PDF Version DemoHow to Prepare For AI-900: Microsoft Azure AI Fundamentals
Preparation Guide for AI-900: Microsoft Azure AI Fundamentals
Introduction
Microsoft AI-900 exam is designed for Microsoft partners who are certified by Microsoft to integrate Microsoft Azure Intelligent Solutions into their own products and solutions. The objective of the certification is to verify that approved partners have the knowledge and skills to deploy, configure, set up, activate, maintain, troubleshoot, and support all necessary Azure services. Microsoft AI-900 exam dumps exam tests Questions are designed to identify the exam taker level of competence in the functions, features, and services of Azure. The Microsoft AI-900 Certification Exam is a three to five-hour exam that covers the technologies necessary for building intelligent applications for cloud computing. Students should have a solid knowledge of Microsoft Azure IaaS, services, APIs, SQL Server 2017, and NET Framework. Courses are available online or in-person depending on individual needs.
This article will cover the areas of knowledge required for this exam, how many questions are covered in each area, and who is taking this certification exam.
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Learning Path
All in all, Microsoft provides two ways to help candidates prepare for the Microsoft AI-900 exam. These include the free online learning option and the paid, instructor-led training. Let’s discuss the two most popular courses offered by each of these options by the vendor:
- Microsoft Azure AI Fundamentals
This one-day course is part of the instructor-led learning platform and is, therefore, a paid option. As the name suggests, it is meant to introduce the candidates to fundamental AI concepts. The training, in particular, emphasizes the skills you need to become well versed in AI workloads and understand the Azure services that support such solutions. Usually, the course curriculum is viewed as comprehensive blended learning, featuring a combination of online materials and instructor-led training to ensure candidates have a good grasp of the exam topic areas. Even more, the hands-on exercises that are featured here are meant to help learners understand the test domains in real-world scenarios. Familiarity with the internet and computer technology is not a prerequisite but a great combination that will go a long way toward helping you register excellent results in this course and the ultimate exam.
- Get Started with Artificial Intelligence
The online gratis class, “Get Started with Artificial Intelligence” features one module and is intended to run for a maximum of 34 minutes. In general, this course is designed to help you get started with Microsoft services that empower new AI solutions. There are no prerequisites associated with this training. However, it features one module with a total of 10 units including the introduction and an understanding of machine learning, anomaly detection, computer vision, natural language processing, conversational AI, and responsible AI just to mention a few. Visit the official certification page to find out more information about this learning path that also includes classes on ML, NLP, and conversational AI.
The Microsoft AI-900: Microsoft Azure AI Fundamentals exam is aimed at those professionals who want to demonstrate their knowledge of basic Machine Learning (ML) and Artificial Intelligence (AI) workloads. The test evaluates their understanding of how to implement both ML and AI on Azure. The candidates who pass this exam are eligible for the Microsoft Certified: Azure AI Fundamentals certification.
Microsoft Azure AI Fundamentals Exam Certification Details:
| Schedule Exam | Pearson VUE |
| Number of Questions | 40-60 |
| Books / Training | Course AI-900T00: Microsoft Azure AI Fundamentals |
| Exam Price | $99 (USD) |
| Duration | 60 mins |
| Exam Name | Microsoft Certified - Azure AI Fundamentals |
| Exam Code | AI-900 |
| Passing Score | 700 / 1000 |
| Sample Questions | Microsoft Azure AI Fundamentals Sample Questions |
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
Microsoft AI-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamental principles of machine learning on Azure | 15–20% | - Describe machine learning pipelines - Describe capabilities of Azure Machine Learning - Describe core concepts of machine learning - Describe automated machine learning |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Identify types of NLP solutions - Describe capabilities of Azure Language - Describe capabilities of Azure Speech - Describe capabilities of Azure Translator |
| Features of generative AI workloads on Azure | 20–25% | - Describe responsible AI practices for generative AI - Describe use cases for generative AI - Describe capabilities of Azure OpenAI Service - Describe generative AI concepts |
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Face - Identify types of computer vision solutions - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Custom Vision |
| Artificial Intelligence workloads and considerations | 15–20% | - Describe considerations for developing AI solutions - Describe responsible AI principles - Identify types of AI workloads |
Microsoft Azure AI Fundamentals (AI-900 Korean Version) Sample Questions:
특정 기간 동안 발생한 택시 여행에 대한 정보가 포함된 데이터 세트가 있습니다.
택시 요금을 예측하려면 모델을 학습해야 합니다.
어떤 기능을 사용해야 하나요?
