Define and prepare the development environment (15-20%)ĭP-200: Implementing an Azure Data SolutionĬandidates for this exam are Microsoft Azure data engineers who collaborate with business stakeholders to identify and meet the data requirements to implement data solutions that use Azure data services.Candidates typically have background in mathematics, statistics, and computer science. Candidates serve as part of a multi-disciplinary team that incorporates ethical, privacy, and governance considerations into the solution. Candidates use applications that involve natural language processing, speech, computer vision, and predictive analytics. Candidates use machine learning techniques to train, evaluate, and deploy models to build AI solutions that satisfy business objectives. Implement and monitor AI solutions (25-30%)ĭP-100: Designing and Implementing a Data Science Solution on AzureĬandidates for this exam apply scientific rigor and data exploration techniques to gain actionable insights and communicate results to stakeholders.Candidates understand when a custom API should be developed to meet specific requirements. Candidates implement AI solutions that use Cognitive Services, Azure bots, Azure Search, and data storage in Azure. Candidates understand the components that make up the Azure AI portfolio and the available data storage options.
Candidates can recommend solutions that use open source technologies. Candidates design and implement AI apps and agents that use Microsoft Azure Cognitive Services and Azure Bot Service. Candidates translate the vision from solution architects and work with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end solutions.
AI-100: Designing and Implementing an Azure AI SolutionĬandidates for this exam analyze the requirements for AI solutions, recommend appropriate tools and technologies, and implements solutions that meet scalability and performance requirements.
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