topic 5: Describe fundamental principles of machine learning on Azure</td>\n<td>25-30%</td>\n<td>- Azure Machine Learning basics <ul>\n<li>1. AutoML concepts<ul></ul>\n</li>\n<li>2. Azure ML workspace components<ul></ul>\n</li>\n</ul>- Machine learning concepts <ul>\n<li>1. Training and evaluation concepts<ul></ul>\n</li>\n<li>2. Supervised vs unsupervised learning<ul></ul>\n</li>\n<li>3. Regression and classification<ul></ul>\n</li>\n</ul>\n</td>\n</tr>\n</tbody></table><a href=\"https://www.testpdf.net/AI-901.html\" style=\"background-color: #d2322d; color: #FFFFFF; text-decoration: none; padding: 10px; font-weight: bold;\" target=\"_blank\">&gt;&gt; 新版AI-901題庫上線 &lt;&lt;</a><h2>最新上傳的新版AI-901題庫上線 &amp;AI-901：Microsoft Azure AI Fundamentals</h2>我們Testpdf配置提供給你最優質的Microsoft的AI-901考試考古題及答案，將你一步一步帶向成功，我們Testpdf Microsoft的AI-901考試認證資料絕對提供給你一個真實的考前準備，我們針對性很強，就如同為你量身定做一般，你一定會成為一個有實力的IT專家，我們Testpdf Microsoft的<a href=\"https://www.pdfexamdumps.com/AI-901_valid-braindumps.html\">AI-901考試</a>認證資料將是最適合你也是你最需要的培訓資料，趕緊註冊我們Testpdf網站，相信你會有意外的收穫。<h2>最新的 Microsoft Certified: Azure AI Fundamentals AI-901 免費考試真題 (Q33-Q38):</h2>問題 #33 You are developing an application that processes voicemail recordings by using Azure Content Understanding in Foundry Tools. Which feature does Azure Content Understanding use to convert audio to text?<ul>\n<li>A. key phrase extraction</li>\n<li>B. transcription</li>\n<li>C. optical character recognition (OCR)</li>\n<li>D. Voice Live</li>\n</ul>答案：B解題說明： Azure Content Understanding uses transcription to convert audio content, such as voicemail recordings, into text. Microsoft's Azure Content Understanding audio documentation states that transcription converts conversational audio into searchable and analyzable text-based transcripts. 問題 #34 Your company has thousands of recorded customer support calls in multiple languages stored as audio files in Azure Storage. You need to generate text transcripts of all the recordings. Which Azure Speech in Foundry Tools capability should you use?<ul>\n<li>A. speech to text batch transcription</li>\n<li>B. text to speech</li>\n<li>C. speech to text real-time transcription</li>\n<li>D. speech translation</li>\n</ul>答案：A解題說明： For thousands of recorded support calls stored as audio files in Azure Storage, the correct capability is speech to text batch transcription. Microsoft states that batch transcription is designed to transcribe a large amount of audio data in storage, including audio files in Azure Blob Storage, and that files can be processed concurrently to reduce turnaround time. Real-time transcription is for live audio, not large stored batches. Text to speech converts text into audio. Speech translation translates speech between languages, but the requirement is to generate transcripts. 問題 #35 Your company processes customer support emails. You need to implement an AI solution that automatically identifies mentions of people, organizations, and locations in the emails. Which text analysis technique should you use?<ul>\n<li>A. key phrase extraction</li>\n<li>B. summarization</li>\n<li>C. sentiment analysis</li>\n<li>D. Named Entity Recognition (NER)</li>\n</ul>答案：D解題說明： The correct text analysis technique is Named Entity Recognition (NER). Microsoft defines NER as a feature that identifies and categorizes entities in unstructured text, including people, places, and organizations. Sentiment analysis detects positive, negative, or neutral opinion. Summarization creates shorter versions of text. Key phrase extraction identifies important phrases, but it does not specifically classify mentions as people, organizations, or locations. 問題 #36 You are using the Azure Speech SDK to develop a Python application that supports real-time spoken conversations. Which Azure speech class should you use to configure the connection to the Azure Speech service?<ul>\n<li>A. AuditOutputConfig</li>\n<li>B. SpeechSynthesizer</li>\n<li>C. AudioConfig</li>\n</ul>答案：A 問題 #37 You plan to develop an AI application that will read the license plates of motor vehicles by using Azure AI Foundry. What should you use to develop the application?<ul>\n<li>A. Azure AI Studio</li>\n<li>B. Copilot for Microsoft 365</li>\n<li>C. GitHub Actions</li>\n<li>D. Microsoft Visual Studio Code</li>\n</ul>答案：A解題說明： Azure AI Studio (now Azure AI Foundry) is used to develop an AI application for reading license plates using its tools and models. The platform allows developers to build, customize, and deploy AI agents and applications, including those that process images to extract information like license plate numbers. Key components of the process Platform: Azure AI Foundry (formerly Azure AI Studio) is the central platform for building and managing AI applications. Tools: You can use its integrated development environment (IDE), SDKs, and APIs to develop and customize models. Models: The platform provides access to a wide range of AI models, including computer vision models capable of optical character recognition (OCR), which can be used to read text from images. Workflow: Create an Azure AI Foundry project in Azure. Use the model catalog to find and deploy a suitable computer vision or OCR model. Integrate the model into your application using the SDK or API. For a license plate application, you would feed images to the model, and the model would output the recognized text from the license plate. Reference: https://azure.microsoft.com/en-us/products/ai-foundry 問題 #38 ......除了確保為考生提供最新和最好的Microsoft AI-901題庫資料之外，我們更希望為您提供優質的服務，我們提供所有的考古題都是最新版的題庫資料。我們還使用國際最大最值得信賴的Paypal付款，安全支付有保障，考生可以放心購買最新的AI-901考古題。在現在競爭激烈的IT行業，擁有Microsoft <a href=\"https://www.newdumpspdf.com/AI-901-practice-test.html\">AI-901認證</a>是證明自己能力的標志。而Testpdf網站的最新版的考古題就確保您通過此認證，AI-901題庫是由多位專業的資深講師研究而來，成就您的夢想！AI-901認證題庫: <a href=\"https://www.testpdf.net/AI-901.html\" target=\"_blank\" title=\"AI-901認證題庫\">https://www.testpdf.net/AI-901.html</a><ul>\n<li><a href=\"https://www.kaoguti.com/AI-901_exam-pdf.html\">Microsoft 新版AI-901題庫上線是行業領先材料＆AI-901認證題庫 \u{1F7E8} “ www.kaoguti.com ”上的免費下載✔ AI-901 ️✔️頁面立即打開AI-901最新考古題</a></li>\n<li><a href=\"https://www.pdc.edu/?URL=https%3a%2f%2fwww.testpdf.net%2fAI-901.html\">Microsoft 新版AI-901題庫上線是行業領先材料＆AI-901認證題庫 🎐 透過「 www.newdumpspdf.com 」輕鬆獲取☀ AI-901 ️☀️免費下載AI-901資訊</a></li>\n<li><a href=\"https://www.vcesoft.com/AI-901-exam-questions.html\">最新的新版AI-901題庫上線 |高通過率的考試材料|完美的AI-901認證題庫 😵 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