Microsoft Azure AI Fundamentals (AI-901) Practice Test
Microsoft Azure AI Fundamentals (AI-901) के लिए अपना आत्मविश्वास बढ़ाएँ। अवधारणाओं का अभ्यास करें, उत्तरों को समझें और हर सवाल के साथ अपना ज्ञान मज़बूत करें।
एक नमूना सवाल आज़माएँपरीक्षा का परिचय और विवरण
Through this practice test, you can build a working understanding of core AI concepts and how Microsoft Foundry supports AI solution implementation. You will connect ideas like identifying AI capabilities and using Microsoft Foundry to practical tasks, such as recognizing when to apply AI and how to begin building solutions. When you are ready, take one focused practice set and review each explanation as a small, manageable next step.
ब्लूप्रिंट 1.0
नमूना प्रश्न
अभ्यास कैसे काम करता है, यह जानने के लिए एक उत्तर चुनें और व्याख्या देखें।
242 में से 234 उत्तरों में जाँचने योग्य संदर्भ है।
You are configuring network access for a Foundry Tools resource. You need to grant access to a virtual network that is in a different Microsoft Entra tenant. What must be true?
A company deploys the gpt-6-astra model in Microsoft Foundry. During inference, the safety systems detect elevated risk. Which action may the model take as part of enhanced safety controls?
A company uses a provisioned deployment of a language model that is scheduled for retirement. What should the company do?
सही उत्तर B है। प्रावधानित डिप्लॉयमेंट्स स्वचालित रूप से अपग्रेड नहीं होते, इसलिए ग्राहकों को मैन्युअल रूप से माइग्रेट करना पड़ता है। मार्गदर्शन यह है कि Microsoft द्वारा आधिकारिक प्रतिस्थापन का नाम घोषित होने का इंतजार न करें; इसके बजाय, जैसे ही नए मॉडल उपलब्ध हों, उनका मूल्यांकन शुरू करें।
A Microsoft certification exam is offered in English and several localized languages. When the exam content is updated, which version is updated first?
A candidate is reviewing the skills measured for the AI-901 exam. They notice that each skill is followed by a list of bullets. What is the purpose of these bullets?
इस परीक्षा में क्या शामिल है
पढ़ाई की योजना बनाने के लिए प्रकाशित डोमेन भार का उपयोग करें। अभ्यास के परिणाम आपके सर्टिफिकेशन परीक्षा के स्कोर का अनुमान नहीं हैं।
01Implement AI solutions by using Microsoft Foundry
विषय
- Create effective system and user prompts for generative AI models
- Deploy a model and interact with it in the Foundry portal
- Create a lightweight chat client application by using the Foundry SDK
- Create and test a single-agent solution in the Foundry portal
- Create a lightweight client application for an agent
- Build a lightweight application that includes text analysis
- Respond to spoken prompts by using a deployed multimodal model
- Build a lightweight application by using Azure Speech in Foundry Tools
- Interpret visual input in prompts by using a deployed multimodal model
- Create new visual outputs by using generative models
- Build a lightweight application that includes vision capabilities
- Extract information from documents and forms by using Azure Content Understanding in Foundry Tools
- Extract information from images by using Content Understanding
- Extract information from audio and video by using Content Understanding
- Build a lightweight application with information extraction capabilities by using Content Understanding
- Last updated on 07/13/2026
- Purpose of this document
- Updates to the exam
- Skills measured as of April 15, 2026
- Study resources
- High contrast
- AI Disclaimer
- Previous Versions
- Contribute
- Privacy
- Consumer Health Privacy
- Terms of Use
- Trademarks
- © Microsoft 2026
सीखने के उद्देश्य
- Create effective system and user prompts for generative AI models
- Deploy a model and interact with it in the Foundry portal
- Create a lightweight chat client application by using the Foundry SDK
- Create and test a single-agent solution in the Foundry portal
- Create a lightweight client application for an agent
- Build a lightweight application that includes text analysis
- Respond to spoken prompts by using a deployed multimodal model
- Build a lightweight application by using Azure Speech in Foundry Tools
- Interpret visual input in prompts by using a deployed multimodal model
- Create new visual outputs by using generative models
- Build a lightweight application that includes vision capabilities
- Extract information from documents and forms by using Azure Content Understanding in Foundry Tools
- Extract information from images by using Content Understanding
- Extract information from audio and video by using Content Understanding
- Build a lightweight application with information extraction capabilities by using Content Understanding
- Last updated on 07/13/2026
- Purpose of this document
- Updates to the exam
- Skills measured as of April 15, 2026
- Study resources
- High contrast
- AI Disclaimer
- Previous Versions
- Contribute
- Privacy
- Consumer Health Privacy
- Terms of Use
- Trademarks
- © Microsoft 2026
02Identify AI concepts and capabilities
विषय
- Describe considerations for fairness in an AI solution
- Describe considerations for reliability and safety in an AI solution
- Describe considerations for privacy and security in an AI solution
- Describe considerations for inclusiveness in an AI solution
- Describe considerations for transparency in an AI solution
- Describe considerations for accountability in an AI solution
- Describe how generative AI models work
- Identify an appropriate AI model, based on capabilities
- Identify appropriate model deployment options and configuration parameters
- Identify scenarios for common AI workloads, including generative and agentic AI, text analysis, speech, computer vision, and information extraction
- Describe common text analysis techniques, including keyword extraction, entity detection, sentiment analysis, and summarization
- Identify features and capabilities of speech recognition and speech synthesis
- Identify features and capabilities of computer vision and image-generation models
- Identify techniques to extract information from text, images, audio, and videos
सीखने के उद्देश्य
- Describe considerations for fairness in an AI solution
- Describe considerations for reliability and safety in an AI solution
- Describe considerations for privacy and security in an AI solution
- Describe considerations for inclusiveness in an AI solution
- Describe considerations for transparency in an AI solution
- Describe considerations for accountability in an AI solution
- Describe how generative AI models work
- Identify an appropriate AI model, based on capabilities
- Identify appropriate model deployment options and configuration parameters
- Identify scenarios for common AI workloads, including generative and agentic AI, text analysis, speech, computer vision, and information extraction
- Describe common text analysis techniques, including keyword extraction, entity detection, sentiment analysis, and summarization
- Identify features and capabilities of speech recognition and speech synthesis
- Identify features and capabilities of computer vision and image-generation models
- Identify techniques to extract information from text, images, audio, and videos