Accelerate Your Career: Microsoft AI-102 Exam Dumps for Advancement

Does the score report show a numerical score for each section?

The score reports provide an overall numerical score to reflect the pass/fail status only. As an alternative to providing a numerical score for each section, we provide score bars to show subject areas of strength and weakness.

How are exam scores calculated? After you AI-102 Questions complete your exam, the points you earned on each question are summed and then compared with the cut score to determine whether the result is pass or fail.

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If I receive the same score every time I retake the same exam, does this imply an error in the results computation?

No. Receiving the same score on multiple attempts does not indicate that the program computing the results is in error. It is not uncommon for candidates to obtain similar or identical scores on multiple attempts of an exam. This consistent result demonstrates the reliability of the exam in evaluating skills in this content domain. If this happens on multiple attempts, you may want to reconsider how you’re preparing for the exam and seek other opportunities to learn and practice the skills measured by the exam.

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If I do not pass, what can I do?

Prioritize the skills that you should practice by focusing on the content areas where your exam performance was the weakest and in the content areas that have the highest percentage of questions. Additionally, you may want to review the resources provided on the exam details page, and our Study Groups, which can be found at the bottom of the individual exam details page. When you are ready to retake the exam, schedule an appointment as you normally would. Note that you must pay for each exam you retake and follow Microsoft’s retake policy.

Take this Designing and Implementing a Microsoft Azure AI Solution: AI-102 exam and become a part of the futuristic world of Artificial Intelligence and grow your career by attaining Azure AI-102 certification.

In This AI-102: Designing and Implementing a Microsoft Azure AI Solution course you will learn how to design, manage, and deploy Microsoft Azure AI solutions that use Azure Cognitive Services and Applied AI services.

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To prepare for the AI-102 certification exam, we provide 110 practice tests with a detailed explanation of answers which are very similar to the actual exam.

By the end of this course, you will be able to pass the AI-102 exam on the first attempt and master yourself in Designing and Implementing a Microsoft Azure AI Solution.

• Key Features of the Course
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• Objective-Based Practice Tests
• Exhaustive Explanation with every question
• Reports to assess strengths & weaknesses
• Unlimited Access for 2 years
• 24x7 Support from our Subject Matter Experts
• Auto-updates to the AI-102 course content

Requirements / Skills Required for taking the AI-102 exam

Candidates who are appearing for this AI 102 exam should have the below skills:

Developing an Azure Cognitive Services strategy and Implementing.

• Computer Vision solutions may be implemented
• Develop natural language processing applications
• Knowledge-mining solutions should be implemented

Make use of AI conversational assistants.

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What you'll learn in the AI-102 Designing and Implementing a Microsoft Azure AI Solution certification exam?

The AI-102: Designing and Implementing a Microsoft Azure AI Solution exam covers the following domains and it is significant to get familiar with the below concepts to pass the exam:

Plan and manage an Azure AI solution (25–30%): In this domain, you can get overview of the following topics such as selection of appropriate Azure AI service , configuration of security for Azure AI services, Creation and management of Azure AI service, deployment of Azure AI services and Creation of solutions to detect anomalies and improvise the content.

Implement image and video processing solutions (15–20%): In this part, you will get the information on how to analyze the images and extract text from images,  image classification and object detection by using Vision service and process videos.

Implement natural language processing solutions (25–30%): It might cover up the topics such as analyzing text, processing speech, translating language, building and managing a language understanding model.

Implement knowledge mining solutions (5–10%): You can be familiar with the key concepts such as Implement a Cognitive Search solution and application of AI enrichment skills to an indexer pipeline.

Implement conversational AI solutions (15–20%): You might get into the topics in this domain such as design and implement conversation flow and building a conversational bot.

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