HIGH QUALITY AI-102 TEST TORRENT TO GET DESIGNING AND IMPLEMENTING A MICROSOFT AZURE AI SOLUTION CERTIFICATION

High Quality AI-102 Test Torrent to Get Designing and Implementing a Microsoft Azure AI Solution Certification

High Quality AI-102 Test Torrent to Get Designing and Implementing a Microsoft Azure AI Solution Certification

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Tags: Well AI-102 Prep, AI-102 100% Correct Answers, New AI-102 Study Materials, Latest AI-102 Exam Dumps, AI-102 Valid Braindumps Questions

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The AI-102 Certification Exam covers a wide range of topics related to Azure AI, including designing AI solutions that use cognitive services, machine learning, and other AI technologies. AI-102 exam also covers topics such as data preparation, natural language processing, and computer vision. Designing and Implementing a Microsoft Azure AI Solution certification exam is intended for professionals who are looking to build their skills in AI and machine learning, and who want to demonstrate their expertise in this area to potential employers.

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Topics of AI-102: Designing and Implementing an Azure AI Solution Exam

Candidates should apprehend the examination topics before they begin of preparation.because it'll extremely facilitate them in touch the core. Our AI-102 exam dumps will include the following topics:

1. Analyze solution requirements (25-30%)

Recommend Cognitive Services APIs to meet business requirements

  • Identify automation requirements
  • Select the appropriate AI models and services
  • Identify components and technologies required to connect service endpoints
  • Select the processing architecture for a solution
  • Select the appropriate data processing technologies

Map security requirements to tools, technologies, and processes

  • Identify appropriate tools for a solution
  • Identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements
  • Identify which users and groups have access to information and interfaces
  • Identify auditing requirements

Select the software, services, and storage required to support a solution

  • Identify storage required to store logging, bot state data, and Cognitive Services output
  • Identify integration points with other Microsoft services
  • Identify appropriate services and tools for a solution

2. Design AI solutions (40-45%)

Design solutions that include one or more pipelines

  • Define an AI application workflow process
  • Design a strategy for ingest and egress data
  • Design pipelines that use AI apps
  • Design the integration point between multiple workflows and pipelines
  • Select an AI solution that meet cost constraints

Design solutions that uses Cognitive Services

  • Design solutions that use vision, speech, language, knowledge, search, and anomaly detection APIs

Design solutions that implement the Bot Framework

  • Integrate bots and AI solutions
  • Integrate bots with Azure app services and Azure Application Insights
  • Design bot services that use Language Understanding (LUIS)
  • Design bots that integrate with channels

Design the compute infrastructure to support a solution

  • Identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure
  • Select a compute solution that meets cost constraints
  • Identify whether to create a GPU, FPGA, or CPU-based solution

Design for data governance, compliance, integrity, and security

  • Define how users and applications will authenticate to AI services
  • Ensure appropriate governance of data
  • Design strategies to ensure that the solution meets data privacy regulations and industry standards
  • Design a content moderation strategy for data usage within an AI solution
  • Ensure that data adheres to compliance requirements defined by your organization

3. Implement and monitor AI solutions (25-30%)

Implement an AI workflow

  • Manage the flow of data through the solution components
  • Develop streaming solutions
  • Implement data logging processes
  • Develop AI pipelines
  • Create solution endpoints

Integrate AI services with solution components

  • Configure prerequisite components to allow connectivity to the Bot Framework
  • Implement Azure Search in a solution
  • Configure integration with Cognitive Services
  • Configure prerequisite components and input datasets to allow the consumption of Cognitive Services APIs

Monitor and evaluate the AI environment

  • Maintain an AI solution for continuous improvement
  • Recommend changes to an AI solution based on performance data
  • Monitor AI components for availability
  • Identify the differences between KPIs, reported metrics, and root causes of the differences
  • Identify the differences between expected and actual workflow throughput

Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q195-Q200):

NEW QUESTION # 195
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:


NEW QUESTION # 196
You are developing a new sales system that will process the video and text from a public-facing website.
You plan to notify users that their data has been processed by the sales system.
Which responsible AI principle does this help meet?

  • A. inclusiveness
  • B. reliability and safety
  • C. transparency
  • D. fairness

Answer: C

Explanation:
Explanation
"When an AI application relies on personal data, such as a facial recognition system that takes images of people to recognize them; you should make it clear to the user how their data is used and retained, and who has access to it." from: https://docs.microsoft.com/en-us/learn/paths/prepare-for-ai-engineering/


NEW QUESTION # 197
You are using a Language Understanding service to handle natural language input from the users of a web- based customer agent.
The users report that the agent frequently responds with the following generic response: "Sorry, I don't understand that." You need to improve the ability of the agent to respond to requests.
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.)

Answer:

Explanation:

Explanation:
- enable active learning
- validate the utterances
- train and republish
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-review-endpoint-utterances#log- user-queries-to-enable-active-learning
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-prebuilt-model


NEW QUESTION # 198
You have a chatbot that uses a QnA Maker application.
You enable active learning for the knowledge base used by the QnA Maker application.
You need to integrate user input into the model.
Which four 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:

1 - For the knowledge base, select Show active learning suggestions.
2 - Approve and reject suggestions.
3 - Save and train the knowledge base.
4 - Publish the knowledge base.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/improve-knowledge-base


NEW QUESTION # 199
You train a Custom Vision model to identify a company's products by using the Retail domain.
You plan to deploy the model as part of an app for Android phones.
You need to prepare the model for deployment.
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
In user want to change to deploy offline model
1. Change model domain to compact model
2. Retrain compact model
3. Export model
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/export-your-model


NEW QUESTION # 200
......

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