AI-900: Microsoft Azure AI Overview
Learn how to identify common AI workloads, apply responsible AI principles, understand machine learning concepts, and recognize the Azure services used for vision, language, speech, document processing, and generative AI solutions.
Curriculum Areas
- Describe Artificial Intelligence workloads and considerations
- Describe fundamental principles of machine learning on Azure
- Describe fe atures of computer vision workloads on Azure
- Describe features of Natural Language Processing (NLP) workloads on Azure
- Describe features of generative AI workloads on Azure
AI-900: Microsoft Azure AI Curriculum
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
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
Identify common types of computer vision solutions
- 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
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
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 the Azure AI Foundry model catalog