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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
  • Processing and Classifying Images with Azure Cognitive Vision Services
  • Processing and Translating Speech with Azure Cognitive Speech Services
  • Evaluating Text with Azure Cognitive Language 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.

The benefit in Obtaining the AI-100 Exam Certification

  • Becoming Microsoft Certified Azure AI Engineer Associate means one thing you are worth more to the company and therefore more to yourself in the form of an upgraded pay package. On average a Microsoft Certified Azure AI Engineer Associate member of staff is estimated to be worth 30% more to a company than their uncertified professionals.
  • When Candidates applying for a job or looking to promotion in their current position, a Microsoft Certified Azure AI Engineer Associate certification in the field in which Candidates are applying will put you at the top of the list and make them a desirable candidate for employers.
  • Candidates will get in-depth knowledge by completing the courses along with the access to revision materials for 6 months upon completion means they will have a wider skill set when it comes to the various technologies and systems than an uncertified professional. Certified Professional in this particular skill set is 74% more efficient when it comes to completing their tasks in a timely well-executed manner.
  • Organization owners invest a lot in their employees when it comes to their training with the goal of making them quicker, more efficient, and more knowledgeable about their role. Certified Professional will reduce the time he spends on tasks, meaning he can get more done this could help reduce company downtime when repairing faults on a system or fixing hardware problems.
  • After completion of Microsoft Certified Azure AI Engineer Associate Candidates receive official confirmation from Microsoft that you are now fully certified in their chosen field. This can be now added to their CV, cover letters and job applications.

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How much AI-100 Exam Cost

The price of the AI-100 exam is $165 USD.

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

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.

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Microsoft AI-100日本語 Exam Syllabus Topics:

SectionObjectives
Implement Computer Vision Solutions- Image analysis and processing
  • 1. Custom Vision training and deployment
    • 2. Computer Vision API usage
      Responsible AI and Monitoring- AI ethics and governance
      • 1. Model monitoring and evaluation
        • 2. Responsible AI principles
          Implement Natural Language Processing (NLP)- Text analytics solutions
          • 1. Sentiment analysis
            • 2. Key phrase extraction
              - Language understanding solutions
              • 1. Entity extraction
                • 2. Intent recognition
                  Implement Knowledge Mining and Search Solutions- Azure Cognitive Search
                  • 1. Skillsets and enrichment pipeline
                    • 2. Indexing and querying data
                      Design AI Solutions on Azure- Design conversational AI solutions
                      • 1. Language understanding (LUIS concepts)
                        • 2. Azure Bot Service architecture
                          - Select appropriate Azure AI services
                          • 1. Azure Cognitive Services selection
                            • 2. Knowledge mining solutions
                              • 3. Azure Machine Learning integration

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