
AI-900 Microsoft Azure AI Fundamentals Exam Prep in 5 Hours
Course Description
Are you ready to earn your Microsoft Certified: Azure AI Fundamentals credential?
This course is your complete, up-to-date guide to passing the AI-900 exam โ covering every domain Microsoft tests, including the newest Generative AI and Azure OpenAI topics added in 2025.
The AI-900 exam is an opportunity to demonstrate knowledge of machine learning and AI concepts and related Microsoft Azure services โ and it's designed for both technical and non-technical backgrounds, with no data science or software engineering experience required. Microsoft Learn
Whether you're a business professional, IT consultant, student, or career-switcher, this course will take you from zero to certified.
What You'll Learn:
AI Workloads & Considerations โ understand common AI use cases and responsible AI principles
Machine Learning on Azure โ core ML concepts and Azure Machine Learning fundamentals
Computer Vision on Azure โ image classification, object detection, and Azure AI Vision services
Natural Language Processing (NLP) โ text analytics, translation, and Azure Language services
Generative AI โ Azure OpenAI Service, GPT models, Copilot, and responsible AI practices Microsoft Learn
Why This Course?
The 2025 version of the AI-900 has a new emphasis on Generative AI, with exam questions covering Azure OpenAI Service, GPT, Copilot, and responsible AI โ topics not always reflected in older practice materials. Medium This course is fully updated to cover all of it.
The AI-900 is one of the more accessible fundamentals exams, but you'll still want to be solid on machine learning types, responsible AI principles, generative AI use cases, computer vision, and Azure's language services. Pluralsight
Who This Course Is For:
IT professionals and cloud beginners wanting to break into AI
Business stakeholders and consultants seeking AI literacy
Students pursuing a Microsoft certification pathway
Anyone who wants a foundation before tackling the Azure AI Engineer Associate or Azure Data Scientist Associate
By the end of this course, you will:
Understand core AI and ML concepts on Azure
Know when and how to use each Azure AI service
Be fully prepared to sit and pass the AI-900 exam
Earn a globally recognised Microsoft certification
Once you pass, the certification doesn't expire โ and it provides a solid foundation for a career in AI or data on Microsoft Azure. P
Skills at a glance
Describe Artificial Intelligence workloads and considerations (15โ20%)
Describe fundamental principles of machine learning on Azure (15โ20%)
Describe features of computer vision workloads on Azure (15โ20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (15โ20%)
Describe features of generative AI workloads on Azure (20โ25%)
Describe Artificial Intelligence workloads and considerations (15โ20%)
Identify features of common AI workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify document processing workloads
Identify features of generative AI 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 (15-20%)
Identify common machine learning techniques
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Identify features of deep learning techniques
Identify features of the Transformer architecture
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 Azure Machine Learning capabilities
Describe capabilities of automated machine learning
Describe data and compute services for data science and machine learning
Describe model management and deployment capabilities in Azure Machine Learning
Describe features of computer vision workloads on Azure (15โ20%)
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
Describe capabilities of the Azure AI Vision service
Describe capabilities of the Azure AI Face detection service
Describe features of Natural Language Processing (NLP) workloads on Azure (15โ20%)
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
Describe capabilities of the Azure AI Language service
Describe capabilities of the Azure AI Speech service
Describe features of generative AI workloads on Azure (20โ25%)
Identify features of generative AI solutions
Identify features of generative AI models
Identify common scenarios for generative AI
Identify responsible AI considerations for generative AI
Identify generative AI services and capabilities in Microsoft Azure
Describe features and capabilities of Azure AI Foundry
Describe features and capabilities of Azure OpenAI service
Describe features and capabilities of Azure AI Foundry model catalog
This exam is an opportunity for you to demonstrate knowledge of machine learning and AI concepts and related Microsoft Azure services. As a candidate for this exam, you should have familiarity with Exam AI-900โs self-paced or instructor-led learning material.
This exam is intended for you if you have both technical and non-technical backgrounds. Data science and software engineering experience are not required. However, you would benefit from having awareness of:
Basic cloud concepts
Client-server applications
Save $84.99 ยท Limited time offer
Related Free Courses

ุงูุฐูุงุก ุงูุนุงุทูู ูููุงูุฏูู ูู ุงูุชุนุงู ู ู ุน ุงูุฃุทูุงู

The Best ChatGPT & AI Course: Make Money With AI

Wordpress (No Coding), Domain not Needed, within 3.5 hours

