AI-900 Azure AI Fundamentals Practice Exam Questions 2025

AI-900 Azure AI Fundamentals Practice Exam Questions 2025
Published 11/2025
Duration: 49m | .MP4 1280×720 30fps(r) | AAC, 44100Hz, 2ch | 335.51 MB

AI 900 Azure AI Fundamentals Exam Preparation Course, AI-900 Azure AI Fundamentals with 324 Practice Exam Questions

What you’ll learn
– From Video Quiz, Students will Gain Confidence Face Real Exam Question
– Attend Original Exam like Question
– Practice with more than 300 Questions
– Learn from the explanation provided in each solution

Requirements
– Familiarity with cloud computing, AI and Azure services will significantly aid your preparation.

Description
Prepare for the AI-900 or AI 900 exam with confidence! This set includes324 unique practice questionscreated from scratch and fully compliant with theofficial 2025 exam syllabus.

The AI-900 exam syllabus is structured around five main domains, covering core AI/ML concepts and how they are implemented using Microsoft Azure AI services.

Domain Approximate Weighting

2. Describe fundamental principles of machine learning on Azure 15-20%

3. Describe features of computer vision workloads on Azure 15-20%

4. Describe features of Natural Language Processing (NLP) workloads on Azure 15-20%

5. Describe features of generative AI workloads on Azure 20-25%

Identify features of common AI workloads: computer vision, NLP, document processing, generative AI.

Identify guiding principles for responsible AI: fairness, reliability & safety, privacy & security, inclusiveness, transparency, accountability.

2.Describe fundamental principles of machine learning on Azure(15-20%)

Identify common machine learning techniques: regression, classification, clustering, deep learning, Transformer architecture.

Describe core machine learning concepts: features and labels, training vs validation datasets.

Describe Azure Machine Learning capabilities: automated ML, data & compute services, model management & deployment.

3.Describe features of computer vision workloads on Azure(15-20%)

Identify Azure tools & services: e.g., Azure AI Vision, Azure AI Face detection service.

4.Describe features of Natural Language Processing (NLP) workloads on Azure(15-20%)

Identify features & uses of NLP scenarios: key phrase extraction, entity recognition, sentiment analysis, language modelling, speech recognition & synthesis, translation.
Identify Azure tools & services for NLP workloads: e.g., Azure AI Language, Azure AI Speech.

5. Describe features of generative AI workloads on Azure(20-25%)

Identify features of generative AI models and common use-cases.

Identify generative AI services/capabilities in Azure: e.g., Azure OpenAI Service, Azure AI Foundry (model catalog).

Who this course is for:
– For students who prefer to build a solid conceptual base before tackling specialized Azure Ai exams.
– Future advanced Azure Ai certification candidates who need to master the fundamentals first.
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