- A. 개별 택시 여행의 여행 거리
- B. 개인 택시 여행 요금
- C. 데이터 세트의 택시 여행 횟수
- D. 개별 택시 여행의 여행 ID
Correct Answer: A 🗳️
Explanation: Only visible for ActualPDF members. You can sign-up / login (it's free).
회귀 모델을 평가하는 데 사용할 수 있는 두 가지 지표는 무엇입니까? 각 정답은 완전한 해답을 제시합니다.
참고: 정답 하나당 1점입니다.
- A. 평균 제곱근 오차(RMSE)
- B. 곡선 아래 면적(AUC)
- C. 결정계수(R2)
- D. F1 점수
- E. 균형 잡힌 정확도
Correct Answer: A,C 🗳️
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컴퓨터 비전의 유형을 적절한 시나리오에 맞춰 연결하세요.
답변하려면 왼쪽 열에서 적절한 워크로드 유형을 오른쪽의 해당 시나리오로 드래그하세요. 각 워크로드 유형은 한 번, 여러 번 또는 전혀 사용되지 않을 수 있습니다.
참고: 정답 하나당 1점입니다.
Correct Answer:
Explanation:
The correct mappings are based on the Microsoft Azure AI Fundamentals (AI-900) curriculum topic:
"Describe features of computer vision workloads." Microsoft divides computer vision tasks into key workload types - image classification, object detection, facial recognition, and optical character recognition (OCR) - each designed for specific visual analysis objectives.
* Identify celebrities in images # Facial recognitionFacial recognition goes beyond simple face detection; it can identify or verify specific individuals by comparing facial features with known profiles.
According to Microsoft Learn, the Face service in Azure Cognitive Services can detect, recognize, and identify people in photos or videos. Recognizing celebrities or known individuals is a prime example of facial recognition.
* Extract movie title names from movie poster images # Optical Character Recognition (OCR)OCR is used to detect and extract text content from images, such as printed or handwritten words. Azure's Computer Vision API uses OCR technology to read text in various languages from photos, scanned documents, or posters. Therefore, extracting movie titles or actor names from a poster image is a perfect use case for OCR.
* Locate vehicles in images # Object detectionObject detection identifies and locates specific objects within an image, returning bounding boxes that indicate their positions. In Azure, the Custom Vision service or Computer Vision object detection models are used to detect multiple objects like vehicles, pedestrians, or animals in a single image.
Summary:
* Facial recognition # Identifies specific people (celebrities)
* OCR # Extracts text (movie titles)
* Object detection # Finds and locates physical items (vehicles)
Thus, the verified and official answer is:
Form Recognizer에서 사용자 정의 모델을 사용하면 어떤 이점이 있나요?
- A. 사용자 정의 모델은 항상 더 높은 정확도를 제공합니다.
- B. 사용자 정의 모델은 다양한 양식 유형을 인식하도록 훈련될 수 있습니다.
- C. 맞춤형 모델은 사전 구축된 모델보다 비용이 저렴합니다.
- D. 사용자 정의 모델만 온프레미스에 배포할 수 있습니다.
Correct Answer: B 🗳️
Explanation: Only visible for ActualPDF members. You can sign-up / login (it's free).
다음 각 문장에 대해, 문장이 사실이라면 '예'를 선택하세요. 그렇지 않으면 '아니요'를 선택하세요.
참고: 정답 하나당 1점입니다.
Correct Answer:
Explanation:
This question is based on identifying Natural Language Processing (NLP) workloads, which is a fundamental topic in the Microsoft Azure AI Fundamentals (AI-900) certification. According to the official Microsoft Learn module "Describe features of natural language processing (NLP) workloads on Azure", NLP enables computers to understand, interpret, and generate human language - both written and spoken.
* A bot that responds to queries by internal users - YesThis is an example of a natural language processing workload because it involves understanding and generating human language. A chatbot interprets user input (queries written or spoken) using language understanding and text analytics, and then produces appropriate responses. On Azure, this can be implemented using Azure AI Language (LUIS) and the Azure Bot Service, both core NLP technologies.
* A mobile application that displays images relating to an entered search term - NoThis application involves searching for or displaying images, which falls under the computer vision workload, not NLP.
Computer vision focuses on analyzing and interpreting visual data like photos or videos, while NLP deals with language and text processing.
* A web form used to submit a request to reset a password - NoA password reset form involves structured input fields and user authentication, not natural language understanding or generation. It's part of standard web development and identity management, not an NLP-related process.
Therefore, based on Microsoft's AI-900 curriculum definitions:
# The only true NLP example is the bot responding to user queries, since it processes and understands natural language input to generate conversational output.
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