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The Microsoft AI-900 Exam consists of 40-60 multiple-choice questions and has a time limit of 60 minutes. The passing score for the exam is 700 out of 1000. To prepare for the exam, Microsoft offers a variety of resources, including online training courses, practice exams, and study guides.
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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 # 145
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://azure.microsoft.com/en-in/blog/microsoft-conversational-ai-tools-enable-developers-to-build-connect-and-manage-intelligent-bots
NEW QUESTION # 146
Match the Azure Cognitive Services service to the appropriate actions.
To answer, drag the appropriate service from the column on the left to its action on the right. Each service may he used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 147
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 148
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier
NEW QUESTION # 149
Match the Microsoft guiding principles for responsible AI to the appropriate descriptions.
To answer, drag the appropriate principle from the column on the left to its description on the right. Each principle may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Reliability and safety
To build trust, it's critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions. These systems should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation.
Box 2: Fairness
Fairness: AI systems should treat everyone fairly and avoid affecting similarly situated groups of people in different ways. For example, when AI systems provide guidance on medical treatment, loan applications, or employment, they should make the same recommendations to everyone with similar symptoms, financial circumstances, or professional qualifications.
We believe that mitigating bias starts with people understanding the implications and limitations of AI predictions and recommendations. Ultimately, people should supplement AI decisions with sound human judgment and be held accountable for consequential decisions that affect others.
Box 3: Privacy and security
As AI becomes more prevalent, protecting privacy and securing important personal and business information is becoming more critical and complex. With AI, privacy and data security issues require especially close attention because access to data is essential for AI systems to make accurate and informed predictions and decisions about people. AI systems must comply with privacy laws that require transparency about the collection, use, and storage of data and mandate that consumers have appropriate controls to choose how their data is used Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles
NEW QUESTION # 150
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