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The Microsoft AI-900 exam is suitable for individuals who want to start a career in AI or individuals who want to expand their knowledge on AI and its implementation on Azure. AI-900 exam is also suitable for IT professionals who want to gain an understanding of AI and its potential applications in their organization. AI-900 exam is an excellent opportunity for those who want to showcase their skills and expertise in AI and Azure.
The interested candidate for the Microsoft AI-900 test, which also goes under the name the Azure test for AI Fundamentals, should have at least some foundational understanding of the concept of AI features alongside ML ones. This exam will test the entrant's knowledge of different AI common workloads, principles of AI and ML, NLP workloads, and other related concepts. When it comes to the details for this exam, the Microsoft AI-900 is available in several languages, among which you'll find Spanish, English, Korean, German, Chinese (Simplified), and French. Such an exam comes with a registration fee of $99 and should be scheduled through Pearson VUE. Also, in the main exam, candidates will be exposed to around 40-60 tasks with 1 hour given to solve them.
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Microsoft AI-900, also known as Microsoft Azure AI Fundamentals, is a certification exam that tests the foundational knowledge of candidates in the field of artificial intelligence (AI) and machine learning (ML). Microsoft Azure AI Fundamentals certification exam is designed for individuals who are interested in learning about AI and ML concepts and how they can be implemented in Microsoft Azure. AI-900 Exam covers a wide range of topics related to AI, including cognitive services, natural language processing (NLP), computer vision, and conversational AI.
NEW QUESTION # 148
Which OpenAI model does GitHub Copilot use to make suggestions for client-side JavaScript?
Answer: C
NEW QUESTION # 149
Select the .
Answer:
Explanation:
NEW QUESTION # 150
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
NEW QUESTION # 151
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation:
The correct answer is object detection. According to the Microsoft Azure AI Fundamentals (AI-900) official study materials and Microsoft Learn module "Explore computer vision", object detection is the process of identifying and locating objects within an image or video. The primary characteristic of object detection, as emphasized in the study guide, is its ability to return a bounding box around each detected object along with a corresponding label or class.
In this question, the task involves returning a bounding box that indicates the location of a vehicle in an image. This is the exact definition of object detection - identifying that the object exists (a vehicle) and determining its position within the frame. Microsoft Learn clearly differentiates this from other computer vision tasks. Image classification, for example, only determines what an image contains as a whole (for instance, "this image contains a vehicle"), but it does not indicate where in the image the object is located.
Optical character recognition (OCR) is specifically used for extracting printed or handwritten text from images, and semantic segmentation involves classifying every pixel in an image to understand boundaries in greater detail, often used in autonomous driving or medical imaging.
The official AI-900 guide highlights object detection as one of the key computer vision workloads supported by Azure Computer Vision, Custom Vision, and Azure Cognitive Services. These services are designed to detect multiple instances of various object types in a single image, outputting bounding boxes and confidence scores for each.
Therefore, based on the AI-900 official curriculum and Microsoft Learn concepts, returning a bounding box that shows the location of a vehicle is a textbook example of object detection, as it involves both recognition and localization of the object within the image frame.
NEW QUESTION # 152
Which two resources can you use to analyze code and generate explanations of code function and code comments? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.
Answer: A,D
Explanation:
The correct answers are C. the Azure OpenAI GPT-4 model and D. the GitHub Copilot service.
According to the Microsoft Azure AI Fundamentals (AI-900) curriculum and Microsoft Learn documentation on Azure OpenAI and GitHub Copilot, both GPT-4 and GitHub Copilot can be used to analyze and generate explanations for code functionality, as well as produce or refine code comments.
* Azure OpenAI GPT-4 model (C):The GPT-4 model is a large language model (LLM) developed by OpenAI and available through the Azure OpenAI Service. It is trained on vast amounts of text, including programming languages, documentation, and natural language instructions. This enables it to interpret source code, explain what it does, suggest optimizations, and automatically generate detailed code comments. When prompted with code snippets, GPT-4 can provide structured natural language explanations describing the logic and intent of the code. In enterprise scenarios, developers use Azure OpenAI GPT models for code understanding, review automation, and documentation generation.
* GitHub Copilot service (D):GitHub Copilot, powered by OpenAI Codex, is an AI coding assistant integrated into IDEs such as Visual Studio Code. It can analyze code context and generate inline comments and explanations in real time. GitHub Copilot understands the syntax and intent of numerous programming languages and provides intelligent suggestions or explanations directly in the developer's environment.
The other options are not suitable:
* A. DALL-E is a generative image model for creating visual content, not text or code analysis.
* B. Whisper is an automatic speech recognition (ASR) model used for converting speech to text, unrelated to code interpretation.
Therefore, based on the official Azure AI and GitHub documentation, the correct and verified answers are C.
Azure OpenAI GPT-4 model and D. GitHub Copilot service.
NEW QUESTION # 153
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