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About Azure AI Fundamentals Certification and Who It Is Intended for

The Microsoft Certified: Azure AI Fundamentals qualification authenticates the learner's understanding and skills in AI & ML concepts along with associated Azure services. In particular, the individual with this certification is competent in demonstrating their understanding of various workloads related to those terms along with their implementation in Azure cloud computing services. In addition, this certification is an excellent way to get a step ahead in the preparation for other role-based Azure certificates as well as showcasing one's skill in the fundamentals of ML as well as AI. All in all, the Azure AI Fundamentals validation form Microsoft is for beginners and thus, doesn't require any technical knowledge and expertise like, for example, engineering for software. However, some understanding of programming will help you a lot to easily nail test AI-900.

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How to book the AI-900: Microsoft Azure AI Fundamentals Exam

• Step 1: Visit to Microsoft Learning and search for AI-900: Microsoft Azure AI Fundamentals Exam Outlook and Modules.
• Step 2: Sign up/Login to Pearson VUE account.
• Step 3: Select local centre based on your country, date, time and confirm with a payment method.

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

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

As for this area, it includes the following:

• 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.
• 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.

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