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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
Reference: https://www.microsoft.com/en-us/learning/exam-ai-100.aspx
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Preparation Process
If you are planning to take the Microsoft AI-100 exam, it is very important that you prepare for it thoroughly. It doesn’t matter if you have a lot of experience in the field because if you don’t study for this certification test, there is a big chance that you will not be able to pass it. To prepare for the AI-100 exam, the first thing that every candidate needs to do is visit the official website. Here you will find a plethora of reliable resources that will convey all the authentic information to you. On this online platform, you will also find a few free learning paths that will allow you to understand all the details of your Microsoft test. These paths are as follows:
- Creating Intelligent Bots with the Azure Bot Service
- Evaluating Text with Azure Cognitive Language Services
- Processing and Classifying Images with Azure Cognitive Vision Services
- Processing and Translating Speech with Azure Cognitive Speech Services
After that, you can also enroll for the paid instructor-led training course available on the official website. As the name suggests, it is taught by a certified expert who knows everything about the topic. It is recommended that the learners use this resource as it will give them a chance to interact with the instructor and ask questions whenever they face difficulties.
One of the last things that every student needs to do is look for the valid practice tests. The Internet is littered with this training tool, so it is advised that the individuals take at least several of those tests. In this way, you will learn a lot about the exam questions and improve your time management skills.
How to book the AI-100 Exam
These are following steps for registering the AI-100 exam. Step 1: Visit to Microsoft Exam Registration Step 2: Signup/Login to MICROSOFT account Step 3: Search for MICROSOFT AI-100 Certifications Exam Step 4: Select Date and Center of examination and confirm with payment value of $165
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Microsoft AI-100 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design AI Solutions | 40-45% | - Design natural language processing solutions - Design conversational AI and bot solutions - Integrate open-source and custom AI components - Design computer vision solutions - Select appropriate Azure Cognitive Services - Design knowledge mining and search solutions |
| Topic 2: Implement and Monitor AI Solutions | 25-30% | - Monitor performance, usage, and health - Maintain and update AI solutions - Deploy AI solutions to Azure infrastructure - Configure security and access controls - Integrate AI models and services into applications |
| Topic 3: Analyze Solution Requirements | 25-30% | - Assess security, compliance, and governance needs - Identify business and technical requirements - Evaluate data storage and processing options - Define solution performance and scalability criteria |
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