AI-900: Microsoft Azure AI Fundamentals Video Course + Ques

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Prix: $24.99

Should you take AI-900 Exam?

Artificial intelligence and machine learning are all set to dictate the future of technology. The focus of Microsoft Azure on machine-learning innovation is one of the prominent reasons for the rising popularity of Azure AI. Donc, many aspiring candidates are looking for credible approaches for the AI-900 exam preparation that is a viable instrument for candidates to start their careers in Azure AI.

The interesting fact about the AI-900 certification is that it is a fundamental-level certification exam. Donc, candidates from technical as well as ones with non-technical backgrounds can pursue the AI-900 certification exam. en outre, there is no requirement for software engineering or data science experience for the AI-900 certification exam.

The AI-900 certification can also help you build the foundation for Azure AI Engineer Associate or Azure Data Scientist Associate certifications.

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What includes in this course?

• 8+ heures. of content, Test de pratique, quiz, etc.

• PPT, Demo resources, and other study material

• Accès à vie complet

• Certificat de fin de cours

• 30-days Money-Back Guarantee

• This course has more than enough practice questions to get you to prepare for the exam.

• Even though there are no labs in the exam, I have practically demonstrated concepts wherever possible to make sure you feel confident with concepts.

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Exam Format and Information

Nom de l'examen Exam AI-900: Principes fondamentaux de l'IA de Microsoft Azure

Durée de l'examen 60 Minutes

Type d'examen Multiple Choice Examination

Nombre de questions 40 – 60 Des questions

Exam Fee $99

Eligibility/Pre-requisite Aucun

Exam validity 1 année

Exam Languages Anglais, Japonais, coréen, et chinois simplifié

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The AI-900 exam covers the following topics:

• Describe AI workloads and considerations (15-20%)

• Décrire les principes fondamentaux de l'apprentissage automatique sur Azure (30-35%)

• Décrire les fonctionnalités des charges de travail de vision par ordinateur sur Azure (15-20%)

• Décrire les fonctionnalités du traitement automatique du langage naturel (PNL) charges de travail sur Azure (15-20%)

• Décrire les fonctionnalités des charges de travail d'IA conversationnelles sur Azure (15-20%)

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Exam Topics in detail

Domaine 1: Describing AI workloads and considerations

The subtopics in this domain include,

• Identification of features in common AI workloads

• Identification of guiding principles for responsible AI

Domaine 2: Describing fundamental principles of machine learning on Azure

The subtopics in this domain include,

• Identification of common machine learning variants

• Description of core machine learning concepts

• Identification of core risks in the creation of a machine learning solution

• Description of capabilities of no-code machine learning with Azure Machine Learning

Domaine 3: Description of features in computer vision workloads on Azure

The subtopics in this domain include,

• Identification of common types of computer vision solutions

• Identification of Azure tools and services for computer vision tasks

Domaine 4: Describing features of Natural Language Processing (PNL) charges de travail sur Azure

The subtopics in this domain are as follows,

• Identification of features in common NLP workload scenarios

• Identifying Azure tools and services for NLP workloads

Domaine 5: Description of features of conversational AI workloads on Azure

The subtopics in this domain include,

• Identification of common use cases for conversational AI

• Identifying Azure services for conversational AI

Bon apprentissage!!

Eshant Garg