AI-102 Dumps [Genuine] To Build Distinctively Microsoft AI-102 Exam Prep

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AI-102: What Do I Need To Pay Extra Attention To In Designing And Implementing A Microsoft Azure AI Solution (beta)?

Artificial intelligence (AI) has played an important role in transforming the way businesses operate. It is also becoming more and more popular with the public. The AI-102 exam really falls into this category.

If you are preparing for the Microsoft AI-102 exam, you need to pay extra attention to what is mentioned below.

Full name of the exam: Designing and Implementing a Microsoft Azure AI Solution (beta)
Abbreviation: AI-102
Passing Score: 700
Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian, Indonesian (Indonesia)

  • Plan and manage an Azure Cognitive Services solution
  • Implement Computer Vision solutions
  • Implement natural language processing solutions
  • Implement knowledge mining solutions
  • Implement conversational AI solutions

Official Learning Resources:

  • Prepare for AI engineering
  • Provision and manage Azure Cognitive Services
  • Process and translate the text with Azure Cognitive Services
  • Process and Translate Speech with Azure Cognitive Speech Services
  • Create a Language Understanding solution
  • Build a question-answering solution
  • Create conversational AI solutions
  • Create computer vision solutions with Azure Cognitive Services
  • Extract text from images and documents
  • Implement knowledge mining with Azure Cognitive Search

Genuine Preparation Resource: Pass4itSure AI-102 Dumps
Successful certification can be obtained: Microsoft Certified: Azure AI Engineer Associate

Notice! The exam will be updated on August 2, 2022, which is tomorrow. You need to keep an eye on the exam policy at all times!

How Do I Prepare For The AI-102 Exam?

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AI-102 Free Dumps Questions And Answers To Prepare You For The Exam:

AI-102 exam dumps questions are available online and are valuable for your exam study.

Q- 1

DRAG DROP You are building a retail chatbot that will use a QnA Maker service. You upload an internal support document to train the model. The document contains the following question: “What is your warranty period?”

Users report that the chatbot returns the default QnA Maker answer when they ask the following question: “How long is the warranty coverage?” The chatbot returns the correct answer when the users ask the following question: \\’What is your warranty period?” Both questions should return the same answer.

You need to increase the accuracy of the chatbot responses. 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. (Choose three.)

Select and Place:

Correct Answer:

Step 1: Add alternative phrasing to the question and answer (QnA) pair.
Add alternate questions to an existing QnA pair to improve the likelihood of a match to a user query.
Step 2: Retrain the model.
Periodically select Save and train after making edits to avoid losing changes.
Step 3: Republish the model

Note: A knowledge base consists of question and answer (QnA) pairs. Each pair has one answer and a pair contains all the information associated with that answer.


Q- 2

You are developing a photo application that will find photos of a person based on a sample image by using the Face API. You need to create a POST request to find the photos.

How should you complete the request? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.
Select and Place:

Box 1: detect
Face – Detect With Url: Detect human faces in an image, return face rectangles, and optionally with faceIds, landmarks, and attributes. POST {Endpoint}/face/v1.0/detect

Box 2: matchPerson
Find similar has two working modes, “matchPerson” and “matchFace”. “matchPerson” is the default mode that it tries to find faces of the same person as possible by using internal same-person thresholds. It is useful to find a known person\\’s other photos. Note that an empty list will be returned if no faces pass the internal thresholds. “matchFace” mode ignores same-person thresholds and returns ranked similar faces anyway, even the similarity is low. It can be used in the cases like searching celebrity-looking faces.


Q- 3

You have the following C# method for creating Azure Cognitive Services resources programmatically.

You need to call the method to create a free Azure resource in the West US Azure region. The resource will be used to generate captions of images automatically. Which code should you use?

A. create_resource(client, “res1”, “ComputerVision”, “F0”, “westus”)
B. create_resource(client, “res1”, “CustomVision.Prediction”, “F0”, “westus”)
C. create_resource(client, “res1”, “ComputerVision”, “S0”, “westus”)
D. create_resource(client, “res1”, “CustomVision.Prediction”, “S0”, “westus”)

Correct Answer: B

Many of the Cognitive Services have a free tier you can use to try the service. To use the free tier, use F0 as the SKU for your resource. There are two tiers of keys for the Custom Vision service. You can sign up for a F0 (free) or S0 (standard) subscription through the Azure portal.

Incorrect Answers:
A: There is no free tier (F0) for ComputerVision.


Q- 4

You need to create a new resource that will be used to perform sentiment analysis and optical character recognition (OCR). The solution must meet the following requirements:

Use a single key and endpoint to access multiple services. Consolidate billing for future services that you might use. Support the use of Computer Vision in the future. How should you complete the HTTP request to create the new resource? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.
Hot Area:

Correct Answer:

Box 1: PUT
Sample Request: PUT

Incorrect Answers:
PATCH is for updates.

