Microsoft Designing and Implementing an Azure AI Solution (AI-100日本語版) : AI-100日本語

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Skills Measured

There are various topics that you will need to study to achieve success in the Microsoft AI-100 exam. All the domains included in this certification tests are as follows:

The first subject area that you will have to master is called Analyzing Solution Requirements. It makes up 25-30% of the exam content and consists of the following subdomains: recommending Azure Cognitive Services APIs to satisfy business requirements; mapping security requirements to tools, technologies, as well as processes; selecting the software, services, and storage necessary for supporting a solution.

The next section that you have to study is Designing an AI Solution that constitutes about 40-45% of the exam questions. It revolves around the subtopics, such as designing solutions that comprise one or more pipelines; designing solutions that utilize Cognitive Services; designing solutions that implement the Microsoft Bot Framework; designing the compute infrastructure to support a solution; designing for data governance, compliance, integrity, as well as security.

The last domain included in the Microsoft AI-100 exam is titled Implementing & Monitoring AI Solutions. It makes up the remaining 25-30% of the whole content. The subtopics covered here are the following: implementing an AI workflow; integrating AI services & solution elements; monitoring and assessing the AI environment.

Reference: https://www.microsoft.com/en-us/learning/exam-ai-100.aspx

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AI-100 Exam topics

Candidates must know the exam topics before they start of preparation. Because it will really help them in hitting the core. Our AI-100 exam dumps will include the following topics:

• Integrate AI models into solutions 25-30%
• Design solutions 30-35%
• Deploy and manage solutions 20-25%
• Analyze solution requirements 20-25%

Exam AI-100: Designing and Implementing an Azure AI Solution

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.

Part of the requirements for: none

Download exam skills outline

Microsoft AI-100日本語 Exam Syllabus Topics: