Preparation Process

Microsoft offers a wide range of resources to help you prepare for your certification exam. The first step in the preparation process is to go through the topics in detail. This will enable you to understand the specific areas that are covered in the test. With this understanding, you can start to get the materials that will provide more knowledge on the objectives. Thus, Microsoft comes with two training options to help the candidates develop the required skills. These are free online training and instructor-led training.

• Free Online Training: The individuals can explore five free training tutorials that are available on the official exam webpage. They have a series of modules that focus on the specific domains of the test. These training tutorials are recommended for those candidates who are comfortable with the self-paced study. The topics of these manuals include the following options:
  • Get Started with AI on Azure;
  • Create No-Code Predictive Models with Azure ML;
  • Explore NLP;
  • Explore Computer Vision on Microsoft Azure;
  • Explore Conversational Artificial Intelligence.

  The students can find the details of these learning paths on the official website.

• Practice Test: As a future examinee, you also have access to the official practice test to evaluate your understanding of the exam topics before taking the actual test. The link to this training tool can be found on the Microsoft website.
• Instructor-Led Training: The Microsoft Azure AI Fundamentals course is designed to help you gain the required skills to pass the exam and obtain the certification. It introduces the learners to the fundamental concepts of AI and the services available in Microsoft Azure that are useful in creating AI solutions. This training is delivered by the certified partners and its details can be found on the Microsoft website. It is important to mention that this course is designed to be combined with other online materials that are available on the Microsoft Learning platform.

Certification Topics of Microsoft AI-900 Exam

Our Microsoft AI-900 exam dumps covers the following objectives of Microsoft AI-900 Exam.

• Describe AI workloads and considerations (15-20%)
• Describe features of conversational AI workloads on Azure (15-20%)
• Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
• Describe fundamental principles of machine learning on Azure (30-35%)
• Describe features of computer vision workloads on Azure (15-20%)

Objective of Microsoft AI-900 Exam

It's important to note that the Microsoft AI-900 exam isn't an exam on Azure; the objective of the exam is to make sure you know how to build and manage intelligent cloud solutions and services on Azure. Foundation to Azure, or you can still get the certificate. Defined best practices for solution design, deployment, and administration. Identity of Azure services. Conclude testing by connecting the solution to the infrastructure to test for functionality. Instructor for the exam has extensive experience with Azure. Textidentify Azure services. Define identity of Azure services. Rewarding in the form of free exam vouchers and in-demand credential. Microsoft AI-900 exam dumps prepare you to become qualified Azure solutions specialist. Focus on the skills that are of high value in your organization. Bots are an important part of this exam.

Pay special attention to Cloud design principles. Terms used to describe the Azure platform. Standing out in the crowd and getting the job you want. Regular updates by Microsoft experts. Space for comments with every question. Sources for determining Azure pricing. Document your approach to meeting your goals. Positive impact of the exam on your career path.

Describe the Basic Principles of ML on Microsoft Azure (30-35%)

As for this area, it includes the following:

• Describe the ML core concepts – You should be able to identify the labels and features within a dataset for ML and describe the usage of validation datasets and training in ML. The applicants also need the ability to explain the usage of ML algorithms in model training, as well as interpret and choose the model evaluation yardsticks for regression and classification.
• Explain the abilities of the No-code ML with Azure ML Learning Studio – This domain equips the individuals with the knowledge of the Azure ML designer and automated ML UI.
• Identify the basic ML types – This section equips the learners with the ability to identify various concepts, such as regression, clustering, and classification ML scenarios.
• Identify the major tasks in crafting an ML solution – This subject area measures the students’ competence in explaining some concepts, such as basic features of data preparation and ingestion, model management and deployment, model training & evaluation, and feature selection and engineering.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

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