The course will include the below exam concepts:
Describe Artificial Intelligence workloads and considerations (15–20%)
Identify features of common AI workloads
Identify features of data monitoring and anomaly detection workloads
Identify features of content moderation and personalization workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify document intelligence 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 (20–25%)
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
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 (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
Describe capabilities of the Azure AI Vision service
Describe capabilities of the Azure AI Face detection service
Describe capabilities of the Azure AI Video Indexer service
Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)
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 capabilities of the Azure AI Translator service
Describe features of generative AI workloads on Azure (15–20%)
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 capabilities of Azure OpenAI Service
Describe natural language generation capabilities of Azure OpenAI Service
Describe code generation capabilities of Azure OpenAI Service
Describe image generation capabilities of Azure OpenAI Service
I hope you find the course useful,
If you need any assistance please message me,
Happy learning!
Thanks,
Neil