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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Exam Format: | Multiple select, Multiple choice, Scenario-based questions |
| Exam Price: | $99 USD |
| Related Certifications: | Microsoft Certified: Azure Fundamentals Microsoft Certified: Azure Data Fundamentals |
| Certificate Validity Period: | Valid indefinitely |
| Available Languages: | Italian, Korean, French, Spanish, Chinese (Simplified), German, Russian, Chinese (Traditional), Indonesian (Indonesia), English, Arabic (Saudi Arabia), Japanese, Portuguese (Brazil) |
| Exam Duration: | 45 minutes |
| Passing Score: | 700 (on a scale of 1–1000) |
| Real Exam Qty: | 40–60 |
| Recommended Training: | Instructor-led Training: AI-900 Course Microsoft Learn: Azure AI Fundamentals Learning Path |
| Exam Registration: | Microsoft Certification Registration Pearson VUE Registration |
| Sample Questions: | Microsoft AI-900 Sample Questions |
| Exam Way: | Online proctored or onsite testing at Pearson VUE test centers |
| Pre Condition: | No required prerequisites; basic familiarity with cloud computing or AI concepts is recommended but not mandatory |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900/ |
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The AI-900 exam covers a range of topics, including AI workloads and considerations, fundamental principles of machine learning, and common machine learning scenarios and algorithms. AI-900 exam also covers Azure AI services and tools such as Azure Cognitive Services, Azure Machine Learning, and Azure Bot Service. Passing AI-900 exam demonstrates that an individual has a good understanding of AI and its applications in Azure and is capable of designing and implementing AI solutions using Azure services.
Passing the Microsoft AI-900 certification exam is a valuable credential for those seeking to demonstrate their expertise in AI and the Azure platform. It can help individuals stand out from the competition in the job market and open up new opportunities for career advancement. Additionally, it provides a foundation for those who wish to pursue further certifications in AI or Azure.
Microsoft AI-900 Certification Exam is an excellent starting point for individuals who want to build their career in the field of AI and ML. Microsoft Azure AI Fundamentals certification provides a solid foundation for understanding the basic principles of AI and how it can be used to solve real-world problems. It also helps individuals to gain hands-on experience in using Microsoft Azure to implement AI solutions. Microsoft Azure AI Fundamentals certification is suitable for anyone who wants to learn about AI, including developers, IT professionals, data scientists, and business analysts.
NEW QUESTION # 209
A medical research project uses a large anonymized dataset of brain scan images that are categorized into predefined brain haemorrhage types.
You need to use machine learning to support early detection of the different brain haemorrhage types in the images before the images are reviewed by a person.
This is an example of which type of machine learning?
Answer: A
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features of classification machine learning", classification is a supervised machine learning technique used when the output variable represents discrete categories or classes. In this case, the brain scan images are already labeled into predefined haemorrhage types, such as "subarachnoid," "epidural," or
"intraventricular." The model's goal is to learn patterns from labeled examples and then predict the correct class for new, unseen images.
The use of categorized brain scan images clearly indicates a supervised learning setup because both the input (image data) and output (haemorrhage type) are known during training. This aligns with Microsoft's definition: classification problems "predict which category or class an item belongs to," often using algorithms such as logistic regression, decision trees, neural networks, or convolutional neural networks (CNNs) for image-based data.
In contrast:
* A. Clustering is an unsupervised learning approach that groups data into clusters based on similarity when no predefined labels exist.
* B. Regression predicts continuous numeric values (e.g., predicting age or temperature), not categories.
Because this project aims to automatically classify medical images into known diagnostic categories, it is a textbook example of classification.
Reference:Microsoft Learn - Identify common types of machine learning models: Regression, Classification, and Clustering (AI-900 Learning Path)
NEW QUESTION # 210
You plan to use Azure Machine Learning Studio and automated machine learning (automated ML) to build and train a model What should you create first?
Answer: B
Explanation:
Before building or training any model in Azure Machine Learning Studio-including when using Automated ML (AutoML)-you must first create a Machine Learning workspace.
A workspace serves as the central environment for all machine learning assets such as datasets, compute targets, models, pipelines, and experiments. According to the AI-900 study guide and Microsoft Learn module
"Describe features and tools for machine learning in Azure," a workspace is the foundational setup required to organize and manage all ML-related resources.
The sequence typically follows these steps:
* Create a Machine Learning workspace.
* Configure compute resources (e.g., compute instance or cluster).
* Upload or register datasets.
* Use Automated ML or Designer to train models.
* Deploy and manage the trained models.
Option A (Jupyter notebook) is an optional tool for coding experiments.
Option C (Registered dataset) is created after the workspace exists.
Option D (Designer pipeline) is a visual tool used within the workspace.
Hence, B. a Machine Learning workspace is the correct answer because it is the first and mandatory step before using Automated ML or any training component in Azure Machine Learning Studio.
NEW QUESTION # 211
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
The correct completion of the sentence is:
"The interactive answering of questions entered by a user as part of an application is an example of natural language processing." According to the Microsoft Azure AI Fundamentals (AI-900) official study materials, Natural Language Processing (NLP) is a branch of Artificial Intelligence that focuses on enabling computers to understand, interpret, and respond to human language in a way that is both meaningful and useful. It is one of the key AI workloads described in the "Describe features of common AI workloads" module on Microsoft Learn.
When a user types a question into an application and the system responds interactively - such as in a chatbot, Q&A system, or virtual assistant - this process requires language understanding. NLP allows the system to process the input text, determine user intent, extract relevant entities, and generate an appropriate response. This is the foundational capability behind services such as Azure Cognitive Service for Language, Language Understanding (LUIS), and QnA Maker (now integrated as Question Answering in the Language service).
Microsoft's study guide explains that NLP workloads include the following key scenarios:
* Language understanding: Determining intent and context from text or speech.
* Text analytics: Extracting meaning, key phrases, sentiment, or named entities.
* Conversational AI: Powering bots and virtual agents to interact using natural language.These systems rely on NLP models to analyze user inputs and respond accordingly.
In contrast:
* Anomaly detection identifies data irregularities.
* Computer vision analyzes images or video.
* Forecasting predicts future values based on historical data.
Therefore, based on the AI-900 official materials, the interactive answering of user questions through an application clearly falls under Natural Language Processing (NLP).
NEW QUESTION # 212
For each of the following statements. select Yes if the statement is true. Otherwise, select No. NOTE; Each correct selection is worth one point
Answer:
Explanation:
Explanation:
NEW QUESTION # 213
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
NEW QUESTION # 214
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