Exam Details
Speaking of the exam details, the test will contain from 40 to 60 questions of various types which you need to complete within 100 or 120 minutes (depends on the inclusion of labs). To pass the exam you need to schedule the test on the PearsonVUE platform, pay an exam fee which is currently $165, and score at least 700 points or more out of 1000. And, of course, the knowledge of exam topics is a must.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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Who should take the AI-102: Designing and Implementing an Azure AI Solution Exam
The AI-102 Exam certification is an internationally-recognized certification which help to have validation for Azure AI Solution Architects who have ability to accomplish the following technical tasks: analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.
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Microsoft AI-102 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement generative AI solutions | 15-20% | - Deploy and manage generative models - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers - Implement model monitoring and feedback - Apply prompt engineering and fine-tuning |
| Implement an agentic solution | 5-10% | - Develop multi-agent workflows and orchestration - Test, deploy, and optimize agents - Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types |
| Plan and manage an Azure AI solution | 20-25% | - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources - Plan solutions aligned with responsible AI principles - Monitor, optimize, and secure AI solutions - Select suitable AI models |
| Implement knowledge mining and information extraction solutions | 15-20% | - Ingest and process structured/unstructured data - Implement intelligent search and retrieval - Build knowledge bases and search indexes - Extract entities, relationships, and key phrases |
| Implement computer vision solutions | 10-15% | - Extract text and handwriting from images - Build and deploy custom vision models - Integrate vision capabilities into applications - Analyze images and detect objects/features - Process and index video content |
| Implement natural language processing solutions | 15-20% | - Implement translation and summarization - Build conversational AI and chatbots - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection |
Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102 Korean Version) Sample Questions:
lu1이라는 언어 이해 리소스가 있습니다.
lu1을 사용하는 bot1이라는 Azure 봇을 빌드하고 배포합니다.
bot1이 Microsoft의 책임 있는 AI 원칙인 포괄성을 준수하는지 확인해야 합니다.
bot1을 어떻게 확장해야 하나요?
- A. 컨테이너의 호스트 Iu1.
- B. bot1에 직접 대화 기능을 추가합니다.
- C. Iu1에 대한 능동 학습을 활성화합니다.
- D. bot1에 대한 인증을 구현합니다.
Correct Answer: B 🗳️
Explanation: Only visible for TrainingDumps members. You can sign-up / login (it's free).
Azure AI 에이전트 솔루션을 보유하고 계십니다.
귀하는 사용자 데이터를 분석 및 요약하고 데이터 기반 추천을 생성하는 에이전트 기반 앱인 App1을 개발할 계획입니다. App1은 기술적인 지식이 없는 비즈니스 사용자가 사용할 것이며, 새롭고 예측 불가능한 비즈니스 문제에 적응하고 시간이 지남에 따라 성능을 개선해야 합니다.
App1에서 사용할 에이전트 유형을 식별해야 합니다. 솔루션은 다음 요구 사항을 충족해야 합니다.
* 사용자 피드백을 기반으로 시간이 지남에 따라 상담원의 성능을 조정하고 개선합니다.
* 사용자가 정보에 입각한 결정을 내릴 수 있도록 맞춤형 추천을 제공합니다.
* 앱의 최상의 성능을 제공합니다.
어떤 에이전트 유형을 식별해야 합니까?
- A. 프롬프트 및 응답
- B. 인지적
- C. 작업 자동화
- D. 자율적인
Correct Answer: D 🗳️
고객이 Azure Cognitive Search를 사용하고 있습니다.
고객은 서버 측 암호화를 활성화하고 Azure에 저장된 고객 관리 키(CMK)를 사용할 계획입니다.
계획된 변경의 세 가지 의미는 무엇입니까? 각 정답은 완전한 해결책을 제시합니다.
참고: 정답 하나당 1점입니다.
- A. Azure Key Vault가 필요합니다.
- B. 자체 서명된 X.509 인증서가 필요합니다.
- C. 인덱스 크기가 증가합니다.
- D. 인덱스 크기가 감소합니다.
- E. 쿼리 시간이 증가합니다.
- F. 쿼리 시간이 감소합니다.
Correct Answer: A,C,E 🗳️
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이동 중 쇼핑 프로젝트를 개발하고 있습니다.
챗봇을 위한 적응형 카드를 구축해야 합니다.
코드는 어떻게 작성해야 하나요? 답변하려면 답변 영역에서 적절한 옵션을 선택하세요.
참고: 정답 하나당 1점입니다.
Correct Answer:
Explanation:
Comprehensive Detailed Explanation
The requirement is to build an Adaptive Card for the chatbot that supports multilingual product display and meets accessibility requirements.
Product Name Display
The product JSON stores localized names like " name " : { " en " : " ... " , " es " : " ... " , " pt " : " ... " } .
To dynamically render based on the current language, you must use name[language].
This ensures the product name shown in the card adapts automatically to the user's preferred language.
Stock Level Warning
Business rules require warnings when stock is low or out of stock.
This means you display the stock warning only when stockLevel is not ' OK ' .
Therefore, the correct condition is:
" $when " : " ${stockLevel != ' OK ' } "
Image Alt Text for Accessibility
Accessibility requirements specify that all images must have alt text in English, Spanish, and Portuguese.
In the product JSON, " alttext " is also localized:
" altText " : { " en " : " Bicycle " , " es " : " Bicicleta " , " pt " : " Bicicleta " } To render the correct localized alt text dynamically, use image.altText[language].
Correct Selections:
First blank: name[language]
Second blank: " $when " : " ${stockLevel != ' OK ' } "
Third blank: image.altText[language]
Microsoft References
Adaptive Cards Templating
Adaptive Card $when property
Multilingual data in Azure Cognitive Search and Adaptive Cards
O에서 음성-음성 번역을 수행하는 App1이라는 앱을 개발합니다.
영어를 독일어로 번역하려면 App1을 구성해야 합니다.
speechTransiationConf ig 객체를 어떻게 완성해야 할까요? 정답은 적절한 값을 적절한 대상에 드래그하여 배치하는 것입니다. 각 값은 한 번, 여러 번 또는 전혀 사용되지 않을 수 있습니다. 콘텐츠를 보려면 창 사이의 분할 막대를 드래그하거나 스크롤해야 할 수도 있습니다.
참고: 정답 하나당 1점입니다.
Correct Answer:
Explanation:
You are configuring speech-to-speech translation in an app. The workflow is:
Recognize spoken input language (in this case, English).
Translate the recognized text into the target language (in this case, German).
(Optional) Synthesize speech in the target language.
Step 1 - SpeechRecognitionLanguage
This property defines the input language for speech recognition.
Since the input is English, it should be set to " en-US " .
Step 2 - AddTargetLanguage
This method specifies the output translation language(s).
Since the requirement is to translate into German, use " de " .
Other options (incorrect here):
speechSynthesisLanguage # used if you want to output translated text as synthesized speech in the target language voice. Not required in this snippet.
voiceName # specifies the actual voice to use for speech synthesis, not translation.
Correct Completed Code Snippet:
var translationConfig = SpeechTranslationConfig.FromSubscription(SPEECH_SUBSCRIPTION_KEY, SPEECH_SERVICE_REGION); translationConfig.SpeechRecognitionLanguage = " en-US " ; translationConfig.AddTargetLanguage( " de " ); Microsoft References Speech Translation with Azure AI Speech SDK SpeechTranslationConfig Class Reference
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