Skills at a glance
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Describe Artificial Intelligence workloads and considerations (15–20%)
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Describe fundamental principles of machine learning on Azure (15–20%)
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Describe features of computer vision workloads on Azure (15–20%)
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Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)
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Describe features of generative AI workloads on Azure (20–25%)
Describe Artificial Intelligence workloads and considerations (15–20%)
Identify features of common AI workloads
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Identify computer vision workloads
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Identify natural language processing workloads
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Identify document processing workloads
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Identify features of generative AI workloads
Identify guiding principles for responsible AI
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Describe considerations for fairness in an AI solution
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Describe considerations for reliability and safety in an AI solution
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Describe considerations for privacy and security in an AI solution
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Describe considerations for inclusiveness in an AI solution
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Describe considerations for transparency in an AI solution
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Describe considerations for accountability in an AI solution
Describe fundamental principles of machine learning on Azure (15-20%)
Identify common machine learning techniques
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Identify regression machine learning scenarios
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Identify classification machine learning scenarios
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Identify clustering machine learning scenarios
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Identify features of deep learning techniques
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Identify features of the Transformer architecture
Describe core machine learning concepts
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Identify features and labels in a dataset for machine learning
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Describe how training and validation datasets are used in machine learning
Describe Azure Machine Learning capabilities
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Describe capabilities of automated machine learning
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Describe data and compute services for data science and machine learning
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Describe model management and deployment capabilities in Azure Machine Learning
Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
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Identify features of image classification solutions
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Identify features of object detection solutions
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Identify features of optical character recognition solutions
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Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
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Describe capabilities of the Azure AI Vision service
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Describe capabilities of the Azure AI Face detection service
Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)
Identify features of common NLP Workload Scenarios
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Identify features and uses for key phrase extraction
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Identify features and uses for entity recognition
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Identify features and uses for sentiment analysis
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Identify features and uses for language modeling
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Identify features and uses for speech recognition and synthesis
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Identify features and uses for translation
Identify Azure tools and services for NLP workloads
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Describe capabilities of the Azure AI Language service
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Describe capabilities of the Azure AI Speech service
Describe features of generative AI workloads on Azure (20–25%)
Identify features of generative AI solutions
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Identify features of generative AI models
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Identify common scenarios for generative AI
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Identify responsible AI considerations for generative AI
Identify generative AI services and capabilities in Microsoft Azure
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Describe features and capabilities of Azure AI Foundry
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Describe features and capabilities of Azure OpenAI service
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Describe features and capabilities of Azure AI Foundry model catalog
