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The Microsoft sector is an ever-evolving and rapidly growing industry that is crucial in shaping our lives today. With the growing demand for skilled Microsoft professionals, obtaining Microsoft Azure AI Fundamentals (AI-900) certification exam has become increasingly important for those who are looking to advance their careers and stay competitive in the job market.

The AI-900 exam covers a range of topics, including AI workloads and considerations, fundamental principles of machine learning, and common machine learning scenarios and algorithms. AI-900 exam also covers Azure AI services and tools such as Azure Cognitive Services, Azure Machine Learning, and Azure Bot Service. Passing AI-900 exam demonstrates that an individual has a good understanding of AI and its applications in Azure and is capable of designing and implementing AI solutions using Azure services.

The Microsoft AI-900 Exam consists of 40-60 multiple-choice questions that need to be completed in 60 minutes. The questions are designed to test your knowledge and skills in the following areas: AI workloads and considerations, fundamental principles of machine learning, computer vision, natural language processing, and conversational AI. You will need to score at least 700 out of 1000 to pass the exam.

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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.

Microsoft Azure AI Fundamentals Sample Questions (Q232-Q237):

NEW QUESTION # 232
For each of the following statements, select Yes If the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation


NEW QUESTION # 233
You plan to use Azure Cognitive Services to develop a voice controlled personal assistant app.
Match the Azure Cognitive Services to the appropriate tasks.
To answer, drag the appropriate service from the column on the left to its description on the right Each service may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 234
You are evaluating whether to use a basic workspace or an enterprise workspace in Azure Machine Learning.
What are two tasks that require an enterprise workspace? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

Answer: A,C

Explanation:
Explanation
Note: Enterprise workspaces are no longer available as of September 2020. The basic workspace now has all the functionality of the enterprise workspace.
Reference:
https://www.azure.cn/en-us/pricing/details/machine-learning/
https://docs.microsoft.com/en-us/azure/machine-learning/concept-workspace


NEW QUESTION # 235
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation

Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing


NEW QUESTION # 236
You use Azure Machine Learning designer to build a model pipeline. What should you create before you can run the pipeline?

Answer: C

Explanation:
Before running a pipeline in Azure Machine Learning Designer, you must have an available compute resource (such as a compute instance or compute cluster). Compute provides the processing power required to train, evaluate, and execute the pipeline's modules.
Other options:
* A. Jupyter notebook - Used for code-first development, not required for Designer pipelines.
* B. Registered model - Created after running a pipeline, not before.


NEW QUESTION # 237
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