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Microsoft Certified: Azure AI Engineer Associate Certification Practice Test Questions, Microsoft Certified: Azure AI Engineer Associate Exam Dumps
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The Microsoft Certified: Azure AI Engineer Associate certification is designed to measure the abilities of the professionals to execute the technical tasks, such as analyzing solution requirements; designing solutions; integrating AI models into solutions; deploying and handling solutions. The candidates who successfully complete the Microsoft AI-100: Designing and Implementing an Azure AI Solution exam will be awarded this certificate.
The Microsoft Certified: Azure AI Engineer Associate certification and its qualifying exam are intended for Azure AI engineers. These are the specialists who are responsible for analyzing the prerequisites for AI solutions, giving recommendations on the relevant technologies & tools, designing as well as implementing AI solutions that satisfy scalability & performance requirements. They also translate the vision from the solution architects and collaborate closely with the data engineers, IoT specialists, software developers, and data scientists to design comprehensive end-to-end solutions.
There are no official prerequisites for the Microsoft Certified: Azure AI Engineer Associate certification. However, the applicants should be well versed in the exam topics before attempting the associated test. Apart from that, they should possess a solid understanding of how to use cognitive services, the familiarity with machine learning, as well as the ability to architect and implement Microsoft AI solutions that involve computer vision, speech, natural language processing, and conversational AI.
Additionally, the individuals pursuing the Microsoft Certified: Azure AI Engineer Associate certification need to have competency in designing as well as applying the AI agents and apps that utilize Azure Bot Service, Microsoft Azure Cognitive Services, data storage in the Azure platform, and Azure Cognitive Search. They should also be capable of recommending solutions that utilize open source technologies, be aware of the Azure AI portfolio components as well as the possible data storage options. Moreover, the students should understand when there is a necessity to create a custom API to satisfy certain requirements.
The Microsoft AI-100 exam is available in multiple languages, including English, Korean, Japanese, as well as Simplified Chinese. To register for the test, the candidates have to pay the fee of $165. The pricing for this certification exam depends on the country where it is taken. If you sit for the test in another country than the United States, this sum can vary for you. The examinees can expect around 40-60 questions in their delivery of the test and the allocated time for the completion of these questions is 180 minutes. The learners need to achieve the passing score of 700 points out of possible 1000 to pass the exam and get certified.
If a candidate fails to achieve this pass mark at the first attempt, he/she will have to wait for 24 hours before retaking the test. For the second and subsequent attempt, a 14-day waiting period is established. In total, the applicants can retake their exam 5 times per year.
The Microsoft AI-100: Designing and Implementing an Azure AI Solution exam encompasses a wide range of topics that the applicants should develop mastery in before attempting the test. Each of these domains includes a number of specific knowledge and skills. They are the following:
Topic 1. Analyzing solution requirements
This subject area makes up 25-30% of the exam content. Within this domain, the students are required to be capable of recommending Azure Cognitive Services APIs to satisfy business requirements. This includes choosing the processing architecture for a solution; choosing proper data processing technologies; choosing the proper AI services & models. The candidates should also have expertise in mapping security prerequisites to technologies, tools, as well as processes. The skills needed for that encompass determining processes & regulations necessary for conforming with data protection, privacy, as well as regulatory requirements; defining which groups and users have access to data as well as interfaces; defining proper devices for a solution; defining auditing requirements. Additionally, they should know how to choose storage, software, and services needed to support a solution.
Topic 2. Designing AI solutions
This section constitutes 40-45% of all the exam questions. The subtopics covered within this topic include designing solutions involving at least pipelines; designing solutions involving Cognitive Services (including speech, search, knowledge, vision, and anomaly detection APIs); designing solutions that utilize the Microsoft Bot Framework; designing compute infrastructure for supporting a solution; designing for data governance, security, compliance, and integrity.
Topic 3. Implementing & monitoring AI solutions
The questions related to this domain amount to 25-30% of the whole exam syllabus. In the framework of this objective, the test takers need to understand how to implement an AI workflow. This incorporates performing such technical tasks as developing AI pipelines; handling the flow of information via the solution elements; applying data logging processes; determining and constructing interfaces for custom AI services, among others. Moreover, the individuals will be tested based on their ability to Integrate AI services & solution components. This means that they should be capable of configuring prerequisite elements as well as input datasets to enable the consumption of Azure Cognitive Services APIs; customizing integration with Azure Cognitive Services; configuring the prerequisite elements to enable connectivity to the Microsoft Bot Framework. In addition, the examinees must have proficiency in monitoring as well as assessing the AI environment.
Artificial intelligence has become one of the leading technologies in the IT industry over recent years. The demand for the AI-related job roles is increasing at a very fast pace. Consequently, the demand for the Azure AI specialists is also rising all the time. This makes the Microsoft Certified: Azure AI Engineer Associate certification so valuable for the professionals who are seeking to pursue their careers in this field.
There are numerous job roles that the individuals holding this certification can take up. Some of the titles are as follows: an AI Engineer, a Machine Learning Engineer, a Senior Software Engineer (Applied Machine Learning), an AI Developer, a Senior Data Analytics, a Business Intelligence Engineer, a Senior Software Engineer (Data Engineering), a Data Scientist, and a Deep Learning Engineer. According to Glassdoor.com, the average remuneration that a certificate holder can earn is around $123,400 per year. However, if you already have some level of experience in the sphere or hold some additional certifications, you can get even more than this figure.
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