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Introducing Updated Microsoft Certified: Azure AI Fundamentals Designation

This certificate is an opportunity for candidates to showcase their mastery of the Machine Learning (ML) and Artificial Intelligence (AI) workloads and their implementation of Azure services. For that reason, AI-900 exam can be taken by all candidates from technical and non-technical fields. While software engineering and data science skills may not be required for such an evaluation, it is important to have general programming knowledge to stand a chance of cracking this test right away. By and large, the updated Microsoft Certified: Azure AI Fundamentals designation can help you advance your career growth by preparing you for advanced Azure role-based certifications including the Microsoft Certified: Azure AI Engineer Associate and the Microsoft Certified: Azure Data Scientist Associate certificates.

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Microsoft Azure AI Fundamentals Sample Questions (Q116-Q121):

NEW QUESTION # 116
Match the machine learning tasks to the appropriate scenarios.
To answer, drag the appropriate task from the column on the left to its scenario on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer: ** Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml
NEW QUESTION # 117**
Match the types of machine learning to the appropriate scenarios.
To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right.
Each machine learning type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer: ** Explanation:

Explanation
1- Regression
2- Clustering
3- Classification
NEW QUESTION # 118**
You need to build an app that will read recipe instructions aloud to support users who have reduced vision.
Which version service should you use?

• A. Speech
• B. Language Understanding (LUIS)
• C. Text Analytics
• D. Translator Text

Answer: A Explanation:
Section: Describe features of Natural Language Processing (NLP) workloads on Azure Explanation/Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/text-to-speech/#features
NEW QUESTION # 119
You build a machine learning model by using the automated machine learning user interface (UI).
You need to ensure that the model meets the Microsoft transparency principle for responsible AI.
What should you do?

• A. Enable Explain best model.
• B. Set Primary metric to accuracy.
• C. Set Validation type to Auto.
• D. Set Max concurrent iterations to 0.

Answer: A Explanation:
Section: Describe Artificial Intelligence workloads and considerations
Explanation:
Model Explain Ability.
Most businesses run on trust and being able to open the ML "black box" helps build transparency and trust. In heavily regulated industries like healthcare and banking, it is critical to comply with regulations and best practices. One key aspect of this is understanding the relationship between input variables (features) and model output. Knowing both the magnitude and direction of the impact each feature (feature importance) has on the predicted value helps better understand and explain the model. With model explain ability, we enable you to understand feature importance as part of automated ML runs.
Reference:
https://azure.microsoft.com/en-us/blog/new-automated-machine-learning-capabilities-in-azure-machine- learning-service/
NEW QUESTION # 120
Match the types of machine learning to the appropriate scenarios.
To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right. Each machine learning type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer: ** Explanation:

NEW QUESTION # 121
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