Box 2: CognitiveServices
Microsoft Azure Cognitive Services provide us to use its pre-trained models for various Business Problems related to Machine Learning.

List of Different Services are:
Language (includes sentiment analysis)
Vision (includes OCR)
Web Search


Q- 5

You are planning the product creation project. You need to build the REST endpoint to create the multilingual product descriptions. How should you complete the URI? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.
Hot Area:

Box 1: Translator 3.0: Translate. Send a POST request to:
Box 2: /translate Reference:

Q- 6

You are building a chatbot by using the Microsoft Bot Framework Composer.

You have the dialog design shown in the following exhibit.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

Hot Area:

Box 1: No
User. name is a property.
Box 2: Yes Box 3: Yes The coalesce() function evaluates a list of expressions and returns the first non-null (or nonempty for string) expression.


Q- 7

You develop a test method to verify the results retrieved from a call to the Computer Vision API. The call is used to analyze the existence of company logos in images. The call returns a collection of brands named brands. You have the following code segment.

Box 1: Yes
Box 2: Yes
If several logs are detected, or the logo image and the stylized brand name are detected as two separate logos, it starts numbering them from the bottom-left corner.
Box 3: No


Q- 8

You are creating an enrichment pipeline that will use Azure Cognitive Search. The knowledge store contains unstructured JSON data and scanned PDF documents that contain text. Which projection type should you use for each data type? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Hot Area:

Correct Answer:

Box 1: Object projection
Object projections are JSON representations of the enrichment tree that can be sourced from any node.
Box 2: File projection
File projections are similar to object projections and only act on the normalized_images collection.


Q- 9

You develop an application to identify species of flowers by training a Custom Vision model. You receive images of new flower species. You need to add the new images to the classifier. Solution: You add the new images and labels to the existing model. You retrain the model and then publish the model. Does this meet the goal?

A. Yes
B. No

Correct Answer: A

The model needs to be extended and retrained.

Q- 10

You develop an application to identify species of flowers by training a Custom Vision model. You receive images of new flower species. You need to add the new images to the classifier. Solution: You create a new model, and then upload the new images and labels. Does this meet the goal?

A. Yes
B. No

Correct Answer: B

The model needs to be extended and retrained.

Q- 11

You build a language model by using a Language Understanding service. The language model is used to search for information on a contact list by using an intent named FindContact.

A conversational expert provides you with the following list of phrases to use for training.
Find contacts in London. Who do I know in Seattle? Search for contacts in Ukraine. You need to implement the phrase list in Language Understanding. Solution: You create a new pattern in the FindContact intent. Does this meet the goal?

A. Yes
B. No

Correct Answer: B

Instead, use a new intent for location.

Note: An intent represents a task or action the user wants to perform. It is a purpose or goal expressed in a user\\’sutterance. Define a set of intents that corresponds to actions users want to take in your application.


Q- 12

You need to build a chatbot that meets the following requirements:
Supports chit-chat, knowledge base, and multilingual models Perform sentiment analysis on user messages Selects the best language model automatically

What should you integrate into the chatbot?

A. QnA Maker, Language Understanding, and Dispatch
B. Translator, Speech, and Dispatch
C. Language Understanding, Text Analytics, and QnA Maker
D. Text Analytics, Translator, and Dispatch

Correct Answer: C

Language Understanding: An AI service that allows users to interact with your applications, bots, and IoT devices by using natural language.

QnA Maker is a cloud-based Natural Language Processing (NLP) service that allows you to create a natural conversational layer over your data. It is used to find the most appropriate answer for any input from your custom knowledge base (KB) of information.

Text Analytics: my insights in unstructured text using natural language processing (NLP)–no machine learning expertise required. Gain a deeper understanding of customer opinions with sentiment analysis. The Language Detection feature of the Azure Text Analytics, REST API evaluates text input

Incorrect Answers:
A, B, D: Dispatch uses sample utterances for each of your bot\\’s different tasks (LUIS, QnA Maker, or custom), and builds a model that can be used to properly route your user\\’s request to the right task, even across multiple bots.


Q- 13

You use the Custom Vision service to build a classifier. After training is complete, you need to evaluate the classifier. Which two metrics are available for review? Each correct answer presents a complete solution. (Choose two.)

NOTE: Each correct selection is worth one point.

A. recall
B. F-score
C. weighted accuracy
D. precision
E. area under the curve (AUC)

Correct Answer: AD

Custom Vision provides three metrics regarding the performance of your model: precision, recall, and AP.

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