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AI-900 Exam Overview - Microsoft Azure AI Fundamentals

Candidates for this exam should have foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.This exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.

This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial. Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.

Skill Measured

Describe AI workloads and considerations (15-20%)
Describe fundamental principles of machine learning on Azure (30-35%)
Describe features of computer vision workloads on Azure (15-20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
Describe features of conversational AI workloads on Azure (15-20%)

Domain 1: Describing AI workloads and considerations

• Identification of features in common AI workloads
• Identification of guiding principles for responsible AI

Domain 2: Describing fundamental principles of machine learning on Azure

• 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

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

• Identification of common types of computer vision solutions
• Identification of Azure tools and services for computer vision tasks

Domain 4: Describing features of Natural Language Processing (NLP) workloads on Azure

• Identification of features in common NLP workload scenarios
• Identifying Azure tools and services for NLP workloads

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

• Identification of common use cases for conversational AI
• Identifying Azure services for conversational AI