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Exam Details
The Microsoft AI-900 exam is the only qualifying test that leads to the Microsoft Certified: Azure AI Fundamentals certification. It measures one’s knowledge of AI considerations & workloads, features of NLP workloads on Azure, and basic principles of ML on Azure. The candidates can choose to take this exam in English, French, Simplified Chinese, Japanese, German, Spanish, or Korean. It contains 40-60 questions covering different types, including case studies, drag and drop, active screen, build list, and multiple choice. You can schedule your test with Certiport or Pearson VUE. However, it is required to pay the fee of $99 before scheduling it.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
The Importance of Microsoft AI-900 Exam
Microsoft AI-900 exam is an associate level certification which is a three to five-hour exam that covers the technologies necessary for building intelligent applications for cloud computing. Students should have a solid knowledge of Microsoft Azure IaaS, services, APIs, SQL Server 2017. Role of Azure Intelligent Solutions. Windows 2012, Windows 2016, and SQL Server 2017. .NET Framework 4.6.1 (or 4.7), or higher. Resident Deployment of the Solutions. Classify application workloads. Apply Azure monitoring and analytics, Operations Management Suite (OMS) logs, and Event Hubs. Manage the master database. Implement master database failover. Microsoft AI-900 exam dumps aligns with the objectives listed below. Classify application workloads. Deploy, configure, set up, activate, maintain, troubleshoot and support all necessary Azure services. Manage the master database.
Informationidentify the load of a given server. Forums and blogs about Azure and use of its products. Long term planning and development of future plans. Categoriesidentify the Azure deployment models. Forums and blogs about Azure and use of its products. Easy management of the Azure resources. Responsible for managing the database when the system doesn't work normally. Array of Solutionstests the knowledge of the candidate. Backgrounds of the candidate before they start their work. Push when you are in the process of testing.
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Microsoft AI-900 中文 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Features of generative AI workloads on Azure | 20–25% | - Describe use cases for generative AI - Describe responsible AI practices for generative AI - Describe capabilities of Azure OpenAI Service - Describe generative AI concepts |
| Topic 2: Artificial Intelligence workloads and considerations | 15–20% | - Describe responsible AI principles - Describe considerations for developing AI solutions - Identify types of AI workloads |
| Topic 3: Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Face - Describe capabilities of Azure Form Recognizer - Identify types of computer vision solutions |
| Topic 4: Fundamental principles of machine learning on Azure | 15–20% | - Describe automated machine learning - Describe core concepts of machine learning - Describe machine learning pipelines - Describe capabilities of Azure Machine Learning |
| Topic 5: Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Translator - Identify types of NLP solutions - Describe capabilities of Azure Speech - Describe capabilities of Azure Language |
Microsoft Azure AI Fundamentals (AI-900中文版) Sample Questions:
選擇 .
Correct Answer:
Explanation:
The correct completion of the sentence is:
"You can use the Custom Vision service to train an object detection model by using your own images." According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features of computer vision workloads," the Azure Custom Vision service is a specialized component of Azure Cognitive Services for Vision that enables developers to train custom image classification or object detection models using their own labeled image datasets.
The Custom Vision service differs from the Computer Vision service in that it allows full customization - meaning you can upload your own images, tag them manually, and train the model to recognize objects specific to your use case (for example, detecting your company's products, tools, or vehicles). Once trained, the model can identify and localize these objects in new images by returning bounding boxes and confidence scores, which is precisely what defines an object detection workload.
Microsoft's AI-900 materials describe object detection as the process of identifying objects in an image and determining their position, typically represented by bounding boxes. Custom Vision supports two main project types:
* Image Classification: Determines what is present in the image (e.g., "dog," "cat," "car").
* Object Detection: Identifies what is present and where it is located in the image.
In contrast:
* Computer Vision provides prebuilt models for general image analysis but doesn't allow custom model training.
* Form Recognizer is used for extracting text and data from structured or semi-structured documents.
* Azure Video Analyzer for Media focuses on video content analysis, not custom object detection.
Therefore, based on the official Microsoft AI-900 study guide and Microsoft Learn content, the verified and correct answer is Custom Vision, as it specifically allows training of a custom object detection model using your own images.
對於以下每個陳述，如果該陳述為真，請選擇「是」。否則，選擇“否”。 注意：每個正確的選擇都值得一分。
Correct Answer:
Explanation:
Box 1: Yes
Automated machine learning, also referred to as automated ML or AutoML, is the process of automating the time consuming, iterative tasks of machine learning model development. It allows data scientists, analysts, and developers to build ML models with high scale, efficiency, and productivity all while sustaining model quality.
Box 2: No
Box 3: Yes
During training, Azure Machine Learning creates a number of pipelines in parallel that try different algorithms and parameters for you. The service iterates through ML algorithms paired with feature selections, where each iteration produces a model with a training score. The higher the score, the better the model is considered to " fit " your data. It will stop once it hits the exit criteria defined in the experiment.
Box 4: No
Apply automated ML when you want Azure Machine Learning to train and tune a model for you using the target metric you specify.
The label is the column you want to predict.
Reference:
https://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features
要使使用 Azure OpenAI GPT-3.5 模型的聊天解決方案產生更詳細的回复，應該配置哪個參數？
- A. 溫度
- B. 最大回應B
- C. 停止序列
- D. 存在懲罰
Correct Answer: A 🗳️
Explanation: Only visible for Dumps4PDF members. You can sign-up / login (it's free).
將電腦視覺的類型與適當的場景相匹配。
若要回答，請將適當的工作負載類型從左側列拖曳到右側的場景。每種工作負載類型可以使用一次、多次或完全不使用。
注意：每個正確的選擇都值得一分。
Correct Answer:
Explanation:
The correct mappings are based on the Microsoft Azure AI Fundamentals (AI-900) curriculum topic:
"Describe features of computer vision workloads." Microsoft divides computer vision tasks into key workload types - image classification, object detection, facial recognition, and optical character recognition (OCR) - each designed for specific visual analysis objectives.
* Identify celebrities in images # Facial recognitionFacial recognition goes beyond simple face detection; it can identify or verify specific individuals by comparing facial features with known profiles.
According to Microsoft Learn, the Face service in Azure Cognitive Services can detect, recognize, and identify people in photos or videos. Recognizing celebrities or known individuals is a prime example of facial recognition.
* Extract movie title names from movie poster images # Optical Character Recognition (OCR)OCR is used to detect and extract text content from images, such as printed or handwritten words. Azure's Computer Vision API uses OCR technology to read text in various languages from photos, scanned documents, or posters. Therefore, extracting movie titles or actor names from a poster image is a perfect use case for OCR.
* Locate vehicles in images # Object detectionObject detection identifies and locates specific objects within an image, returning bounding boxes that indicate their positions. In Azure, the Custom Vision service or Computer Vision object detection models are used to detect multiple objects like vehicles, pedestrians, or animals in a single image.
Summary:
* Facial recognition # Identifies specific people (celebrities)
* OCR # Extracts text (movie titles)
* Object detection # Finds and locates physical items (vehicles)
Thus, the verified and official answer is:
您正在建立一個聊天機器人，它將使用自然語言處理 (NLP) 根據使用者的文字輸入執行以下操作：
* 接受客戶訂單。
* 檢索支援文件。
* 檢索訂單狀態更新。
您應該使用哪種類型的 NLP？
- A. 情緒分析
- B. 命名實體識別
- C. 翻譯
- D. 語言建模
Correct Answer: D 🗳️
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