Microsoft AI-100 Practice Test Questions, Microsoft AI-100 Exam Dumps

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The Microsoft AI-100: Designing and Implementing an Azure AI Solution certification exam evaluates the expertise of the candidates in analyzing the solution prerequisites, incorporating the AI models into different solutions, designing solutions, and managing & deploying solutions. The target audience for this test is majorly Azure AI Engineers. These professionals have the relevant skills in the use of machine learning, cognitive services, and knowledge mining for the implementation and architecture of Microsoft solutions that involve natural language processing, conversational AI, computer vision, and speech. The intended individuals have the responsibilities of analyzing the requirements for artificial intelligence solutions, designing & implementing artificial intelligence solutions that fulfill performance and scalability requirements. They also have the skills in recommending the relevant technologies and tools.

Although the certification exam does not have any official prerequisites, the candidates should have the expertise in the design & implementation of artificial intelligence applications and agents that utilize Azure Bot Service, data storage in Azure, Azure Cognitive Search, and Microsoft Azure Cognitive Services. Additionally, they should possess the competence in advising on the solutions that utilize open source technologies and also a good understanding of the elements that make up an Azure artificial intelligence portfolio. Passing this test leads to the award of the Microsoft Certified: Azure AI Engineer Associate certificate.

Exam Details

The Microsoft AI-100 test is the only exam required to obtain the Microsoft Certified: Azure AI Engineer Associate certification. It can be taken in English, Korean, Japanese, or Simplified Chinese. To register for the test, the students have to pay the fee of $165, which applies to one sitting of the exam. The applicants who do not achieve the passing score of 700 points out of 1000 will need to retake the test to qualify for the certificate. The questions that are administered in the exam vary from 40 to 60 and cover different formats. They include fill-in-the-blank, drag and drop, performance-based, multiple choice, build list, and active screen, among others. The learners can sit for the test at any Pearson VUE center around them or take it online.

The candidates preparing for the test are advised to take the official instructor-led training course, Designing and Implementing an Azure AI Solution, to gain the required knowledge and skills. The learners who participate in this course are equipped with the ability to design an Azure IA solution through the development of customer support chat Bot with the use of AI from the Microsoft Azure platform. It includes an understanding of the language as well as the pre-built AI functionality with Azure Cognitive Services. This instructor-led training is a paid option but the students can also explore four free learning paths to get the expertise in the domains of the certification exam. They should also go through the official practice test or alternative mock exams from other training sources to boost their competence in the topics of Microsoft AI-100.

Exam Topics

One of the best ways to improve performance in the Microsoft AI-100 test is to gain competence in the skills areas that are covered in the exam syllabus. The highlights of these topics are enumerated below:

Evaluate Solution Obligations: 25-30%

• Suggest Azure Cognitive Service APIs that can fulfill the business requirements: It covers one’s competence in choosing the relevant data processing technologies, relevant AI services, and models, and processing architecture for the solution. The test takers should also be able to establish the technologies and elements needed for connecting service endpoints and automation prerequisites.
• Map the security prerequisites to processes, technologies, and tools: It requires your skills in establishing the regulations & processes required to match data privacy, regulatory requirements, and protection. It also requires the ability to establish the relevant tools and services for solutions as well as integration points with different Microsoft services.

Design Artificial Intelligence Solutions: 40-45%

• Design specific solutions that cover at least one pipeline: It includes designing a strategy for egress and ingests data, integration points between different pipelines and workflows, pipeline utilizing AI applications, and pipelines calling Azure ML models.
• Design specific solutions implementing Microsoft Bot Frameworks: It requires that the candidates demonstrate their skills in integrating AI solutions & bots, designing bots that combine with channels, designing bot services using LUIS, incorporating bots with Azure Application Insights and Azure app services.
• Design for data security, integrity, compliance, and governance: It covers the individuals’ skills in defining how applications and users can authenticate to artificial intelligence services and ensuring the relevant data governance and that data conforms to compliance the prerequisites as defined by an organization.
• Design compute infrastructures for supporting solutions: It includes the applicants’ skills in establishing whether to develop a CPU, FPGA, or GPU-based solution or not; establishing whether to utilize hybrid, on-premises, or Cloud-based compute infrastructure or not; choosing the compute solution that fulfills cost constraints.

Monitor & Implement AI Solutions: 25-30%

• Implement AI workflow: It requires that the students demonstrate their skills in developing artificial intelligence pipelines, implementing data logging procedures, managing data flow through solution components, developing streaming solutions, creating solution endpoints, establishing and constructing interfaces for custom artificial intelligence services.
• Incorporate solution components and AI services: It covers the competence for configuring input datasets and prerequisite components that enable Azure Cognitive Services APIs consumption, configuring Azure Cognitive Services configuration, as well as implementing Azure Cognitive Search within solutions.
• Evaluate & monitor the artificial intelligence environment: It requires that the examinees suggest changes to AI solutions according to data performance. It also covers their skills in monitoring the components of AI for availability, maintaining AI solutions for continuous improvement, establishing the variations between actual and expected workflow throughput.

Career Path

The professionals who pass the Microsoft AI-100 exam are awarded the Microsoft Certified: Azure AI Engineer Associate certification. With this certificate, they can build a mid-level career as Azure AI Engineers. This career path is highly lucrative and with this associate-level certification, it becomes easier to climb the corporate ladder in the industry. As an Azure AI Engineer, you can earn an average of $172,000 per annum. Some of the job roles that the certified individuals can also apply for include a Cloud Operations Engineer, a System Verification Engineer, a Senior BI Engineer, a Software Engineer, a Technology Implementation Engineer, a Data Scientist, a Cloud Engineer, or a DevOps Engineer.

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