Candidates for this exam should have subject matter expertise using cognitive services, machine learning, and knowledge mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, and conversational AI.
Responsibilities for an Azure AI Engineer include analyzing requirements for AI solutions, recommending the appropriate tools and technologies, and designing and implementing AI solutions that meet scalability and performance requirements.
Azure AI Engineers translate the vision from solution architects and work with data scientists, data engineers, IoT specialists, and software developers to build complete end-to-end solutions.
A candidate for this exam should have knowledge and experience designing and implementing AI apps and agents that use Microsoft Azure Cognitive Services, Azure Bot Service, Azure Cognitive Search, and data storage in Azure. In addition, a candidate should be able to recommend solutions that use open source technologies, understand the components that make up the Azure AI portfolio and the available data storage options, and understand when a custom API should be developed to meet specific requirements.
- Analyze solution requirements (25-30%)
- Design AI solutions (40-45%)
- Implement and monitor AI solutions (25-30%)
Exam AI-100: Skills Outline
In this session we will break down the Objective Domains and information supporting those Objective Domains in order to prepare for the AI-100 Exam. AI-100 is a great exam...