Skills measured
- Describe features of conversational AI workloads on Azure (15-20%)
- Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
- Describe fundamental principles of machine learning on Azure (30-35%)
- Describe features of computer vision workloads on Azure (15-20%)
- Describe AI workloads and considerations (15-20%)
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Explain Conversational Artificial Intelligence Workloads Features on Azure (15-20%)
In the last section, you will face with the following subtopics:
- Establish Azure services for Conversational Artificial Intelligence – The potential candidates for the Microsoft AI-900 exam should have the capacity to identify the capabilities of Azure Bot Service and QnA Maker service.
- Identify the basic use cases for Conversational Artificial Intelligence (AI) – The students should be able to identify the features and usage for a range of elements. These include personal digital assistants, webchat bots, and telephone voice menus. It also covers the skills in identifying the basic features of conversational Artificial Intelligence solutions.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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Target Audience
The Microsoft AI-900 exam is designed for those individuals who have little to no experience in the world of IT. It is aimed at the students with both non-technical and technical backgrounds. They have basic programming experience and knowledge. However, they are not required to have software engineering or data science experience.
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Career Prospects
Although the Microsoft AI-900 exam is associated with the foundational-level certification, all the successful candidates can pursue various lucrative career paths in the field of IT. Some of the job roles that these professionals can work in include a Data Scientist, a Software Developer, and an Azure AI Engineer, among others. They can also proceed to get some other role-based certificates to boost their potential in the world of Information Technology. With the Microsoft Certified: Azure AI Fundamentals certification, you can earn an average of $48,000 per annum as an entry-level specialist. Those with some work experience can get an average of $74,000 per year.
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Microsoft AI-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Describe features of Generative AI workloads on Azure | 15-20% | - Identify responsible AI considerations for generative AI - Describe generative AI concepts - Describe Azure OpenAI Service capabilities |
| Describe AI workloads and considerations | 15-20% | - Identify guiding principles for responsible AI - Identify features of common AI workloads |
| Describe fundamental principles of machine learning on Azure | 30-35% | - Describe core machine learning concepts - Identify common machine learning tasks - Describe features of no-code automated ML - Describe Azure Machine Learning capabilities |
| Describe features of computer vision workloads on Azure | 15-20% | - Describe Azure capabilities for computer vision - Identify Azure AI services for computer vision - Identify common computer vision tasks |
| Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify common NLP tasks - Describe Azure capabilities for NLP - Identify Azure AI services for NLP |
Microsoft Azure AI Fundamentals (AI-900 Korean Version) Sample Questions:
Foundry Tools의 Azure Document Intelligence에 있는 사전 구축된 영수증 모델을 사용할 수 있는 Azure 서비스는 무엇입니까?
- A. Azure Al Custom Vision
- B. Microsoft Foundry 서비스
- C. Foundry Tools의 Azure Vision
- D. Azure 머신 러닝
Correct Answer: B 🗳️
다음 각 문장에 대해, 문장이 사실이라면 '예'를 선택하세요. 그렇지 않으면 '아니요'를 선택하세요.
참고: 정답 하나당 1점입니다.
Correct Answer:

Explanation:
Yes, Yes, and No.
According to the Microsoft Azure AI Fundamentals (AI-900) official study materials and the Microsoft Learn module "Identify features of natural language processing (NLP) workloads on Azure", the Azure Translator service is a cloud-based AI service within Azure Cognitive Services that provides real-time text translation across multiple languages.
* "You can use the Translator service to translate text between languages." - Yes.This is the core function of the Translator service. It takes text as input in one language and returns it in another using advanced neural machine translation models. This aligns with the AI-900 learning objective: "Describe the capabilities of Azure Cognitive Services for language", which specifically names Azure Translator as the service used to perform automatic text translation. The service supports over 100 languages and dialects, offering both single-sentence and document-level translations.
* "You can use the Translator service to detect the language of a given text." - Yes.This statement is also true. The Translator service automatically detects the source language if it is not specified in the request. This feature is documented in the Azure Translator API, where the system identifies the input language before performing translation. The AI-900 exam content emphasizes this as one of the Translator service's built-in capabilities-language detection for untagged text.
* "You can use the Translator service to transcribe audible speech into text." - No.This is not a function of Translator. Transcription (converting speech to text) is a speech AI workload, handled by the Azure Speech Service, not Translator. The Speech-to-Text capability in Azure Cognitive Services processes spoken audio input and returns the text transcription. The Translator service only works with text input, not direct audio.
Therefore, based on official AI-900 guidance, the verified configuration is:
# Yes - for text translation
# Yes - for language detection
# No - for speech transcription.
This aligns precisely with the AI-900 learning outcomes describing Text Translation and Language Detection as Translator capabilities, and Speech Transcription as part of the separate Speech service.
스캔한 계약서 이미지에서 세부 정보를 추출하려면 어떤 도구를 사용해야 할까요?
- A. Azure AI 검색
- B. Azure AI 문서 인텔리전스
- C. Azure AI 몰입형 리더
[출처]: Azure OpenAI
Correct Answer: B 🗳️
문장을 올바르게 완성하는 답을 선택하세요.
Correct Answer:

Explanation:
In the Microsoft Azure AI Fundamentals (AI-900) curriculum, computer vision capabilities refer to artificial intelligence systems that can analyze and interpret visual content such as images and videos. The Azure AI Vision and Face API services provide pretrained models for detecting, recognizing, and analyzing visual information, enabling developers to build intelligent applications that understand what they " see. " When asked how computer vision capabilities can be deployed, the correct answer is to integrate a face detection feature into an app. This aligns with Microsoft Learn's module "Describe features of computer vision workloads," which explains that computer vision can identify objects, classify images, detect faces, and extract text (OCR). The Face API, a part of Azure AI Vision, specifically provides face detection, verification, and emotion recognition capabilities.
Integrating these services into an application allows it to perform actions such as:
* Detecting human faces in photos or video streams.
* Recognizing facial attributes like age, emotion, or head pose.
* Enabling secure authentication based on face recognition.
The other options are incorrect because they relate to different AI workloads:
* Develop a text-based chatbot for a website: This falls under Conversational AI, implemented with Azure Bot Service or Conversational Language Understanding (CLU).
* Identify anomalous customer behavior on an online store: This task relates to machine learning and anomaly detection models, not computer vision.
* Suggest automated responses to incoming email: This uses Natural Language Processing (NLP) capabilities, not visual analysis.
Therefore, the correct and Microsoft-verified completion of the statement is:
"Computer vision capabilities can be deployed to integrate a face detection feature into an app."
귀사에서 병 재활용 기계를 제작하려고 합니다. 재활용 기계는 올바른 모양의 병을 자동으로 식별하고 나머지는 모두 폐기해야 합니다.
회사에서는 어떤 유형의 AI 워크로드를 사용해야 합니까?
- A. 컴퓨터 비전
- B. 자연어 처리
- C. 이상 감지
- D. 대화형 AI
Correct Answer: A 🗳️
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