Microsoft - AI-102 Updated Exam Answers

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To prepare for the Microsoft AI-102 exam, candidates should have a strong understanding of Azure services and AI concepts. They should also have experience in designing and implementing AI solutions, as well as knowledge of programming languages such as Python and C#. In addition, candidates should be familiar with machine learning concepts such as supervised and unsupervised learning, deep learning, and reinforcement learning. With the Microsoft AI-102 certification, professionals can demonstrate their expertise in AI solution development and implementation on the Azure platform, opening up opportunities for career advancement and higher salaries.

Microsoft AI-102 Exam is designed for individuals who have a strong understanding of artificial intelligence (AI) and how it can be implemented in Microsoft Azure. AI-102 exam focuses on the design and implementation of AI solutions that can help businesses improve their operations, increase efficiency, and generate insights from data.

Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q201-Q206):

NEW QUESTION # 201
You are developing the shopping on-the-go project.
You need to build the Adaptive Card for the chatbot.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 202
You build a QnA Maker resource to meet the chatbot requirements.
Which RBAC role should you assign to each group? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/role-based-access-control


NEW QUESTION # 203
You are developing an application that includes language translation.
The application will translate text retrieved by using a function named get_text_to_be_translated. The text can be in one of many languages. The content of the text must remain within the Americas Azure geography.
You need to develop code to translate the text to a single language.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 204
You are developing an application that will recognize faults in components produced on a factory production line. The components are specific to your business.
You need to use the Custom Vision API to help detect common faults.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation:

Comprehensive Detailed Explanation You are tasked with building a solution using Custom Vision to detect faults in factory components. Custom Vision follows a defined workflow:
* Create a project
* Before anything else, you must create a Custom Vision project in the Azure AI portal.
* This project specifies the type of model you are building: classification (classifying entire images) or object detection (locating items within images).
* Since the question is about detecting faults in specific components (a business-specific scenario), it aligns with classification unless explicitly stated otherwise.
* Upload and tag images
* You must provide training data.
* Upload a set of images showing both faulty and non-faulty components.
* Tag each image correctly so that the model can learn from labeled examples.
* Train the classifier model
* Once images are tagged, you run training on the dataset to generate the classifier model.
* The model can then be published and used for inference via API calls.
* Initialize the training dataset: This is not a direct step in Custom Vision; instead, uploading and tagging images inherently prepares the training dataset.
* Train the object detection model: Object detection is used if you need bounding boxes around items within an image. Since the question is about recognizing faults in a component (faulty vs non-faulty), a classifier model is appropriate.
Why not the other options?
Correct Sequence:
* Create a project
* Upload and tag images
* Train the classifier model
* Quickstart: Build an image classification project with the Custom Vision portal
* Custom Vision overview
* Train and test a Custom Vision model
Microsoft References


NEW QUESTION # 205
You are building a multilingual chatbot.
You need to send a different answer for positive and negative messages.
Which two Text Analytics APIs should you use? Each correct answer presents part of the solution. (Choose two.) NOTE: Each correct selection is worth one point.

Answer: D,E

Explanation:
B: The Text Analytics API's Sentiment Analysis feature provides two ways for detecting positive and negative sentiment. If you send a Sentiment Analysis request, the API will return sentiment labels (such as "negative", "neutral" and "positive") and confidence scores at the sentence and document-level.
D: The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
This capability is useful for content stores that collect arbitrary text, where language is unknown. Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to- sentiment-analysis?tabs=version-3-1
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to- language-detection


NEW QUESTION # 206
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