


AI-900: Microsoft Azure AI Fundamentals is an essential course for anyone looking to gain a solid understanding of artificial intelligence and its applications in the Microsoft Azure platform. This course is designed to provide a comprehensive overview of AI concepts, tools, and services offered by Azure, making it an ideal starting point for beginners in the field.
AI-900 is a certification exam offered by Microsoft that validates the foundational knowledge of individuals in AI and its associated services on the Azure platform. It serves as a stepping stone for both technical and non-technical professionals who wish to gain a comprehensive understanding of AI and its implications.
This Practice Exam, you will learn the fundamentals of AI and how it can be leveraged to solve real-world problems. You will explore various AI technologies such as machine learning, natural language processing, computer vision, and more. The course covers the basics of Azure AI services, including Azure Cognitive Services, Azure Machine Learning, and Azure Bot Service, giving you a hands-on experience in building AI-powered applications.
Earning the AI-900 certification demonstrates proficiency in AI technologies and methodologies provided by Azure. It showcases an individual's ability to leverage AI tools and services to solve business problems effectively. This certification is highly valuable for professionals aiming to become data scientists, AI engineers, or solution architects.
AI-900 : Microsoft Azure AI Fundamentals Exam details :
Exam Name: Microsoft Certified - Azure AI Fundamentals
Exam Code: AI-900
Exam Price: $99 (USD)
Number of Questions: Maximum of 40-60 questions,
Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,
Length of Test: 60 Minutes. The exam is available in English and Japanese languages.
Passing Score: 700 / 1000
Languages : English, Japanese, Korean, and Simplified Chinese
Schedule Exam : Pearson VUE
AI-900 : Microsoft Azure AI Fundamentals Certification Exams skill questions:
Skill Measurement Exam Topics:-
Describe Artificial Intelligence workloads and considerations (20–25%)
Describe fundamental principles of machine learning on Azure (25–30%)
Describe features of computer vision workloads on Azure (15–20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
##) Describe Artificial Intelligence workloads and considerations (20–25%)
Identify features of common AI workloads
Identify features of anomaly detection workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify guiding principles for responsible AI
Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution
##) Describe fundamental principles of machine learning on Azure (25–30%)
Identify common machine learning types
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Describe core machine learning concepts
Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning Studio
Automated machine learning
Azure Machine Learning designer
##) Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
Identify capabilities of the Computer Vision service
Identify capabilities of the Custom Vision service
Identify capabilities of the Face service
Identify capabilities of the Form Recognizer service
##) Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
Identify features of common NLP Workload Scenarios
Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation
Identify Azure tools and services for NLP workloads
Identify capabilities of the Language service
Identify capabilities of the Speech service
Identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure
Identify features and uses for bots
Identify capabilities of Power Virtual Agents and the Azure Bot service
AI-900: Microsoft Azure AI Fundamentals is a valuable certification that equips individuals with essential knowledge and understanding of AI and its applications. With the increasing adoption of AI technologies, this certification opens doors to exciting career opportunities and enhances credibility in the rapidly evolving world of artificial intelligence. Whether you are a technical or non-technical professional, AI-900 can be a stepping stone towards building a successful career in AI. So, why wait? Start your AI journey today with AI-900 and unlock the possibilities of this transformative technology!